Green Finance Framework J U N E 2 0 2 0 Contents PART 1 Creating a Water-Secure World 1 1.1 Company Overview 1 1.2 Approach to Sustainability 3 PART 2 Green Finance Framework 9 2.1 Use of Proceeds 10 2.2 Process for Project Evaluation and Selection 13 2.3 Management of Proceeds 14 2.4 Reporting 15 2.5 External Review 16 Annex 17 XYLEM GREEN FINANCE FRAMEWORK 1 PART 1 Creating a Water-Secure World 1.1 Company Overview Xylem Inc., together with its subsidiaries (“Xylem” or the “Company”), with 2019 revenues of $5.2 billion and approximately 16,300 employees, is a leading global water technology company. The Company designs, manufactures and services highly engineered products and solutions ranging across a wide variety of critical applications primarily in the water sector, but also in electric and gas. Xylems broad portfolio of products, services and solutions addresses customer needs across the water cycle, from the delivery, measurement and use of drinking water to the collection, testing, analysis and treatment of wastewater to the return of water to the environment. XYLEM GREEN FINANCE FRAMEWORK 1 XYLEM GREEN FINANCE FRAMEWORK 2 Xylem has three reportable business segments that are aligned around the critical market applications they provide: Water Infrastructure, Applied Water, and Measurement enable water operators and communities to build resilience by helping prevent stormwater pollution and lower greenhouse gas emissions; and improve water affordability by helping water operators reduce water losses and optimize water system assets. Xylem is harnessing the power of data, analytics and decision intelligence to transform water management and deliver powerful water, energy and cost savings for its customers and the communities they serve. Building a Sustainable Company: Xylem knows that in order to be a company that advances sustainability, we have to be a company with a strong financial foundation that executes with discipline today while also focusing on the future. Xylem operates its business with integrity, minimizing its environmental footprint, ensuring the safety of its people and quality of its products, promoting an inclusive and diverse culture, and partnering with suppliers and organizations that share its values. The Company still has much to do but is fully committed to this purpose. Empowering Communities: Xylem creates social value by providing water- related disaster relief expertise, technology and equipment to communities in need; educating and raising awareness about water challenges; inspiring the next generation of water stewards; and tapping into the passion of its workforce and stakeholder volunteers to give time to local water-related causes. XYLEM GREEN FINANCE FRAMEWORK 5 Sustainability Reporting An important aspect of the overall approach to sustainability is our reporting. The Company reports extensively on its sustainability performance. Its 2019 Sustainability Report was prepared in accordance with GRI Standards. Material Topics for Xylem To advance its sustainability strategy, Xylem conducts a periodic materiality assessment to identify and prioritize issues deemed most important by its stakeholders and the business. The 2018 assessment resulted in the categorization of material topics into three key areas: Opportunities for Differentiation Issues that Warrant Close Attention Issues to Monitor BUSINESS EXPOSURE TO NATURAL DISASTER POLITICAL, SOCIAL Give 1% company profits to water-related causes and education Xylem set ambitious new sustainability goals aligned to the three key pillars of its sustainability strategy, called the 2025 Sustainability Goals XYLEM GREEN FINANCE FRAMEWORK 8 Given that sustainability is core to Xylems business strategy, the Company has sought to align its financing with its overall sustainability profile Alignment to the UN Sustainable Development Goals Xylem aligns its sustainability efforts with the United Nations Sustainable Development Goals (“SDGs”), a universal call to action to end poverty, protect the planet and ensure that all people enjoy peace and prosperity by 2030. The full SDG mapping is provided in Table 4 of the Annex. Sustainability Governance The Board, primarily through the Nominating and Governance Committee, provides oversight of the overall approach to sustainability, corporate responsibility and social value creation. The Xylem Environmental, Social and Governance Committee assesses strategic sustainability issues, seeks to improve sustainability performance, provides recommendations to Xylems SVP, General Counsel or (b) provides adaptation solutions that () contribute substantially to preventing or reducing the risk of the adverse impact of the current climate and the expected future climate on people, nature or assets, without increasing the risk of an adverse impact on other people, nature or assets. Article 12.1 (a)Protecting the environment from the adverse effects of urban and industrial waste water discharges, including from contaminants of emerging concern such as pharmaceuticals and microplastics, for example by ensuring the adequate collection, treatment and discharge of urban and industrial waste waters; Article 12.1 (b)Protecting human health from the adverse impact of any contamination of water intended for human consumption by ensuring that it is free from any micro-organisms, parasites and substances that constitute a potential danger to human health as well as increasing peoples access to clean drinking water; Article 12.1 (c)Improving water management and efficiency, including by protecting and en- hancing the status of aquatic ecosystems, by promoting the sustainable use of water through the long-term protection of available water resources, including through measures such as water reuse, by ensuring the progressive reduction of pollutant emissions into surface water and groundwater, by contributing to mitigating the effects of floods and droughts, or through any other activity that protects or improves the qualitative and quantitative status of water bodies. * Position of the Council at first reading with a view to the adoption of a REGULATION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on the establishment of a framework to facilitate sustainable investment, and amending Regulation (EU) 2019/2088 - Adopted by the Council on 15 April 2020 ST 5639 2020 REV 2, https:/eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CONSIL:ST_5639_2020_REV_2&qid=1591466733873&from=EN Annex XYLEM GREEN FINANCE FRAMEWORK 19 Disclaimer This document is intended to provide non-exhaustive, general information. This document may contain or incorporate by reference public information not separately reviewed, approved or endorsed by Xylem and accordingly, no representation, warranty or undertaking, express or implied, is made and no responsibility or liability is accepted by Xylem as to the fairness, accuracy, reasonableness or completeness of such information. This document contains information that may constitute “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-look- ing statements by their nature address matters that are, to different degrees, uncertain. Generally, the words “anticipate,” “estimate,” “expect,” “project,” “intend,” “plan,” “contemplate,” “predict,” “forecast,” “believe,” “target,” “will,” “could,” “would,” “should,” “potential,” “may” and similar expressions identify forward-looking statements. However, the absence of these words or similar expressions does not mean that a statement is not forward-looking. These forward-looking statements include any statements that are not historical in nature, including any statements about the capitalization of the company, future strategic plans and other statements that describe the companys business strat- egy, outlook, objectives, plans, intentions or goals. All statements that address events or developments that we expect or anticipate will occur in the future are forward-looking statements. Forward-looking statements involve known and unknown risks, uncertainties and other important factors that could cause actual results to differ materially from those expressed or implied in, or reasonably inferred from, such forward-looking statements. Many of these risks and uncertainties are currently amplified by and may continue to be amplified by, or in the future may be amplified by, the novel coronavirus (covid-19) pandemic. Xylem has no obligation, and undertakes no obligation, to update, modify or amend this document, the statements contained herein to reflect actual changes in assumptions or changes in factors affecting these statements or to otherwise notify any addressee if any information, opinion, projection, forecast or estimate set forth herein changes or subsequently becomes inaccurate. This document is not intended to be and should not be construed as providing legal or financial advice. It does not constitute an offer or invitation to sell or any solicitation of any offer to subscribe for or purchase or a recommendation regarding any securities, nothing contained herein shall form the basis of any contract or commitment whatsoever and it has not been approved by any security regulatory authority. The distribution of this document and of the information it contains may be subject of legal restrictions in some countries. Persons who might come into possession of it must inquire as to the existence of such restrictions and comply with them. The recipient is solely liable for any use of the information contained herein and Xylem shall not be held responsible for any damages, direct, indirect or otherwise, arising from the use of this document by the recipient. 2020 XYLEM, INC. All RIGHTS RESERVED
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Sustainable Finance in Asia Pacific Regulatory State of Play 3 March 2020 Page 2 Disclaimer The inf.
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Green Finance Impact Report 2020 2020 Green Finance Impact Report 3 Table of Contents Introduction . 2 Key highlights . 3 Summary of green metrics . 4 Macquaries green financing transactions . 6 Approach . 8 Green impact . 11 Macquarie and green investment . 12 Glossary . 16 Appendix 1: GIG Green Impact Report . 17 Appendix 2: PWC Assurance Report . 29 2020 Green Finance Impact Report 2 Introduction Macquarie Group Limited (“Macquarie or MGL”) is pleased to present its Green Finance Impact Report for the twelve months to 31 March 2020. This report relates to the MGL 2018 2,100 million loan facility of which 500 million constitutes as green financing (“green tranches”). It provides information on the environmental benefits (“green impact”) of the eligible projects1 which have been notionally allocated2 green tranche financing. MGL is also pleased to note it has raised its second green financing transaction in March 2020, a US$300 million Samurai loan facility in the Japanese market of which US$150 million constitutes as green financing. This loan was not drawn at the 31 March reporting period and is not covered by this report. The approach presented in this report is consistent with Macquaries Green Finance Framework (“GFF”) which was developed in accordance with the APLMA3 Green Loan Principles. Macquarie has utilised the expertise of its Green Investment Group (“GIG”) Green Investment Ratings team to demonstrate the green impact of its eligible projects. The full Impact Report is available in Appendix 1. Macquaries GIG is a specialist in green infrastructure principal investment, project development and delivery, green impact advisory and the management of portfolio assets. Its track record, expertise and capability make it a global leader in green investment and development, dedicated to accelerating the transition to a greener global economy. 1 See glossary for definition of eligible project 2 See glossary for definition of notional allocation. 3 Asia Pacific Loan Market Association. 2020 Green Finance Impact Report 3 Key highlights 500m of green financing drawn at March 31 from 19 financiers across the globe GIG Carbon Score: 3,462 AA The portfolio is forecast to produce over 8,000 GWh per year enough to power over 1.9 million households for a year6 The Green Finance Framework has been developed in accordance with the APLMA Green Loan Principles Over 2,400 MW of renewable energy capacity generated from the eligible projects allocated to, in development, construction and operation The portfolio4 is forecast to avoid greenhouse gas emissions of 3,462kt CO2e per year equivalent to taking over 1.1 million cars off the road5 Independent Assurance provided by PwC over Macquaries compliance with the Green Finance Framework 13 projects were allocated funding from the green tranches during the reporting period 4 The portfolio refers to the 13 eligible projects which were allocated green financing throughout the reporting period. 5 Year on year increase in cars off the road is not due to change in portfolio but rather due to the updated conversion factor calculated using a petrol car based on data from UK Government Greenhouse gas reporting conversion factors. See www.gov.uk/government/collections/government-conversion-factors-for-company-reporting for further detail. 6 Calculated using the average household electricity data for the relevant country of the underlying projects available from the World Energy Council, and based on 2014 data (see https:/www.worldenergy.org/data/). 2020 Green Finance Impact Report 4 Summary of green metrics Throughout the reporting period 13 projects were allocated funding from the green tranches, delivering a significant green impact and achieving a Carbon Score of 3,462 AA. Throughout this report the green impact and associated metrics: 1. incorporate all the eligible projects which have been notionally allocated green tranche financing from 1 April 2019, to 31 March 2020 (the “portfolio”). This is in line with the Green Loan Principles and allows full transparency and disclosure of each project that has been supported by the green tranches. 2. reflect the total green impact derived from 100% of those projects that have been notionally allocated green tranche financing, and not just the proportional impact of the green tranches. This approach has been adopted, as the GFFs Management of proceeds described on page 9 does not support proportional allocation due to the revolving allocation of the use of proceeds (i.e. as above, projects may not necessarily be supported by the facility for the entire reporting period). GIG Carbon Score The GIG Carbon Score is GIGs standard mark for communicating the impact of low carbon infrastructure in helping to reduce greenhouse gas emissions. While other measures of GHG emissions only consider the emissions produced during a projects operational phase, the GIG Carbon Score also considers the emissions across the projects entire lifecycle. The rating shows the aggregated GIG Carbon Score for Macquaries green tranches is 3,462 AA. The rating of AA reflects the low lifecycle carbon intensity of the wind and solar power projects notionally allocated funding (see page 7), and the mix of project locations in lower carbon intensive grids (e.g. UK and Sweden) and higher carbon grids (e.g. Taiwan and Poland). Projects located in countries with higher carbon intensive grids achieve higher ratings, reflective of the effectiveness of GHG emissions reduction. The GIG Carbon Score also shows the quantified greenhouse gas emissions avoided (3,462 kt CO2e/yr), which indicates the portfolio lifecycle emissions avoided relative to the counterfactual (a scenario in which the projects were not built).7 This globally applicable approach allows investors to compare the relative performance of projects using an emissions avoided measure. Full details of the GIG Carbon Score methodology is provided within the Green Impact Report in Appendix 1. 7 For renewable energy projects, the GIG Carbon Score is a measure of a projects lifecycle GHG emissions compared to the emissions of energy taken from the local grid. AAA AA A B C D E GIG CARBON SCORE kt CO2e AVOIDED (ANNUAL AVERAGE) 3,462 AA 3,462 2020 Green Finance Impact Report 5 Portfolio renewable energy capacity The portfolio is forecast to avoid greenhouse gas emissions of 3,462kt CO2e per year equivalent to taking over 1.1 million cars off the road9 The portfolio is forecast to produce over 8,000 GWh per year enough to power over 1.9 million households8 for a year 8 Calculated using the average household electricity data for the relevant country of the underlying projects available from the World Energy Council, and based on 2014 data (see https:/www.worldenergy.org/data/) 9 Year on year increase in cars off the road is not due to change in portfolio but rather due to the updated conversion factor calculated using a petrol car based on data from UK Government Greenhouse gas reporting conversion factors. See www.gov.uk/government/collections/ government-conversion-factors-for-company-reporting) for further detail. 645 MW of renewable energy in operation 1,570 MW of renewable energy in construction 209 MW of renewable energy in development 2020 Green Finance Impact Report 6 Macquaries green financing transactions Climate change and the associated legislative and regulatory responses present significant challenges for society and the global economy. Green financing has an important role to play in supporting the global energy transition, and investor appetite for these products is rising. In June 2018, Macquarie issued a 2,100 million GBP loan facility of which 500 million constitutes green financing. The green tranches were issued in accordance with Macquaries GFF. The GFF was established to demonstrate how Macquarie and its entities intend to enter into green financing transactions10 to fund projects that will deliver environmental benefits to support Macquaries business strategy. In March 2020, Macquarie issued its second green financing facility, a US$300 million facility into the Japanese market. Of this, US$150 million (Tranche A) constitutes as green financing and was issued in accordance with Macquaries GFF. For the purposes of this report, the green impact of this facility is not discussed as the facility was drawn down after the 31 March 2020 reporting period end. Macquarie GBP Facility Macquarie Samurai USD Facility TrancheTranche A1Tranche B1Tranche A IssuerMacquarie Group LimitedMacquarie Group LimitedMacquarie Group Limited Issue Date13 June 201813 June 201830 March 2020 Maturity Date13 June 202113 June 202330 March 2025 Original Tenor3 years5 years5 years Total Volume250m250mUS$150m StructureRevolverTermTerm Initial Drawdown Date31 July 201926 July 20189 April 2020 Drawn Volume as at 31 March 2020 250m250m0 Use of Proceeds In accordance with Macquaries Green Finance Framework In accordance with Macquaries Green Finance Framework In accordance with Macquaries Green Finance Framework The details of Macquaries green tranches are as below: 10 See glossary for definition of green financing transactions. 2020 Green Finance Impact Report 7 Eligible ProjectsLocationTechnologyStage Percentage of Macquarie Funding11 Total Capacity (MW) Total GHG emissions avoided (kt CO2e/yr)14 BLE MalaysiaMalaysiaSolarConstruction1002 verturingen Wind Park SwedenOnshore WindConstruction10023541 East Anglia OneUKOffshore WindConstruction16% 12,13714980 Energy Pratham Godo Kaisya JapanSolarOperation1007 Eolica KiselicePolandOnshore WindOperation100B73 Formosa 1TaiwanOffshore WindOperation50128207 Formosa 2TaiwanOffshore WindConstruction75376625 Rampion Offshore Wind Farm UKOffshore WindOperation25400578 Lal Lal Wind FarmAustraliaOnshore WindConstruction208401 Lohas Ece Brown K.K (Tochigi) JapanSolarConstruction1008 Lohas Ece Brown K.K (Nagano) JapanSolarOperation10010 Zajaczkowo WindfarmPolandOnshore WindOperation100H62 Murra Warra Wind Farm 2 AustraliaOnshore Wind Pre- Construction 50 9468 Total2,4243,462 11 Reflects the share of the projects funded by Macquarie green financing at the time of allocation. 12 The funding percentage was subject to variation during the reporting period. As at March 2020, funding to verturingen Wind Park, East Anglia One, Formosa 1, Formosa 2 and Rampion Offshore Wind Farm was 50%, 13%, 25%, 26% and 0%, respectively. 13 As at March 2020, Macquaries interest in East Anglia One was 40%. 14 In an update to the 2019 Macquarie Green Finance Impact Report, projects that commence operations after July 2019 adopt an updated (v2.0) marginal grid electricity emission factor to calculate avoided GHG emissions, in line with International Financial Institutions IFI approach to GHG accounting for renewable energy projects. In most cases, this has the effect of reducing the estimate of avoided GHG emissions for projects previously evaluated with the v1.0 marginal grid emission factors. For the reporting period April 2019 to March 2020: MGL GBP Facility Tranche A1 was drawn down on 31 July 2019 and allocated to from this date until the end of the reporting period. MGL GBP Facility Tranche B1 was drawn down and allocated to throughout the entire reporting period. MGL Samurai USD Facility Tranche A was undrawn and not allocated to during the reporting period. The eligible projects which have been notionally allocated funding from the green tranches during the reporting period are summarised in the following table. 2020 Green Finance Impact Report 8 Approach The GFF under which the green tranches were issued was developed in accordance with the APLMA Green Loan Principles. It was supported by a second opinion external review by Sustainalytics and was noted to be credible and impactful. The framework is based on four core components: 1. use of proceeds 2. process for project evaluation and selection 3. management of proceeds 4. reporting Use of proceeds Under the GFF, the use of proceeds of each green financing transaction is notionally allocated against the financing or re-financing of eligible projects which provide clear environmental benefits. The GFF explicitly recognises several broad categories of eligibility for projects with the objective of addressing key areas of environmental concern such as climate change, natural resources depletion, loss of biodiversity, and air, water and soil pollution. The proceeds from the green tranches have so far been applied towards financing solar, offshore wind and onshore wind projects across the globe. Going forward, we may extend the use of loan proceeds to support further renewable energy, energy efficiency, waste management, green buildings and clean transportation projects. Activities and lending to an industry or technology which directly involves fossil fuels, nuclear or biomass suitable for food production are specifically excluded under the GFF. 2020 Green Finance Impact Report 9 Process for project evaluation and selection Macquarie has established a Green Finance Working Group (“GFWG”) who have responsibility for governing and implementing the GFF. The GFWG currently comprises representatives from the Environmental and Social Risk (“ESR”) team and the GIG Green Investment Ratings team who hold the in-house environmental expertise, as well as representatives from Risk Management Group - Credit, Financial Management Group - Group Treasury and Macquarie Capital. Business units will identify potential eligible projects based on the criteria in the GFFs use of proceeds. Potential eligible projects are submitted to the GFWG for review and confirmation that they qualify under the GFF. This includes the preparation of a suitable Green Opinion15 provided by the GIG Green Investment Ratings team where appropriate. The Green Investment Ratings team is responsible for confirming that the projects: fall within one of the eligible project categories defined in the GFF are anticipated to provide clear environmental sustainability and/or climate change mitigation benefits in terms of the contribution to one or more of GIGs Green Purposes16. In addition to meeting the green loan eligibility criteria, all projects are assessed under Macquaries group wide ESR policy and ESR assessment tool during the investment decision process. The ESR policy and tool provide a robust due diligence process and evaluate ESR issues including labour and employment practices, climate change, human rights, resource efficiency, pollution prevention, biodiversity and cultural heritage. The approach is based on international guidelines including the International Finance Corporation Performance Standards. Reporting This report is designed to
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Network for Greening the Financial System Technical document A Status Report on Financial Institutions Experiences from working with green, non green and brown financial assets and a potential risk differential May 2020 NGFS Technical document MAY 2020 This report has been coordinated by the NGFS Secretariat/Banque de France. For more details, go to and to the NGFS Twitter account NGFS_ , or contact the NGFS Secretariat sec.ngfsbanque-france.fr NGFS Secretariat NGFS REPORT 2 Executive summary 3 Introduction: Why focus on potential risk differentials between green, non-green and brown? 6 1.Classification principles 7 1.1. What is green and what is brown?7 1.2. Most respondents use a voluntary classification or principle8 1.3. Alternative views on the use of the taxonomies and classifications10 2.Respondents views on the risk aspect and risk assessments performed by the industry 10 2.1. Various motives for engaging in climate- and environment-related issues10 2.2. The results of backward-looking approaches are not conclusive yet on a risk differential 12 2.3. Forward-looking approaches may be a better tool for capturing this emerging risk. 15 3.Integration of climate- and environment-related risks into risk monitoring appears to be a challenge for the respondents 15 3.1. The path towards integration into risk assessment and monitoring15 3.2. Identified challenges and obstacles17 Tentative conclusions and high-level messages to financial institutions 19 Appendix I : Defining green and brown sector, asset, activity and value-chain aspects 21 Appendix II : Case study: Practical application internal classification 25 Appendix III : A summary of the Chinese taxonomy 27 Appendix IV : The Brazilian classification framework 28 Acknowledgements 29 Table of Contents NGFS REPORT 3 Executive summary A point-in-time survey of how financial institutions are tracking green, non-green and brown risk profiles It is important for financial institutions to consider all relevant risks in order to avoid suffering unexpected losses. Such losses could potentially have a negative impact on the stability of the financial system. Against the backdrop of the increasing impact from climate- and environment- related risks in the financial system1, financial supervisors need to understand how these risks are taken into account by supervised institutions. Therefore, with the help of a select group of financial institutions, the NGFS has performed a survey to assess whether a risk differential could be detected between green, non-green and brown2 financial assets. This survey focuses on the work performed by financial institutions to track specific risk profiles of green, non-green and brown financial assets (loans and bonds), develop specific risk metrics and analyse potential risk differentials. It aims to present a point-in-time snapshot of current practices among financial institutions, based on the information these institutions have obtained up until now. Forty-nine banks from the following jurisdictions have submitted their answers (anonymised in this report): Brazil, Belgium, China, Denmark, Finland, France, Germany, Greece, Japan, Malaysia, Morocco, the Netherlands, Portugal, Spain, Sweden, Switzerland, Thailand, the UK, and one supranational. We have also received answers from five insurance companies in Malaysia. shows that the institutions have not established any strong conclusions on a risk differential between green and brown The striking result from the study was the diversity of methods, results and motivations for whether to undertake a climate- and environment-related risk assessment. Most of the institutions have undertaken an operational commitment towards greening their balance sheets, with 57% of the respondents undertaking commitments that affect their daily operations either by limiting their exposure to brown assets or by setting green or positive-impact targets. However, the survey responses highlight that the underlying justification is not based on an attested financial risk differential between green and brown assets but rather on a more diffuse perception of risks. Most banks tend to consider their actions to be part of their corporate social responsibility or mitigation measures for reputational, business model or legal risks. Backward-looking studies on a potential risk differential have only been performed by five respondents. Another three respondents (banks) indicated that they conducted backward-looking analysis with ESG or energy rating of housing loans, but not strictly using green or brown criteria. In both cases, they failed to reach strong conclusions on a risk differential between green and brown assets. These studies have been limited to sub-sectors and performed on a project-basis rather than at counterparty level. Overall, it appears that it is only possible to track the risk profile of green, non-green and brown assets in very few jurisdictions. An important reason for this is that the prerequisites, e.g. a clear taxonomy and available granular data, are not yet in place in most jurisdictions. These results illustrate the challenges for banks and insurance companies to assess their exposure in the absence of common classifications and the inherent limits of backward-looking analysis in a rapidly developing area. 1 See NGFS first comprehensive report “A call for action: Climate change as a source of financial risk”, April 2019 2 As of yet, there are no clear, uniform definitions of the commonly used terms “green”, “non-green” and “brown” are being used . We abstain from adhering to any particular definition. Please see section III. NGFS REPORT 4 Using national or international taxonomies and/or principles is the most common approach for classifying green and brown assets In its first comprehensive report, the NGFS established the need for a clear taxonomy3 as a prerequisite for a better understanding of possible risk differentials between different types of assets4. Given the the lack of an official taxonomy in the majority of jurisdictions, the most common approach among the respondents has been to implement and use an international or national classification in the form of a voluntary classification or principle. The second most frequent approach is to use an internally developed classification. There is a wide variety of approaches to classify assets, the most common being to classify the assets by the use-of-proceeds method. The survey shows a growing use of climate- related taxonomies among the respondents: only 15% of the respondents did not use any taxonomy or voluntary principle, and the majority of them are considering implementing an international/national taxonomy in the future. but there are some challenges to overcome when classifying financial assets The majority of the institutions only apply their internal classification to a part of their assets within each asset category (bonds or loans). Several respondents highlight that they encounter different challenges when trying to classify different types of assets (e.g. loans, bonds, investments). For loans in particular, whilst the classification of single purpose loans (e.g. within project finance) may seem quite obvious, loans for general corporate purposes have a weaker direct link to a physical asset or a project and seem more difficult to classify. Lack of harmonised client data and a lack of internal resources are other main challenges Many respondents stressed the lack of harmonised client data as the main obstacle for defining the greenness of an asset. One root cause identified by some respondents is the lack of legal disclosure requirements for companies to report verified data on a sector-specific basis, but respondents also highlighted some limitations of international or internal taxonomies and classifications. The respondents stressed the internal challenges posed to their organisations. The integration of climate- and environment-related risk assessment into their usual risk analysis requires the build-up of internal knowledge as well as investment to adapt existing IT systems to track this emerging risk. Different views on methodologies for assessing the effective riskiness of green and brown assets The respondents provided a number of comments on what methodology characteristics are important for assessing the effective riskiness of green or brown assets. In particular, diverging views were expressed with regard to the question of compatibility with existing methods or models. Some respondents take the position that climate-related risks can be considered in existing internal rating-based approach (IRB) standards, while others feel that the different timeframes do not allow for this5. Some respondents highlighted the need to consider long horizons in a forward-looking approach through scenario analysis and forward-looking assessment of relative riskiness. In terms of the development of methodologies for the assessment of the vulnerability of counterparties to climate- or environment-related risks, respondents broadly agreed that the methodologies should consider key environmental issues that could impact the repayment ability of clients or the value of an asset. For economic sectors, the sensitivity to key parameters could be assessed. However, according to some institutions, it may be necessary to go deeper than the sectoral level and perform risk assessment at an individual or corporate level. Some institutions are currently working on integrating counterparty ESG factors into their credit processes and, subsequently, their risk management frameworks. 3 A taxonomy can be defined as a system for organising objects into groups that share similar qualities. 4 See NGFSs first comprehensive report, “A call for action: Climate change as a source of financial risk”, April 2019, Recommendation No 6. 5 The IRB model uses a time horizon of one year, but climate risks are expected to fully materialise over a longer time frame. NGFS REPORT 5 Respondents mentioned a variety of environmental risk monitoring measures including ESG scoring, Risk Appetite Statement (RAS) limit setting, an internal capital allocation model, and environmental veto systems. and some respondents have entirely different views A few of the respondents consider monitoring of the specific risk profiles of green or brown assets is not and should not be a priority in their on-going work on climate-related challenges. Some institutions also raised doubts on the relevance of monitoring risk profiles based on green and brown classifications and insisted on other more decisive risk factors. Forward-looking studies still at an early stage Forward-looking studies to assess how different climate scenarios can affect different kinds of activities and assets were performed at the portfolio level by twelve respondents (22%). Of these forward-looking studies, scenario analyses and stress tests are the most common. These types of analyses are typically at an early stage and often stem from international initiatives such as the TCFD and the UNEP FI pilot, in which some respondents participated. Tentative conclusions and high-level messages to financial institutions The survey does not allow us to conclude on a risk differential between green and brown assets. Overall, it appears that in all but a few jurisdictions the prerequisites for tracking the risk profile of green or brown assets are not yet in place. The vast majority of institutions cannot yet conclude on the relationship between greenness and credit risk, pending further analyses, which require a better tagging of exposures and meaningful performance data. With those prerequisites in place, it should be possible to expand the risk management tools already in use for more traditional risk categories to comprise climate-related and environmental risks. Given the increasing magnitude of climate change and its impact on the financial system, forward-looking methodologies are necessary to assess the impact on individual financial institutions. NGFS REPORT 6 Why focus on potential risk differentials between green, non-green and brown? Most local and regional prudential frameworks are based on BCBS and IAIS1 standards for banks and insurance companies. The BCBS guidelines Principles for the Management of Credit Risk2 state inter alia, that banks should identify and analyse existing and potential risks inherent in any product or activity3. Against the backdrop of the increasing impact from climate and environmental risks on the financial system4, supervisors need to better understand how and to what extent such risks translate to financial risks. An important part of this work is to analyse the potential risk differentials between green, non-green, and brown financial assets and how financial institutions take these risks into account in their credit assessments. If, for example, a consistent link between brown financial assets (such as loans or bonds) and higher default rates could be established, financial institutions holding such assets would need to safeguard themselves against this increased default risk. This would mean for example, closer risk monitoring and setting aside more economic capital.5 Regulators would probably also need to consider increasing regulatory capital requirements6 held against these assets in order to safeguard financial stability. In 2018, the NGFS performed a preliminary stock-take of studies conducted by market participants on credit risk differentials between green, non-green and brown financial assets. The findings showed that it was not possible to draw any general conclusions on potential risk differentials based on the studies conducted so far. These studies also pointed to differing results depending on the financial assets that had been surveyed, the geography and the underlying factors the study had been able to control for. Based on this, the NGFS pointed to the need for further fact-gathering and analyses. The NGFS therefore decided to perform an exploratory data collection from selected institutions. The original intention was to analyse the collected data, and assess whether a risk differential could be detected between green, non-green, brown and non-brown financial assets. However, due to the lack of relevant and comparable data, the scope and methodology were slightly altered. In the end, this survey does not allow a conclusion on a risk differential between green and brown assets. However, it provides a useful and encouraging snapshot of the current practices among a sample of financial institutions around the globe to monitor climate-related financial risks and the challenges these institutions are facing. Scope and methodology of the exercise The scope has been to collect information from financial institutions7 on how they have responded to the need to take the emerging climate-related risks into account in their risk assessment. Given that a
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Crunchbase Industry Spotlight: Fintech Industry Spotlight: Fintech 2Crunchbase Industry Spotlight: Fintech Fintech is short-form for “financial technology” and includes everything from mobile banking technology to investment apps to cryptocurrency. As one of the most rapidly evolving sectors, fintech has changed significantly since banking technology was first introduced in the 1860s. Since then, the invention of credit cards, e-trade and online banking has quickly progressed the industry, threatening traditional financial institutions and changing the way people manage their finances. What is fintech? Crunchbase is the leading provider of private-company prospecting and research solutions. Over 55 million usersincluding salespeople, entrepreneurs, investors, and market researchersuse Crunchbase to prospect for new business opportunities. And companies all over the world rely on us to power their applications, making over 3 billion calls to our API each year. About Crunchbase. 3Crunchbase Industry Spotlight: Fintech At Crunchbase, we are constantly analyzing our growing dataset and thinking about how to contextualize information to better equip people to make informed business decisions. Part of this process includes identifying trends and sharing complicated data insights in an easily digestible way, so you dont need advanced analytics tools or a data science degree to quickly identify and understand industry developments. Fintech companies hold 16 percent of the spots on the Crunchbase Unicorn Leaderboard, collectively valued at close to $500 billion, per last known disclosed or reported valuations. Since 2010, investments in fintech have grown more than ninefold, with $43 billion invested in 2019 alone. Why we cover fintech. 4Crunchbase Industry Spotlight: Fintech With the impact of COVID-19 hundreds of millions of people are changing how they conduct their daily lives. Industries that rely on people gathering to provide a service have been disrupted in a short time frame. Travel, events, restaurants, and retail businesses have been instantly impacted, casting a wider net on services that supply these businesses. Broad adoption of social distancing measures, along with shutdowns of businesses deemed non-essential, impacts a wide array of companies, including manufacturing, construction, logistics, and supply chain. Investors will be assessing their portfolio companies for risks to their businesses based on a very different consumer and business environment. Consumers will also rely on companies that connect us virtually. As with every sector, some will fare better than others. Companies that rely on the revenue of impacted industries will see shrinking markets. Those whose offerings address real needs in a challenging economy will see more attention. In financial services the underlying trends towards servicing newer market segments through online services are accelerated by these changes. The trend towards cashless economies is furthered, as businesses stop accepting cash in order to stem the transmission of the virus. Loans are expected to increase, and mortgage refinancings are seeing unprecedented demand. According to Ryan Gilbert of Propel Venture Partners, “Balance sheet businesses, specifically non-bank lenders are under tremendous pressure to collect on their issued loans and prove that their lending models can actually survive an economic shock like the one we are dealing with. The consumer and small business lending sectors seem to be hit the hardest.” Impact of COVID-19. 5Crunchbase Industry Spotlight: Fintech Companies providing benefits and services to independent workers become important in helping non-W2 workers stay covered during this health crisis. Services for the unemployed will become critical as society addresses those that are most in need of short and longer term support. Retail banks are shuttering their outlets on a short term basis. Will some of these short term closures become permanent as services move online? The full economic impact of COVID-19 is still too early to tell but a long- term recession or depression seems likely. “B2B companies will need to prepare for frozen sales pipeline for most of this year and longer sales cycles and shrinking budgets in 2021. B2C companies will need to adjust to reductions in consumer spending, greater emphasis on short term cash needs given spiking unemployment, and increased reluctance from consumers to switch financial service providers,” said Satya Patel founder of seed investor Homebrew. “The hardest hit fintech businesses will be lending businesses that have large outstanding loan balances and that will have to deal with lots of uncertain credit risk. In general, an increasing emphasis on unit economics over growth, will put some companies in a very difficult fundraising position.” For this report we look at the last decade to provide a lens on the prevailing trends in fintech. 6Crunchbase Industry Spotlight: Fintech Fintech has been a key arena for investment in the past decade with the rise of challenger banks, innovation in online payments, the changing market around lending and insurance, and the launch of cryptocurrencies. With the impending recession, there will be companies that face a changed market opportunity and do not make it through. However, fintech will continue to lead as a sector, as financial services become more deeply integrated into the consumer mobile experience-a bank in your pocket-along with the growth in services integrating financial products aimed at both consumers and businesses. The next 10 years are going to be more interesting to watch, with the growth of infrastructure and compliance as a service, allowing more players to enter this ecosystem. Alongside challenger banks in Europe, the U.S., and now Latin America, 2,000 newly funded fintech companies per year are chipping away at services provided by banks and other finance incumbents not limited to checking, transfers, loans, mortgages, brokerage, insurance, and more. Established public tech companies are building financial products into their services, with Google offering checking accounts (via Citigroup and small lender Stanford Federal Credit Union), Facebook launching Facebook Pay to facilitate payments across all its apps, and Apple launching Apple Card (developed by Goldman Sachs) that is linked to Apple Pay - launched back in 2014. In China, where credit card penetration is low, mobile payments represent 83 percent of all payments in 2018, up from just three percent in 2011 led by AliPay launched in 2004, and WeChat Pay in Crunchbase Industry Spotlight: Fintech 7Crunchbase Industry Spotlight: Fintech 2013. The Chinese government is planning to launch its own state-backed cryptocurrency on the back of the Facebook Libra mislaunch. The most highly valued private company in the world is Ant Financial valued at $150 billion. As of February 2020, 90 companies on the Crunchbase Unicorn Leaderboard (16 percent) are in financial services, collectively valued at close to $500 billion. Fintech received 16 percent of global venture capital funding in 2019 and 17 percent in 2018, up from 10 percent in 2010. 2020 already exceeds 2019 in exits with the pending Visa acquisition of Plaid and Intuit acquisition of Credit Karma leading the way. Asia leads in payments, Europe in Neobanks, the U.S. in infrastructure, and LatAm in services for the unbanked. Despite the downturn, we will continue to see multiple leading companies in fintech across geographies. Fintech companies will reassess their product offerings in light of business and consumer needs in this changed funding environment. With this report, we dive into the last decade in fintech funding and exits as we look to the next decade. I. Decade Of Venture Investments Into Financial Services II. Leading Sectors III. Growth In Leading Countries IV. Active Seed And Venture Investors V. Large Exits In 2019 VI. 90 Fintech Unicorns VII. Investor Predictions 8Crunchbase Industry Spotlight: Fintech In 2010 fintech represented 10 percent of total venture funding. Fast forward to 2019, fintech held 16 percent of total venture funding I. Decade Of Venture Investments Into Financial 9Crunchbase Industry Spotlight: Fintech Investments in fintech companies have grown more than ninefold since 2010 and more than doubled since 2015. 2019 was the second highest investment year over the last decade with $43 billion invested in fintech. 2018 is an all time high for investment in fintech at $57 billion, with the largest growth percent year-over-year in late-stage venture. The largest funding round to a fintech company was raised by Ant Financial - a $14 billion Series C round in 2018. (The gap in funding between 2019 and 2018 decreases to $600 million if you remove Ant Financials single Series C round from consideration.) 10Crunchbase Industry Spotlight: Fintech Financial services companies attracted a greater proportion of late-stage venture funding rounds in 2018 and 2019. Seed and early stage investments in fintech were at 34 percent in 2019 and 32 percent in 2018. Seed and early stage venture represent a higher proportion of investment dollars, averaging 51 percent from 2010 to 2017. 11Crunchbase Industry Spotlight: Fintech As of February 2020, year-over-year deal counts were down by 22 percent, but over time will lessen. Much of the difference in funding round counts are attributed to the seed stage - down 31 percent - where we see the most reporting delays. At the early venture stage, counts are down by 10 percent. Late stage round counts are down by 5 percent. We fully expect these numbers to go up for 2019 relative to 2018, due to reporting delays. However, 2019 will not exceed 2018 a decade long peak for fintech both in funding count and amount. (Reporting delays for funding amounts are less pronounced in Crunchbase data.) Investments And Deal Count 12Crunchbase Industry Spotlight: Fintech Leading financial services industries in 2019 included payments (along with mobile payments), insurance, banking, and lending, respectively. For many companies there is integration between these sectors; for example companies that offer payment and banking services or companies that offer banking and lending products. We assigned companies a single industry for this analysis. Industries that grew year-over-year above 75 percent by invested dollars include lending and banking. Insurance grew over 33 percent. (Payments did not grow year-over-year due to Ant Financial raising $14 billion in 2018.) II. Leading Industries: Lending, Banking, these products are accessible via APIs.” Cherry Miao, Accel “The sharing economy, in certain parts of the world, is breaking into fintech way beyond the expectations.” said Ryan Gilbert of Propel Venture Partners. “This is driven in part by peer to peer transactions in payments, lending and insurance.” “Although we are in uncertain times due to COVID-19, the market dynamics remain interesting in LatAm, particularly in Brazil and Mexico. Both are still substantially cash-based economies with mobile phone penetration over 70 percent, so there is an opportunity to deliver digital financial services tailored for consumer and small to midsize enterprise (SME) audiences that fill the gaps left by traditional financial institutions that often require in-person interaction for delivery of financial services products.” Michael Sidgmore, Broadhaven Ventures. “All of the fintech companies with products that have achieved significant consumer scale will work to introduce complementary products, such as savings, debit, credit, lending and investing, to round-out their offerings and to drive customer engagement and loyalty.” Satya Patel, Homebrew 28Crunchbase Industry Spotlight: Fintech Methodology This report is based on data in Crunchbase as of Feb. 27, 2020. Industries in Crunchbase are not exclusive. A company can be in more than one industry and in more than one industry group. For Financial Services we include the following leading industries: Banking, Insurance (InsurTech), Lending, Payments (Mobile payments), Personal Finance, and Wealth Management. All Financial Services Industries Accounting, Angel Investment, Asset Management, Auto Insurance, Banking, Bitcoin, Commercial Insurance, Commercial Lending, Consumer Lending, Credit, Credit Bureau, Credit Cards, Crowdfunding, Cryptocurrency, Debit Cards, Debt Collections, Finance, Financial Exchanges, Financial Services, Fintech, Fraud Detection, Funding Platform, Gift Card, Health Insurance, Hedge Funds, Impact Investing, Incubators, Insurance, InsurTech, Leasing, Lending, Life Insurance, Micro Lending, Mobile Payments, Payments, Personal Finance, Prediction Markets, Property Insurance, Real Estate Investment, Stock Exchanges, Trading Platform, Transaction Processing, Venture Capital, Virtual Currency, Wealth Management 29Crunchbase Industry Spotlight: Fintech For this report we look at reported-not projected data, which means that 2019 numbers will increase over time, relative to previous years. Private market financing data is subject to reporting delays. Numbers may have changed since publication as more data gets added to Crunchbase. Please note that all funding values are given in U.S. dollars unless otherwise noted. Crunchbase converts foreign currencies to U.S. dollars at the prevailing spot rate from the date funding rounds, acquisitions, IPOs and other financial events are reported. Even if those events were added to Crunchbase long after the event was announced, foreign currency transactions are converted at the historic spot price. 30Crunchbase Industry Spotlight: Fintech Glossary of Funding Terms Seed/Angel includes financings that are classified as a seed or angel, including accelerator fundings and equity crowdfunding$3 million and below. Early stage venture includes financings that are classified as a Series A or B, venture rounds without a designated series that are above $3 million and equal to or below $15M. Late stage ventures include financings that are classified as a Series C and venture rounds without a designated series greater than $15M. Note: Fundings denoted by Crunchbase as private equity are not included in this report. Special thanks go to the following investors; Satya Patel Founder, Homebrew John Locke Partner and Cherry Miao, Accel Ryan Gilbert Partner, Propel Venture Partners Michael Sidgemore Partner, BroadHaven Ventures, Howard Lindzon Founder & General Partner, Social Leverage
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ISSN: 1962-5361 Disclaimer: This Philadelphia Fed working paper represents preliminary research that is being circulated for discussion purposes. The views expressed in these papers are solely those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. Philadelphia Fed working papers are free to download at: https:/philadelphiafed.org/research-and-data/publications/working-papers. Working Papers A Survey of Fintech Research and Policy Discussion Franklin Allen Imperial College London Xian Gu Central University of Finance and Economics and the University of Pennsylvania Julapa Jagtiani Federal Reserve Bank of Philadelphia Supervision, Regulation, and Credit Department WP 20-21 June 2020 https:/doi.org/10.21799/frbp.wp.2020.21 1 A Survey of Fintech Research and Policy Discussion* Franklin Allen Imperial College London Xian Gu Central University of Finance and Economics and the University of Pennsylvania Julapa Jagtiani Federal Reserve Bank of Philadelphia First Draft: April 21, 2020 Current Draft: May 28, 2020 Abstract The intersection of finance and technology, known as fintech, has resulted in the dramatic growth of innovations and has changed the entire financial landscape. While fintech has a critical role to play in democratizing credit access to the unbanked and thin-file consumers around the globe, those consumers who are currently well served also turn to fintech for faster services and greater transparency. Fintech, particularly the blockchain, has the potential to be disruptive to financial systems and intermediation. Our aim in this paper is to provide a comprehensive fintech literature survey with relevant research studies and policy discussion around the various aspects of fintech. The topics include marketplace and peer-to-peer lending, credit scoring, alternative data, distributed ledger technologies, blockchain, smart contracts, cryptocurrencies and initial coin offerings, central bank digital currency, robo-advising, quantitative investment and trading strategies, cybersecurity, identity theft, cloud computing, use of big data and artificial intelligence and machine learning, identity and fraud detection, anti-money laundering, Know Your Customers, natural language processing, regtech, insuretech, sandboxes, and fintech regulations. Keywords: fintech, marketplace lending, P2P, alternative data, DLT, blockchain, robo advisor, regtech, insuretech, cryptocurrencies, ICOs, CBDC, cloud computing, AML, KYC, NLP, fintech regulations JEL Classification: G21, G28, G18, L21 *Author contacts: Julapa Jagtiani, Federal Reserve Bank of Philadelphia, Ten Independence Mall, Philadelphia, PA 19106, julapa.jagtianiphil.frb.org; Franklin Allen, Imperial College London, f.allenimperial.ac.uk; and Xian Gu, Central University of Finance and Economics, and the University of Pennsylvania; xianguwharton.upenn.edu. Comments are welcome. The authors thank Mitchell Berlin and Bill Wisser for their comments, and thanks to Erik Dolson, Adam Lyko, Dan Milo, and Andes Lee for their research assistance. Disclaimer: This Philadelphia Fed working paper represents preliminary research that is being circulated for discussion purposes. The views expressed in these papers are solely those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. Any errors or omissions are the responsibility of the authors. No statements here should be treated as legal advice. Philadelphia Fed working papers are free to download at https:/philadelphiafed.org/research-and- data/publications/working-papers. 2 1. Introduction The rapid advance in financial technology (fintech) in recent years has played an important role in how financial products and services are produced, delivered, and consumed. Fintech has become one of the most popular discussion topics recently, primarily because of its potential disruption to the entire financial system. There has been a dramatic digital transformation in the financial landscape. The term fintech is, however, a broad term, and it tends to mean different things to different people. The goal of this paper is to describe the various aspects of fintech and its role in each segment of the financial market and the associated impact on consumers and the financial system overall. A great deal of data have been collected in recent years. For example, as of 2016, IBM estimated that 90 percent of all the global data was collected in the past year. The amount of data collection accelerated even more between 2016 and 2020. There have been new opportunities for data to be monetized, such as through data aggregation. Big data (including data from nontraditional sources and trended data) have been collected and used widely, in conjunction with advances in artificial intelligence (AI) and machine learning (ML) for digital identity and fraud detection, sales and marketing, security trading strategies, risk pricing and credit decisions, and so forth. More than 2 billion consumers are currently excluded from financial systems around the globe (especially in less developed countries such as Bangladesh, Nigeria, and Pakistan) who could potentially benefit from the use of more data and complex algorithms to access credit. There also have been new questions related to data ownership and the ethical use of data, such as who should have control over the ability to aggregate, use, and share data to safeguard consumer privacy and to avoid systemic misuse of consumer data. Cloud storage and cloud computing have also played increasing roles in payment systems, financial services, and the financial system overall. Financial data and payment data have been stored in the cloud, and cloud computing has made it possible for many fintech innovations, such as real-time payment and instantaneous credit evaluations/decisions. Firms no longer need to commit a large investment (usually unaffordable for smaller firms) to in-house technology, but they could outsource to the cloud computing service providers and share the cost with other firms. This leveled the playing field; size is no longer the most important determinant for success. Consumers preferences have also adapted to prioritize faster services and greater convenience and transparency through online services and applications. There have been concerns among regulators about the impact on the safety and soundness and stability of the financial systems (e.g., the impact 3 on the payment system when a cloud service platform is rendered nonoperational, the exposure to a greater risk of cyberattack, and other similar events). Blockchain and smart contracts are the buzzwords in the fintech community, partly because blockchain is the technology underlying bitcoin transactions. Blockchain and other digital ledger technologies (DLT) have also been used in creating various cryptocurrencies, initial coin offerings (ICOs), other payment applications, and smart contracts thus, leading some to believe that blockchain has the potential to become the mainstream financial technology of the future. There has been some disappointing evidence on the role and potential of blockchain in that it may not be as disruptive as initially expected, and one of the main obstacles seems to be its scalability. For example, bitcoin transactions take about 10 minutes to clear, and it is expected to take longer as the block length gets longer over the years. While thousands of tech start-ups and other tech experts have been working to resolve the issue, permissioned blockchain platforms have benefited some segments of the economy through their use for identity detection, supply chain management, digital-asset-backed lending, and securitization. Fintech activities have been progressing quickly, penetrating all areas of the financial system. Fintech has produced great benefits to a large number of consumers around the world and has made the financial system more efficient. The rapid growth of bank-like services provided by fintech firms has raised potential concerns among bank supervisors. There have also been legal challenges and concerns associated with fintech around consumer privacy and the potential fintech disruption to overall financial stability. While fintech could greatly improve credit access and enhance efficiencies (providing faster, better, or cheaper services) in the financial system, risk cannot be completely eliminated. In this paper, we provide a comprehensive summary of what research studies have found so far, what the experts (academic, industry, and regulators) are working on, and the potential evolving nature of fintechs impact on consumer privacy and well- being, the structure of the financial and payment systems, the role of financial intermediation, and the effectiveness of existing regulatory policies. The rest of the paper is organized as follows. In Section 2, we discuss recent enhanced systems for credit scoring using AI/ML and alternative data, the roles of marketplace lending and peer-to-peer (P2P) lending, and digital banking and investment services. Section 3 discusses how fintech has played a big role in digital payment, such as e-wallet and allowing a large number of the unbanked population around the world to be included in financial systems for the first time. The roles of alternative data in financial inclusion, improving credit access, and more accurate risk pricing will also be discussed. 4 Section 4 describes the roles of blockchain, other distributed ledger technologies (DLTs), and smart contracts. As mentioned earlier, these have been the underlying technologies for cryptoassets and initial coin offerings (ICOs), which will be discussed in Section 5. There are frictions in the current payment system, especially cross-border payments. Consumers have come to expect faster or real-time payments with minimal fees. Digital currencies could potentially deliver these, and the payment processes have been involving rapidly toward a cash-lite (or potentially cashless) economy. Section 5 will also discuss the developments around the potential for central banks to issue fiat digital currencies, so-called central bank digital currency (CBDC). This idea of CBDC acknowledges that trust is the most important factor in payments, and private sectors may not be able to accomplish the goal of originating and supporting the value of the digital currencies it issues. There are also fears around CBDC: Several key considerations need to be incorporated into CBDCs design to avoid adverse impact on the financial system and the ability to conduct effective monetary policy. Section 6 deals with fintechs roles in securities trading and markets, such as the high- frequency trading or program trading that uses big data and ML algorithms to deliver superior performance. Section 7 discusses the impact of fintech on cybersecurity, which has been one of the top concerns among corporate CEOs and senior management teams. While the advanced technology has delivered vast benefits, the technology has also allowed for more sophisticated cyberattacks. Given all these innovations and rapid digital transformation, the existing regulations need to adapt to keep up with the new financial landscape. The increasing roles of BigTech and cloud computing in financial services, their potential impact on interconnectedness between financial institutions, and how these activities are likely to evolve in the near future are discussed in Section 8. There are just a handful of providers for all financial institutions, and these providers are currently not subject to supervision by bank regulators. There have been concerns about quality control, data security, and a possible conflict of interest that need to be addressed in the new fintech regulatory framework. Some of the technologies have also been used to assist regulators in regulatory compliance examination, such as the natural language processing (NLP) and the ML techniques used in RegTech, which will be discussed in Section 9, along with the various factors to be considered in designing fintech regulations to protect consumers and the financial systems while continuing to promote responsible fintech innovations. Finally, Section 10 provides conclusions and policy implications, such as those related to open banking policy, ethical use of consumer data, and whether a cashless economy is expected in 5 the near future. Quantum computing has also been transitioning from theory into practice, with potential implications/disruptions in the financial services industry and the overall economy in the coming decade. It is debatable whether the future mainstream financial technology will be blockchain and DLTs, quantum computing, or something else and how the industry and policymakers can best be prepared to keep pace with evolving technologies and the new adoption. We will also discuss potential directions for future fintech research. 2. Credit Scoring, Digital Banking, and Marketplace Lending 2.1 Credit Scoring Using AI/ML and Alternative Data Credit scores, such as FICO scores (or Vantage Scores), have served as the primary factors in credit decisions, especially for credit card applications. Previous studies, such as Mester, Nakamura, and Renault (2007) and Norden and Weber (2010), have documented the importance of consumer credit history and other financial and accounting data in credit risk evaluation by lending institutions. However, about 26 million American consumers have thin credit files or do not have bank accounts (unbanked); thus, they do not have FICO scores because of an insufficient credit history. More recently, there has been a breakthrough in which consumers default probability could be estimated not only from their official credit history or credit ratings but rather from more complex statistical methods using AI and ML techniques, along with (nontraditional) alternative data. These big data and complex algorithms have been rapidly adopted by fintech lenders to overcome the limitations of traditional models and data in evaluating borrowers credit risk and their ability to pay back loans. Fintech lending, which started in personal lending after the recent financial crisis, has expanded to cover small business lending and mortgage lending in recent years. Previous research studies that compare traditional default prediction models with more advanced techniques using AI/ML seem to suggest that there are significant lifts in predictive ability. Jagtiani and Lemieux (2019), Goldstein, Jagtiani, and Klein (2019), and Croux, Jagtiani, Korivi, and Vulanovic (2020) have documented that the information asymmetry, which used to b
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WORLD FINTECH REPORT 2020 2 Preface 3 Executive summary 4 Banks must board the last train to relevan.
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EBA REPORT ON THE IMPACT OF FINTECH ON PAYMENT INSTITUTIONS AND E-MONEY INSTITUTIONS BUSINESS MODEL.
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WORLD FINTECH REPORT 2020 2 Preface 3 Executive summary 4 Banks must board the last train to relevan.
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中东和北非地区也不例外:在监管的推动和创业的势头下，中东和北非地区近年来见证了金融科技行业前所未有的增长。无论是老牌企业还是企业家，都在抓住机遇，填补众多细分行业的市场空白，每次都对个人和企业主的生活产生深远影响。我们相信这只是开始。随着各国政府继续实施有利的激励措施和监管举措，机会将继续发展，使该地区的金融科技行业不仅有潜力提升支付生态系统，而且有潜力提升参与国的整体福利。
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2019年，马尼拉被评为全球金融科技初创公司最友好的城市之一，预计该市场将从2018年的约57亿美元增长到2022年的105亿美元。鉴于这些数字，加上读者对该地区最新发展的兴趣日益增长，我们很高兴地宣布，Fintech News将很快在菲律宾推出。
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它继续打击和清理P2P借贷业务和其他不符合监管要求或带来新的行业稳定风险的金融科技企业。这样的努力表明，中国政府对金融科技企业给现有合规和监管机制带来的新挑战持谨慎态度。政府虽然鼓励金融科技的发展，但.
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旅游、活动、餐馆和零售行业立即受到影响，为这些行业提供更广泛的服务。社会保持距离措施的广泛采用，以及被视为非必要的企业关闭，影响了包括制造、建筑、物流和供应链在内的广泛公司。投资者将根据截然不同的消费者和商业环境来评估其投资组合公司的业务风险。消费者也将依赖于虚拟连接我们的公司。
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我们的影响力源于十多年来对150个城市的100多万家公司进行的独立研究。与300多家合作伙伴机构并肩工作，我们的框架和方法已经成为初创公司成长的重要基础。我们的努力为我们赢得了2019年全球创业大会的研究冠军奖。
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2019GLOBAL INSURANCE MARKET REPORT GIMARAbout the IAIS The International Association of Insurance Supervisors(IAIS)is a voluntary membership organisation of insurance supervisors and regulators from more than 200 jurisdictions.Since its establishment in 1994,its mission has been to promote effective and globally consistent supervision of the insurance industry in order to develop and maintain fair,safe and stable insurance markets for the benefit and protection of policyholders and to contribute to global financial stability.The IAIS is the international standard setting body responsible for developing principles,standards and other supporting material for the supervision of the insurance sector and assisting in their implementation.It also provides a forum for members to share their experiences and understanding of insurance supervision and insurance markets.The IAIS coordinates its work with other international financial policymakers,supervisors and regulators,and assists in shaping financial systems globally.It is a member of the Financial Stability Board and the Standards Advisory Council of the International Accounting Standards Board,and a partner in the Access to Insurance Initiative.In recognition of its collective expertise,the IAIS is routinely called on by the G20 leaders and other international standard setting bodies for input on insurance issues and the regulation and supervision of the global financial sector.This document is available on the IAIS website(www.iaisweb.org).International Association of Insurance Supervisors(IAIS),2020.All rights reserved.Brief excerpts may be reproduced or translated provided the source is stated.Editing,design and layout by Clarity Global Strategic Communications.CONTENTSAcronyms and Abbreviations 1Executive Summary 2About This Report 3Chapter 1 Macroeconomic and Financial Environment 41.1 International Economic Growth and Inflation 41.2 Financial Markets 5Chapter 2 Global Insurance Market Developments 82.1 Non-life Insurance 92.2 Life Insurance 102.3 Reinsurance 11Chapter 3 Special Topics 133.1 Cyber-underwriting:Regulatory Considerations 133.1.1 Introduction 133.1.2 Market Overview 133.1.3 Risk Management and Regulatory Considerations 153.1.4 Market Access and Potential Barriers to Entry 18 3.1.5 Conclusion 183.2 The Risks of Interest Rate Spikes When Moving Out of a Low Interest Rate Environment 193.2.1 Introduction:The Different Aspects of Interest Rate Risk for an Insurer 193.2.2 Moving Out of a Low Interest Rate Environment 223.2.3 Conclusions 313.3 Current Challenges in the Life Insurance Industry 323.3.1 Unit-linked Insurance Products 323.3.2 Jurisdictional Developments 333.3.3 Private Equity 413.3.4 Conclusions 42Chapter 4 Global Reinsurance Market Survey 434.1 Reinsurance Premiums 434.2 Risk Transfer between Regions 454.3 Assets 474.4 Profitability 474.5 Capital Adequacy 494.6 Assets and Liabilities Allocation 504.7 Liquidity 534.8 Summary of Main Findings 54References 551Acronyms and AbbreviationsACPR French Prudential Supervision and Resolution AuthorityBaFin German Federal Financial Supervisory AuthorityBIS Bank for International SettlementsBMA Bermuda Monetary AuthorityEIOPA European Insurance and Occupational Pensions AuthorityESRB European Systemic Risk BoardEU European UnionFINMA Swiss Financial Market Supervisory AuthorityFSA Japan Financial Supervisory AuthorityFSC/FSS Korean Financial Services Commission/Supervisory ServiceGDP Gross domestic productGIMAR Global Insurance Market ReportIAIS International Association of Insurance SupervisorsIMF International Monetary FundInsurTech Insurance technologyIT Information technologyIVASS Italian Institute for the Supervision of InsuranceNAIC National Association of Insurance CommissionersNBB National Bank of BelgiumOECD Organisation for Economic Co-operation and DevelopmentPRA Prudential Regulation Authority,Bank of EnglandUK United Kingdom ULIP Unit-linked insurance productUS United StatesUSD United States dollarVIX Volatility indexZZR Zinszusatzreserve2EXECUTIVESUMMARYThis edition of the Global Insurance Market Report(GIMAR)discusses the global(re)insurance1 sector in 2019 from a supervisory perspective,focusing on recent performance and risks.The(re)insurance sector operates in a challenging global financial setting that is highly prone to vulnerabilities.Persistent trade tensions and slower economic growth may lead to the repricing of risks.This in turn may amplify low-yield vulnerabilities that have built up over previous years.Growth in non-life(re)insurance is mainly driven by emerging markets.The market and its profitability remained fairly stable in 2018 compared to previous years.Property rates have increased every quarter since the series of natural catastrophes that took place in 2017.Losses,especially those stemming from natural catastrophes,are at a period low.The expansion of alternative capital slowed down in 2019,although it retained a high relative share of overall reinsurance capital.The life insurance industry has operated in a low interest rate environment for a decade.2 This strains profitability,but abrupt rate increases also pose a risk.Sudden spikes could not only affect leverage and liquidity profiles but also lead to policy lapses and surrenders(full policy cancellations).The life insurance sector is experiencing several challenges.Sales of guaranteed rate products are struggling to grow because yields are low.As a result,in some jurisdictions,unit-linked business is the main driver of growth in life insurance.Several insurers are also shifting their focus towards asset management or were taken over by asset managers,while some markets have seen more insurers owned by private equity funds.Cyber-insurance is a new and rapidly growing line of insurance business.This report illustrates how market participants price this risk in the absence of historical data sets and points to the main challenges of managing the risks involved in this type of business.It also covers the main regulatory considerations for cyber-insurance.This report discusses these issues in four chapters:Chapter 1 analyses the overall macroeconomic and financial environment.Chapter 2 focuses on global(re)insurance market developments.Chapter 3 covers the measurement of cyber-risk,the movement out of low interest rates and the risk of interest rate spikes,and the current challenges facing the life insurance industry.Chapter 4 summarises the results of the IAIS survey of the global reinsurance market,covering 47 reinsurers in nine jurisdictions in North America,Europe and Asia,and links the financial position of reinsurers to the broader financial economy.3 ABOUT THIS REPORTThis is the seventh issue of the GIMAR.This report assesses developments relevant to the (re)insurance industry and identifies key risks and vulnerabilities for the industry to promote awareness among IAIS Members,stakeholders and interested parties.By assessing developments and risks across the whole financial system,the GIMAR plays an important role in the IAIS macroprudential policy and surveillance framework.Importantly,a global macroprudential view complements microprudential insurance supervision,which focuses on the soundness of individual financial institutions.This report was prepared by the IAIS Macroprudential Policy and Surveillance Working Group and draws on IAIS data on (re)insurers and contributions from several jurisdictions.It is not part of the IAIS supervisory or supporting material,and is not intended to reflect the official views of IAIS Members.The report was drafted between August 2019 and January 2020 and is based on data available during that period.4 CHAPTER 14MACROECONOMIC AND FINANCIAL ENVIRONMENTThe economic growth in markets at the beginning of 2018 began to slow down in the second half of the year,driven by a decrease in worldwide output.This trend continued in the first half of 2019.The Bank for International Settlements(BIS)reports shrinking global trade,manufacturing and investments as the main causes,although the negative effects are partially offset by consumption.3 Due to its interconnectedness within the global financial system,Chinas debt-reduction strategy(deleveraging)is also a factor in these trends.1.1 INTERNATIONAL ECONOMIC GROWTH AND INFLATIONThe International Monetary Fund(IMF)October 2019 World Economic Outlook4 forecastsglobal growth of 3%in 2019 and 3.4%in 2020.These figures are 0.3 percentage pointsand 0.2 percentage points lower,respectively,than the April 2019 forecast,5 based on a dropin corporate and domestic long-term spending and sluggish global trade.In its July 2019 World Economic Outlook,6 the IMF observed a softening in the lower-boundtarget of core inflation in the United States(US),and inflation well below the lower-boundtarget in the euro area and Japan.This is consistent with subdued growth in final demand.Market-based inflation expectations,measured by 10-year government bond break-even yields,dropped by about 36 basis points over the past year in the US,to 2.10%in July 2019.In Germany,they reached a 40-month minimum of 0.72%in June 2019,while Japans rates dropped to 0.16%in July 2019,compared with 0.53%in July 2018.Comparatively,market-based inflation expectations yields in the United Kingdom(UK)have risen by 30 basis points over the past 12 months,remaining well above 3%.Figure 1.1a:Market-based inflation expectations,break-even rates of 10-year bonds(%,June 2009 July 20197)Source:Bloomberg5In its Annual Economic Report,the BIS explains the low levels of inflation amid rising wages by suggesting that in mature markets,like the US,Japan and Germany,higher wages are slow to translate into higher price inflation.This may be due to globalisation and the relocation of production to developing economies,unions diminished ability to capture the benefits of productivity,as well as technological advancements.Similar trends can be observed in emerging markets with declining inflation expectationsover the past year.1.2 FINANCIAL MARKETSGlobally,monetary policy has focused on reducing interest rates to address global tradetensions and declining economic growth.However,financial markets remain vulnerable to asudden tightening of financial conditions,materialising through a sharp repricing of risk,escalating trade tensions or ongoing slow growth.These triggers could unearth vulnerabilities that built up during the low-yield environment since the 20072008 financial crisis.8 In its 2019 Global Financial Stability Report,the IMF estimated that corporate debt has increased.Notably,the stock of BBB-rated bonds has quadrupled and speculative-grade debt has doubled in the US and the euro area since the financial crisis.This may lead to credit risk repricing,which in turn will affect lending and borrowing capacity.On 31 July 2019,the Federal Reserve cut its interest rate for the first time since 2008,from2.25%to 2%,as a precautionary measure against ongoing global trade tensions,subdued global growth and volatility in the euro area.9 In addition,both the European Central Bank10 and the Bank of Japan11 announced that they will carry on with their expansionary monetary policy through their asset-purchase programmes.Several commercial banks have started to offer negative interest rates to their wealthier clients in order to pass on part of the low and negative interest rates offered by central banks.A“low-for-long”interest rate environment12 is setting in,with some jurisdictions observing negative rates for various maturities.In the 2019 Annual Economic Report,the BIS discusses how volatility in financial marketsreappeared towards the end of 2018.The US stock market declined,mainly due to lower growth expectations and earnings uncertainty.Previous expectations of further monetary policy tightening may have also contributed to these trends.Generally speaking,with notable exceptions that can be observed in the figures below,housing prices maintained their upward momentum of previous years.Trends appear to be fairly stable and are mainly shaped by the downward pressure created by the further decrease in long-term interest rates.As a result,several supervisors and international organisations,such as the European Systemic Risk Board(ESRB),13 have warned against a potential overheating of certain residential real estate markets and the risks of high or rising household indebtedness.Figure 1.1b:Market-based inflation expectations for selected emerging market economies,break-even rates of 10-year bonds(%,February 2014 July 2019)Source:Bloomberg6Figure 1.2a:Long-term interest rates(%,January 2007 May 2019)Figure 1.2b:Long-term interest rates negative territory snapshot(%,January 2015 May 2019)Figure 1.2c:Volatility in the financial markets(July 2007 July 2019)Source:BloombergSource:OECDSource:Organisation for Economic Co-operation and Development(OECD)7Figure 1.2d:Real house price indices in selected advanced economies(Q1 2007 Q1 2019,Index 2007:Q1=100)Source:OECDFigure 1.2e:Real house price indices in selected emerging economies(Q3 2010 Q4 2018,Index 2010:Q3=100)Source:OECD 8 CHAPTER 28GLOBAL INSURANCE MARKET DEVELOPMENTSThe global insurance market operates in the larger macroeconomic environment and is subject to an environment where interest rates remain low over the long term.Such a low-for-long environment may not only directly hurt the profitability and solvency of insurers,but also increase the probability of a reassessment of risk premia(spreads),resulting in an abrupt spike in interest rates.The interest rate risk to which an insurer is exposed is linked to its asset-liability mismatch risk,especially in companies offering long-term guaranteed rateson their products.Previous editions of the GIMAR have highlighted these challenges.In this years report,a more detailed analysis of the challenges linked to an environment ofsuddenly increasing rates can be found in Chapter 3.The Swiss Re Institute14 forecasts that emerging markets will further consolidate their share of global direct insurance premiums to 34%by 2029.In 2018,global direct premiums reached their highest level yet at$5,193 billion,or 6.1%of global gross domestic product(GDP).Although this is a historical maximum,growth has since slowed as a result of a contraction in life markets in China,Europe and Latin America.Technological developments could continue to put downward pressure on pricing and may disrupt markets even further.The gross written premiums at year-end 2018 for several selected jurisdictions are set out inFigure 2a.The figure shows life and non-life premiums as a proportion of total gross writtenpremiums.The life sector is dominant in many jurisdictions,while in Switzerland,for example,the non-life insurance industry drives the market.Figure 2a:Selected jurisdictions gross written premiums(USD billion,year-end 2018)Sources:NBB,FINMA,BaFin,ACPR,IVASS,FSA,FSS,Bank of Russia,PRA,NAIC9Figure 2.1a:Global insurance market renewal rates(Q1 2012 Q1 2019)Source:Marsh:“Global Insurance Market Index First Quarter 2019”Figure 2.1b:Non-life profitability of selected jurisdictions combined ratioSources:NBB,FINMA,BaFin,ACPR,IVASS,FSA,FSS,Bank of Russia,PRA,NAIC2.1 NON-LIFE INSURANCEThe non-life insurance market is expected to grow by 3ch year between 2018 and2020,driven by a growth rate of 8%in emerging markets and 2%in advanced economies.15 In its Global Insurance Market Index:First Quarter 2019 outlook,Marsh reports a sixth consecutive quarter of increasing commercial rates,with a 3%average rise in the first quarter of 2019.This trend has been mainly supported by developments in property insurance and directors and officers liability insurance.Prices in the non-life insurance market fluctuated within a narrow range.Property rates have consistently increased in all regions since the fourth quarter of 2017,following the extreme natural catastrophes that occurred that year.10In its sigma research publication(no.3/2019),the Swiss Re Institute discusses the events of 2018,in which half of total economic losses from natural and man-made disasters were insured($81 billion out of$161 billion).The most severe event was the California Camp Fire,which made 2018 the year with the fourth highest one-year aggregate industry payout(above the$71 billion 10-year average).The non-life market remains soft,although it is showing weak signs of recovery.This puts further downward pressure on its profitability,with returns barely covering the cost of capital.Natural catastrophes made 2017 and 2018 the highest consecutive two-year period of insured losses($219 billion)in recorded history.16 Increasing climate risks have led insurers and supervisors to develop tools to understand the natural catastrophe protection gap.Disasters driven by rising temperatures have a considerable impact on the global economy,with less developed regions being the most vulnerable.17 The combined ratio18 for selected jurisdictions between 2016 and 2018 can be seen below.2.2 LIFE INSURANCEThe Swiss Re Institutes Global Economic and Insurance Outlook 2020 calculates a 1.6%increase in real terms in the global life insurance market throughout 2018.This growth is slightly lower than in previous periods,mainly as a result of a life premiums contraction in China.However,life insurance premiums in emerging markets are expected to increase by 9%in 201920,with those in advanced economies remaining stable.Given the low interest rate environment,the life insurance market will struggle to retain profitability.Traditional life products with fixed guaranteed rates may remain unattractive and policyholders may direct their savings to other markets and risk profiles,even though the opposite trend is being observed in some jurisdictions,such as Italy and France.Life insurers may respond to these challenges by innovating under the current regulatory regime or offering products with lower or no guaranteed benefits at all.As discussed in Chapter 1 and in the 2018 GIMAR,life insurers will need to prepare to operate in a low-for-long environment and protect themselves against interest rate spikes that could lead to lapses and surrenders.Given the current macroeconomic environment,a shift towards riskier investments,such as equities,real estate and collateralised assets,may need to bemonitoried by insurance supervisors.Supervisors track the difference between net investment yields and guaranteed crediting rates for the life industry.In the US,the margin widened last year,with the overall net spread(the difference between the portfolio rate and the guaranteed rate)increasing from 93 basis points in 2017 to 110 basis points in 2018.Figure 2.2a:US life insurance market net spreads19(20062018)Source:NAIC11Figure 2.2b:Profits and losses in the German life insurance market(EUR million,20102018)Source:BaFin2.3 REINSURANCE21The global reinsurance market remains well capitalised.Losses incurred have not increasedrates significantly.Reinsurers are still operating in a soft market,with ongoing consolidation(albeit at a smaller scale than in the past).These and other findings are discussed further in the IAIS Global Reinsurance Market Survey presented in Chapter 4 of this report.As observed in Figure 2.3a,global reinsurance capital recovered in the first three quarters of2019,mainly driven by an increase in traditional capital.This trend was supported by thelower levels of natural catastrophe losses and an upswing in capital markets.22 The proportion of alternative capital reached 14.9%of total reinsurance capital in the first three quarters of 2019,slightly above the percentage attained for the whole of 2017(14.7%)but below the 2018 figure(16.6%).The growth of alternative reinsurance capital in recent years is partly explained by investors searching for higher yields in the capital markets.In its sigma no.3/2019 report,the Swiss Re Institute estimates that primary insurers ceded$260 billion in 2018.23 This represents 5%of all direct premiums written.Catastrophe bonds and insurance-linked securities issuances have remained strong at$3.3 billion in the fourthquarter of 2019$1.1 billion above the 10-year average for the quarter and$1.4 billion above the level observed during the same quarter of 2018.24At the end of 2019,property catastrophe bond issuance dropped by$2.7 billion below thelevel reached in 2018.However,the total limit outstanding reached an all-time high of$41 billion.This trend could be the result of Data from selected European jurisdictions show that interest rate margins remain low,with net spreads in 2018 of 41 basis points in Belgium,76 basis points in Switzerland,121 basis points in Italy and 223 basis points in France.A full analysis of underwriting profits would also need to take into account the undertakings reserve levels.As Figure 2.2b shows,German life insurers profits and losses are split into components:capital/interest rate gains,risk/mortality gains and other profits.As the method to derive the Zinszusatzreserve(ZZR)has changed slightly,the expenses to build up the ZZR reduced in 2018.20 As a result,the profits from capital gains increased.12Figure 2.3a:Global reinsurance capital(USD billion,2006 Q3 2019)Source:AON Benfield Reinsurance Market Outlook,January 2020Figure 2.3b:Property catastrophe bond issuance(USD million,2007 Q2 2019)Source:AON Benfield Reinsurance Market Outlook,September 2019trapped capital where collateral is temporarily“trapped”to act as a buffer against losses.Renewals during 2018 and the beginning of 2019 have seen moderate rate increases,particularly in regions and lines of business affected by natural catastrophes.Competitive pressures are still high,while the ability to release reserves decreased in line with lower solvency positions.Taking these developments into consideration,the European Insurance and Occupational Pensions Authority(EIOPA)emphasises the need for risk-adequate prices for reinsurers.2513CHAPTER 33.1 CYBER-UNDERWRITING:REGULATORY CONSIDERATIONS3.1.1 IntroductionThis section provides an overview of the cyber-insurance market and the main risk management and regulatory considerations.It concludes with a discussion on marketaccess and potential barriers to entry.3.1.2 Market OverviewDefining key cyber-related termsCyber-attacks can affect the company itself,infrastructure providers(such as cloud servicesand payment systems)and individuals whose data,identities and privacy may be exposed ina data breach.26The Financial Stability Boards Cyber Lexicon,published in November 2018,provides thefollowing definitions:Cyber-risk is the combination of the probability of cyber-incidents occurring and their impact.A cyber-incident is a cyber event that:1)jeopardises the cyber-security of an information system or the information the system processes,stores or transmits;or 2)violates security policies,security procedures or acceptable use policies,whether as a result of malicious activity or not.Cyber-resilience refers to an organisations ability to continue to carry out its work by anticipating and adapting to cyber-threats and other relevant changes in the environment,and by withstanding,containing and rapidly recovering from cyber-incidents.Cyber-insurance is an insurance product primarily created to transfer risk,but has evolved into a product that also helps policyholders reduce the impact of their cyber-risk.Types of cyber-insurance productsBecause cyber-insurance is a relatively new risk,coverage may be provided in one of twoways:affirmative cyber-insurance or non-affirmative(or“silent”)cyber-insurance.Affirmative cyber-insurance is a product that explicitly covers cyber-risks.Coverage iscontained within a standalone insurance policy(covering only cyber-risk)or offered as apackage(covering both cyber-risk and other types of property and casualty coverage).Some insurers also offer cyber-related ancillary services(for example,assessing risk management and security practices,and recommending prevention programmes)in combination with cyber-products,which are tailored to the buyers needs.In contrast,non-affirmative cyber-insurance refers to products in which cyber-risk is assumed to be covered because the policy does not include an explicit exclusion forcyber-risk.Although including cyber-risk in these policies may be intentional,it may also be a form of“unintended insurance”,referring to an unknown or unquantified cyber-risk exposure that may trigger other traditional property and casualty insurance events.SPECIAL TOPICS1314Market size and growth outlooksAccording to AON,global cyber-insurance premiums have grown steadily,with an annualgrowth rate of about 15%since 2009.If growth continues at this pace,the cyber-insurancemarket may be worth$7 billion by 2022.Figure 3.1a confirms that the US continues to make up the majority of the global cyber-insurance market,but other markets started to develop rapidly from 2015.27 Despite steady growth,the global cyber-insurance market remains relatively small,making up less than 1%of the total insurance market.The projections for growth shown in Figure 3.1a are driven by two assumptions:1)current silent cyber-insurance policies will not translate into affirmative cyber-products;and 2)the frequency and magnitude of cyber-events will not grow drastically in future.If either of these assumptions is incorrect,the cyber-insurance market may exceed projected levels.Given that the cyber-insurance market is relatively young,detailed information about markets other than the US is not yet publicly available.The penetration rate varies across countries,28 amounting to about 30%in advanced economies,which is low compared to other lines of insurance.29 The IAIS Global Monitoring Exercise,starting in 2020,may provide more detailed information on the cyber-insurance market.Future market growth is expected to be largely propelled by technological innovation,whichwill amplify customers vulnerabilities and is likely to increase the frequency,magnitude andvolatility of cyber-attacks.Digital transformation and technological progress are creating a more competitive environment,producing business opportunities for new entrants and incumbents seeking to enter the cyber-insurance marketplace.Customers will benefit from the bundling of products,such as insurance sold with information technology(IT)mitigation and recovery services.Insurers can take advantage of this undeveloped market,given its high capacity and the potential for increased take-up rates.They can adjust their overall market strategies and operations,enter into partnerships,and/or offer new products,which in turn could lead to high insurer growth rates and profits.30Insurance technology(InsurTech)startups and other partnerships may provide an opportunity to encourage market participation.InsurTech could facilitate the development of new products or offer innovative methods of assessing IT risks.Startups and partnerships could also provide other valuable services such as access to a large database of information or customer support in risk mitigation and incident response(whether from a technical or legal perspective).Figure 3.1a:Global cyber-insurance premiums and future estimates(USD million,20092022)Source:Aon Cyber Insurance Market Insights Q3 20188000700060005000400 030002000100002009 2010 2011 2012 2013 2014E 2015E 2016E 2017E 2018E 2019E 2020E 2021E 2022ERest of the world Europe USMillions15This type of business collaboration is already happening in other markets and incentivises further developments in the insurance market.As these opportunities develop,insurers will need to assess the potential value of new partnerships,while supervisors will need to assess their role in supervising the activities of these businesspartners.The hope is that new players in the market may improve efficiency and create innovative solutions that meet insurers specific business needs and expectations.3.1.3 Risk Management and Regulatory ConsiderationsCyber-risk measurementAt a basic level,measuring cyber-risk uses the same methodology as other risks:an underwriter must project the likelihood of covered incidents at different levels of severity.Insurers may use a variety of data sources,including:Insurer experience data Counterfactual risk assessment Third-party cyber-risk models Worst-case scenario analysis Compliance with cyber-security standards.Four main approaches have been used in the past,31 but an overall lack of harmonisation creates wide variations in pricing and product offerings.Insurers may quote differently for the same type of risk,depending on what they define as a cyber-risk,cyber-incident or cyber-attack,and this determination will be based on a variety of available data sets and other underlying information used to price the risk coverage.Questions remain about the reliability of traditional cyber-models as very few insurers have the capability to accurately measure cyber-risk.The Geneva Association has noted that property catastrophe modelling took between 25 and 30 years to mature,32 and that modelling was based on a risk that had a clear geographic footprint and extensive experience data.In addition,accurately measuring cyber-risks involves several challenges:given that this risk has only recently developed,experience data is limited;the occurrence of an event relies on the unpredictability of human nature;and the severity of the loss depends on a nearly endless number of variables that occur in a highly connected digital environment.As the industry continues to develop advanced modelling techniques to account for these factors,deterministic scenario-based methods have provided a working solution in the interim.Some modelling vendors are developing dedicated cyber-risk models,with several creating predictive models that seek to specifically quantify non-affirmative risk.All cyber-models must be continuously developed on an iterative basis in response to the dynamic nature of cyber-risk.Insurers and modellers can examine previous cyber-events(and near misses)using counterfactual analysis to identify potential worst-case scenarios and calculate maximumprobable exposure levels.Insurers,particularly new entrants to the cyber-insurance market,also rely on knowledge gained from modelling and underwriting in established categories,particularly in complex and specialty risk classes,such as pandemics and terrorism.These risk classes influence the development of algorithms,and underwriters can draw on policy language used for these complex risks to limit their potential exposure in the event of a claim.Other insurers rely on external services(outsourcing),integrating the information theyreceive with their experience and public data,or they develop premiums by replicating with some adjustments the rates applied by their main competitors.In this scenario,where data and modelling are scarce,the risk of mispricing and over/under-reserving is high,especially when comparing rates applied to products with different characteristics(type and scope of coverage,risk included/excluded)and a low degree of standardisation.Given the limitations of current models,some insurers rely on other methods to measure cyber-risk.Primarily,pricing reflects a qualitative assessment of the insureds security environment.This level of assessment will depend on the amount of protection being sought under a policy.A lower level of coverage may rely on the use of checklists and assessing the presence of standard security protocols.Large clients posing a high level of risk are generally subject to highly QUESTIONS REMAIN ABOUT THE RELIABILITY OF TRADITIONAL CYBER-MODELS AS VERY FEW INSURERS HAVETHE CAPABILITY TO ACCURATELY MEASURE CYBER-RISK.16individualised and detailed IT security audits.These underwriting processes also help identify areas of vulnerability and provide an opportunity for the insured to improve their resilience and reduce the overall level of risk.A qualitative assessment also supports the insurers ability to form a comprehensive understanding of its client bases overall security defences,and improves its ability to differentiate risks and refine pricing among policyholders.This leads to the development of certain standardised data protocols used to measure cyber-risk in an insurers portfolio.Similarly,supervisors can also play a role in reviewing an insurers practices to ensure appropriate risk management.As part of this effort,insurers and supervisors can reviewexternal standards and incorporate them into their own risk assessment processes.Insurers may also attempt to measure risk by analysing scenarios or using other risk assessment tools.33Data availabilityThe market suffers from a lack of experience data,which makes underwriting cyber-risk difficult.Although more data are becoming available,most cyber-incidents are underreportedby companies,whether due to fear of reprisal or concerns about reputational damage.In addition,cyber-risk experience data can quickly become dated and lose value as attackers rapidly adapt to exploit new vulnerabilities and evade cyber-security measures.Only a few big players with extensive experience in the cyber-market can generate their ownmass of data,and they are reluctant to share that experience with other companies to ensure they remain competitive and gain an advantage in underwriting.34 This data paucity may weaken the insurers confidence in pricing and underwriting cyber-insurance.At the same time,buyers may question the appropriateness of the premium and coverage offered.These factors depress sales and reduce the penetration rate.35Although current measurement methods attempt to access a broad range of information,insurers still need a centralised source of information/data repository about cyber-events.Consensus is building that the evolving nature of cyber-risk,combined with the cross-border and cross-industry economic implications of a cyber-attack,demand an increased level of coordination both within the insurance industry and beyond.Insurance supervisors can assist with monitoring overall cyber-risk aggregation within theindustry by collecting data.In the US,the National Association of Insurance Commissioners(NAIC)requires insurers to include a cyber-supplement in their annual data reporting.Supervisors can also help mitigate systemic risk by facilitating the sharing of informationrelated to cyber-risk,and encouraging insurers to share information with each other.Not onlydoes this increase resilience levels of similarly situated policyholders,but the collectedinformation could contribute to the ability of the insurance industry to accurately assessaggregate risk levels and predict how risk may evolve in future.Although an insurance-centricrepository is ideal,current information-sharing repositories include:Financial Services Information Sharing and Analysis Center(FS-ISAC): National Institute of Standards and Technologys National Vulnerability Database(US):nvd.nist.gov Department of Homeland Securitys Cyber Information Sharing and Collaboration Program(US):www.dhs.gov/cisa/cyber-information-sharing-and-collaborationprogram-ciscp FBIs Infraguard(US):www.infragard.org Malware Information Sharing Platforms Threat Intelligence Platform:www.misp-project.orgCloser analysis of the governance and security issues that are preventing the creation of anincident data repository is needed,36 but for now supervisors can continue to share generalbest practices and experiences with each other in order to improve the industrys ability to measure and mitigate cyber-risk.Supervisors will also need to build a level of trust and ensure ongoing communication with insurers to ensure that they can freely share information(with both supervisors and each other)without concerns about competition or fear of reprisal.The Operational Riskdata eXchange Association is an example of a successful industry-led data-sharing mechanism outside of cyber-risk.The association was set up to“provide a platform for the secure and anonymised exchange of high-quality operational risk loss data from around the world”.37 Banks and insurers provide anonymised data on operational risk losses in return for access 17to the data set.This creates a growing pool of data that can be used to improve the industrys understanding of operational risk.A similar mechanism for cyber-risk could also be effective.To encourage the development of an insurance-centric repository,supervisors could standardise the amount and type of data needed on each cyber-incident.This would make it easier for insurers to share information.Non-affirmative cover and risk accumulationSupervisors and the industry have expressed concern about non-affirmative cyber-risks.The Bank of Englands Prudential Regulation Authority(PRA)survey on cyber-underwriting found that,for non-affirmative risks,most firms reported considerable exposure on many traditional lines of business,including casualty,financial,motor,and accident and health.The survey found that firms did not have well-developed quantitative assessment frameworks for non-affirmative exposure and that the assessments generally involved stress tests and expert elicitation.38In 2018,the EIOPA asked 11 insurers if it was possible to quantify non-affirmative exposure.Nine described it as“very difficult”and the other two as“nearly impossible”.39 In a later survey,only five insurance groups out of the 26 that responded to the question reported that they had cyber-exclusions on property and casualty policies.40 Some of those that did not provide exclusions said that it was due to the difficulty of relating the risk for example,personal injury to a cyber-incident.Other respondents did not see cyber-risk as a current threat.The Monetary Authority of Singapore,in collaboration with the IMF,conducted a stress test on cyber-risk as part of the 2019 financial sector-wide stress test exercise and the IMFs Financial Sector Assessment Program.Direct insurers were asked to measure their exposures to cyber-risk as a result of the affirmative and non-affirmative coverage that they had written.The insurers expected claims from affirmative and non-affirmative cyber-coverage to be manageable,mainly due to the reinsurance arrangements in place.However,one key observation from the exercise was that insurers non-affirmative cyber-exposure was five times more than their affirmative exposure.Moving forward,insurers with exposures to non-affirmative cyber-coverage intend to include appropriate exclusion clauses in their contracts.41Potential mitigants to non-affirmative exposure include writing explicit cyber-exclusions,increasing premiums to reflect the increased risk,and attaching specific limits to coverage.Many insurers are starting to carefully review policy language to minimise their potential exposure to unintentional cyber-coverage,which has lowered the perceived level of non-affirmative risk by insurers.Although this action occurs after a policy has been written,it is one way in which insurers have been developing their capabilities to measure cyber-risk and ensure healthy loss ratios.In some jurisdictions,regulators have issued guidance on non-affirmative risk.In a supervisory statement in July 2017,the PRA advised that it expected insurers to be able to“identify,quantify and manage”both affirmative and non-affirmative cyber-exposure.42Non-affirmative cyber-risks can quickly accumulate.A cyber-incident may affect multiplebusinesses at the same time due to shared connections(such as payment systems,operating systems,internet providers and cloud services).A cyber-incident that takes advantage of the interdependency of businesses and infrastructure may even compromise the supply chain,resulting in extensive economic losses and large-scale disruptions.Although no such attack has occurred to date,a large-scale cyber-attack that exploits a mass vulnerability or cloud service provider could result in catastrophe-level losses an extreme act of cyber-terrorism affecting infrastructure could result in up to$1 trillion in economic losses.43 Concerns about this type of event have led the industry to take a fairly conservative approach to underwriting cyber-risk,even though the line of business has been largely profitable to date.Until a large-scale event happens,it will be difficult to predict the impact it would have on the insurance industry.Concerns about the aggregate level of risk have led to discussions about ways to properly address potential accumulation risk.IN 2018,THE EIOPA ASKED 11 INSURERS IF IT WAS POSSIBLE TO QUANTIFY NON-AFFIRMATIVE EXPOSURE.NINE DESCRIBED IT AS“VERY DIFFICULT”AND THE OTHER TWO AS“NEARLY IMPOSSIBLE”.18Currently,companies use models and stress testing scenarios to identify and quantify accumulation risk.This risk is then transferred to reinsurers and risk-sharing pools as part of an insurers overall risk management strategy.3.1.4 Market Access and Potential Barriers to EntryInsurers are struggling to grow in a slow-recovering economy,and cyber-insurance presents an opportunity to gain market share.But new entrants face several challenges,including limited historical data,evolving methods of measuring cyber-risk and a high degree of uncertainty about the level of risk.This section focuses on the additional drivers that insurers must consider when deciding whether to enter the cyber-insurance marketplace.It also discusses current government initiatives supporting the markets growth.Development of cyber-expertiseA key priority for insurers exploring the cyber-insurance market is to ensure they have sufficient technical expertise to understand the risks associated with this type of underwriting and to support new cyber-related business projects.Access to skilled experts is important for the success of market participants,but uncertainty around market development makes it difficult to find people with the skills needed to understand the nature of cyber-risk,design contracts,underwrite and price risk,and manage an insurers risk portfolio.This shortage of skilled experts is being addressed through training programmes and recruitment campaigns to hire experienced individuals.Insurers may also rely on external expertise,as noted by respondents to a PRA survey.Methods of risk transfer and pooling for insurer considerationIn the absence of actuarial/historical underwriting data and given the difficulty in accurately measuring risks,many insurers rely on mechanisms to transfer their own risk.44Reinsurance in the cyber-market is expected to grow at a fast pace.Insurers have a strongpreference to work with reinsurers because they can provide broader data sets of information,give comprehensive underwriting information to support their premium pricing process,and quantify cyber-risks.Reinsurers have access to information on threats and vulnerabilities and,as such,could help reduce the gap in data availability for underwriting and modelling cyber-risk.Reinsurers are currently the main method of transferring risk to reduce insurers exposure and losses.In Europe,quota share treaty contracts45 appear to be the most common type of contract used,followed by proportional facultative reinsurance.46,47Cyber-risk can also be transferred to the capital markets using alternative risk-transfer instruments,although using insurance-linked securities such as catastrophe bonds,sidecars and industry-loss warranties can be challenging.For example,while insurance-linked security vehicles are primarily issued to cover catastrophe risks(and,to a lesser extent,products in other business lines),issuing such an instrument to cover cyber-losses is difficult due to a lack of data and modelling capabilities.Using insurance-linked securities for cyber-risks may also be less appealing to capital market investors due to the unpredictability of cyber-risk and the potential correlated impact on bonds and equity.However,a pooling mechanism could potentially facilitate the issuing of insurance-linked securities for cyber-risk,supported by regulatory measures or tax incentives to encourage risk transfer to capital markets.48Some jurisdictions use consortiums or risk-pooling mechanisms to manage insurer cyber-risk.Risk-pooling mechanisms are instruments that can:Carry a higher level of risk through diversification,which reduces overall uncertainty and leads to lower coverage prices.Facilitate the participation of smaller insurers by providing access to others experience and limiting risk exposure.Standardise products among pool members(who are likely covering similar risks).Allow insurers to share claims experience and reduce the data gap for underwriting and modelling cyber-risk.Allow the industry to cover cyber-events that would otherwise be uninsurable and permit further risk mitigation through the use of reinsurers and capital markets.3.1.5 ConclusionsNon-affirmative cyber-risk remains prominent and a lack of standardisation in policy language has exacerbated this issue,resulting in many insurers being uncertain about their overall levels of exposure.Cyber-risk models are relatively immature due to the lack of underwriting experience and availability of data,paired with a volatile and fast-evolving risk.Insurers therefore rely on other methods of risk measurement,including individualised risk assessments,which provide policyholders with a map of risk mitigation guidelines but make it difficult for insurers to 19engage in comparative pricing and assess their overall risk portfolio.Information sharing is critical but underused.The use of reinsurance and other risk-pooling mechanisms can help promote the flow of information while offering insurers the benefits of risk transfer.Although many public and private initiatives and studies have collected information on previous cyber-incidents,coordinated actions by supervisors will play a key role in streamlining the variety of data sources available to measure cyber-risk,encouraging the standardisation of data collection while maintaining the benefits of competition,and fostering information sharing to improve insurer underwriting and encourage market growth.Insurers may not be fully aware of their overall risk exposure,which affects their ability to accurately calculate premiums,set appropriate limits and adopt appropriate pricing strategies.Given the evolving nature of the cyber-landscape,companies should demonstrate a continued commitment to developing their knowledge of cyber-insurance underwriting risk.Supervisors need to share information and best practices to enhance their own ability to evaluate the pricing and exposure of insurers within their jurisdictions.They also need to consider how they can support an integrated approach to cyber-risks that will adequately reflect the risk in insurers strategy and risk appetite.Initiatives are under way in several countries to foster greater risk awareness and to push insurers to adopt conscious risk management and supervision,but additional efforts are required by both supervisors and insurers.3.2 THE RISKS OF INTEREST RATE SPIKES WHEN MOVING OUT OF A LOW INTEREST RATE ENVIRONMENT3.2.1 Introduction:The Different Aspects of Interest Rate Risk for an InsurerThere is a time gap between insurers receiving premiums and making payments if a claim arises.During this gap,premiums are invested in financial assets.Ideally,the cash flows of these financial assets closely match the cash flows of liabilities but,in practice,these cash flows dont match perfectly for various reasons.One reason is that finding assets with a maturity and cash flow profile similar to the liabilities is challenging.It is also possible that insurers prefer to take on more risk in order to increase their expected returns.As a result,insurers actively participate in capital and money markets.According to data from the Federal Reserve Bank of Chicago,49 US life insurers invested$5.4trillion in total in 2013,while US non-life insurers50 invested$1.7 trillion in 2018.Respectively,about 75.5%and 57.9%of US life and non-life insurers investment portfolios comprise bonds.Similarly,insurers in the European Union(EU)invested 51%(not taking into account unit-linked investments)of their total assets of 11.3 trillion in bonds and an additional 5%in loans and mortgages.51 The value of these bonds is directly affected by interest rate changes,exposing insurers to risk.Insurers are also exposed to interest rate risk through liabilities when there is a mismatch between the cash flows of assets and liabilities.If interest rates move,insurers are affected in the following ways:Portfolio revaluation effects.As interest rates change,the market value of assets and liabilities that are sensitive to the interest rate also changes.Longer-term bonds and liabilities are affected more than shorter-term items because they are more sensitive to rate changes.Reinvestment effect.Insurers also rely on bond interest payments to match liabilities cash flows.When interest rates rise,buying bonds with large enough coupon payments to match liabilities cash flows is easier.However,the opposite is true when interest rates go down.Lapse rates.Moving interest rates(and related commercial incentives)may influence policyholder behaviour.Rising interest rates may increase the appetite of policyholders to lapse and seek other investment alternatives,while decreasing interest rates may induce policyholders to stay in contracts with high guaranteed interest rates longer than expected.Life and non-life insurers often have a different sensitivity to interest rate movements.Life insurers offer long-term products such as whole life insurance with and without a savings component.To match these products liability cash flows,life insurers try to buy long-term assets with similar cash flows.The better the insurer can match asset and liability cash flows,the less pronounced its sensitivity to interest rate movements will be.But finding the right match is not always possible.Non-life insurers invest in bonds and other assets that are sensitive to interest rates,but are affected to a lesser extent than life insurers.Property insurers,for example,tend to have short duration liabilities and therefore require shorter-term bonds to match their liabilities.As it is often easier for 20non-life insurers to find these shorter duration bonds,their sensitivity to interest rate changes is less pronounced.Whether or not this interest rate sensitivity is translated to the balance sheet of the insurer depends on the valuation system applied.For example,in its most basic form,a life insurance reserve reflects the changes in the companys net asset value,based on actuarial assumptions about interest rates,mortality,lapses and so on.In mark-to-market regimes,such as Solvency II,the market prevailing risk-free rates are used to calculate the best estimate of liabilities/reserves(the actuarial present value of claims and expenses minus the actuarial present value of premiums,gross of expenses).As risk-free interest rates change in the market,the valuation of life insurance reserves under such a regime changes as well(see Box 1).Not all regulatory systems are fully mark-to-market.Under US Generally Accepted Accounting Principles,for example,reserves are valuated using the prevailing economic assumptions at the date when the insurance contract was written.Insurers make an allowance for a deficiency reserve,but in general interest rate volatility is not fully apparent in the valuation of the liabilities in such a regime.Under US accounting principles,mark-to-market assets can be revaluated based on changes in interest rates,with liabilities exhibiting less volatility due to little revaluation.Spread movements also affect insurers balance sheets under a full mark-to-market regime.While such movements directly affect spread-sensitive assets,the degree to which they affect liabilities depends on the valuation approach used(particularly the discounting features).Solvency II has long-term guarantee measures,which partly transfer the spread movements of assets to liabilities by adding part52 of the spread to the risk-free discounting rate.This portion often represents the part of the spread that is not related to credit fundamentals.There is no agreement among economists about the extent to which the risk-free rate should be adjusted for spread changes.Certain types of life insurance are not sensitive to interest rate movements.Unit-linked insurance often transfers investment risk to the policyholder,while the insurer bears some residual risk(for example,if there is rider coverage).21Although insurers are not liable to compensate investment losses for these types of insurance,changing interest rates can affect the desirability of these products.If interest rates are low,exposure to higher risk may be desirable and unit-linked products may be more appealing53 than traditional products.The interest rate environment also determines the profitability of all types of insurers.For example,although they are less sensitive to interest rate movements,non-life insurers profitability also depends on their investment income.The extent to which investment income is required to meet profitability goals depends on the ability of non-life insurers to achieve sound technical underwriting the better they manage to write premiums that cover their claim payments and expenses,the less non-life insurers depend on their investment income to be profitable.Figure 3.2a:Underwriting profit life sector(USD billion,2018)54Source:BloombergFigure 3.2b:Underwriting profit non-life sector(USD billion,2018)Source:Bloomberg22However,in a highly competitive underwriting environment,downward pressure on insurance premiums may decrease underwriting gains and,as a result,increase non-life insurers reliance on investment income.If life insurer products have a guaranteed savings component(such as universal life or variable annuities with guaranteed rates),their profitability is also strongly affected by the prevailing interest rates.By guaranteeing a return,insurers assume the obligation to cover the difference between the investments return and the guaranteed return,even if the investment return is lower than the guaranteed rate.The relation between investment income and profitability of different types of insurers is further discussed below.Figure 3.2a shows the life underwriting profit of 50 large life insurers,covering broad geographic regions such as Asia,Europe and North America.The sample for 2018 indicates that the median underwriting loss was$1.24 billion,with the lowest 10th percentile losing$8.13billion.At the same time,the 90th percentiles underwriting profit reached$10.54 billion due to an extraordinary year for one life insurer.In previous years,the 90th percentile underwriting profit was negative.Figure 3.2b shows the underwriting profit of 50 large non-life insurers,55 covering the same broad geographic regions.The graph illustrates how non-life insurers have,on average,profitable underwriting activities.For 2018,the median non-life underwriting profit was$0.31billion,while the 10th percentile underwriting loss was$0.13 billion and the 90th percentile underwriting profit was$2.16 billion.The figures above illustrate that,while many life insurers rely on investment income to achieve positive profits,most non-life insurers are profitable without accounting for investment income.As such,the profitability of life insurers is more vulnerable to interest rate risk.In some instances,composite insurers can cross-fund their activities by having life segments at an underwriting loss and non-life segments at an underwriting profit.The next part of this special topic discusses the macroeconomic aspects and impact of the current low-yield environment on insurers,before listing the possible implications of a scenario where interest rates revert to higher levels.This section relies on existing studies and impact analyses performed by supervisory authorities and central banks.3.2.2 Moving Out of a Low Interest Rate EnvironmentThe impact of a low interest rate environment on the insurance sector As highlighted in Chapter 1(see Figure 1.2a),several developed economies are still experiencing low nominal and real interest rates.When the financial crisis hit in 2007,policymakers around the world responded by easing monetary conditions.As a result,interest rates fell precipitously.When the recession hit,the Federal Reserve moved swiftly to cut rates,which eventually reached close to zero.After 2016,rates slowly climbed,but events in 2019 have prompted the Federal Reserve to start cutting rates again for the first time since 2008.An analysis of data spanning July 1954 to June 2019 shows that the federal funds rate has experienced an average of 4.8%and a maximum of 19.1%,demonstrating how recent rates are far below historical averages.Since 2011,the European Central Bank has gradually lowered its policy rates.The marginal lending facility rate and main refinancing operations rate have been as low as 0.25%and 0%respectively since 2016.The deposit facility rate turned negative as low as-0.50%since 18 September 2019.Based on these recent developments,it is becoming evident that developed economies are increasingly considered to be in a protracted low,and sometimes even negative,interest rate environment.For several of the economies confronted with low interest rates,there is a debate about whetherthis low-yield environment is a temporary phenomenon,or whether it will remain over thelonger term.These two opposing views were discussed by the ESRB in its report56 on low interest rates.Each argument is based on different views on the main drivers of interest rateevolutions in recent decades.One view attributes the current environment to cyclical(“financial cycle”)factors;the other relates it to structural(“secular stagnation”)factors.The“financial cycle”view highlights how different factors drove interest rates down in recent years.These low rates could be here for a long time,but are not necessarily expected to stay permanently and should recover.It is argued that,following the excessive debt that economic agents accumulated in the period leading up to the global financial crisis,the need to deleverage contributed to lower investment and interest rates.In addition,nominal interest rates fell in response to the recession and the accompanying monetary policy responses by major central banks.23As the factors are bound to reverse at some point,interest rates are also expected to increase.The“secular stagnation”view reasons that,beyond cyclical factors relating to the globalfinancial crisis,there could also be structural factors causing low interest rates in several developed economies.These structural factors have a more permanent effect on interest rates.Demographic trends and a decline in total factor productivity growth(supply-side factors),as well as an increased preference for scarce safe assets and rising inequality(demand-side factors),have all contributed to the low interest rate environment.Consequently,even if the role of cyclical factors diminishes over time,nominal interest rates are expected to stay relatively low for a long time due to structurally depressed real rates.Because of the potentially devastating effects of long-lasting low interest rates on the insurance sector,particularly for life insurance,many insurance supervisors around the world have focused on measuring the impact of a long-lasting low-yield environment.The EIOPA,for example,has tried to measure the impact of a low-for-long interest rate scenario on the EUs insurance industry through a series of stress test exercises conducted over the last few years.The 2011,2014,2016 and 2018 stress tests all contained at least one scenario focusing on the impact of low interest rates.In the most recent stress test exercise(2018),a scenario of low yields was combined with a series of stresses on other asset classes and a positive shock on longevity(more details can be found in the 2018EIOPA stress test report).57 In this downward yield curve scenario,the aggregate solvency capital ratio of the participating insurers dropped by 64.9 percentage points to 137.4%,with seven participants reporting a ratio below 100%(see Figure 3.2c).When excluding Solvency II transitional measures,58 the solvency capital ratio would drop even further,to 124.1%,with 20 participating groups showing a ratio below 100%.The 2018 EIOPA stress test illustrates how low yields increase the market value of the participating insurers technical provisions.For example,the participants life insurance technical provision increased by 6.1%due to the lower discounting curve(and the longevity shock).Often this is partly compensated by an increase in the value of the assets on the insurers balance sheets(bond portfolios in particular are positively affected by interest rate decreases).As several insurers in the EU still have material life insurance portfolios with long durations that offer a guarantee and are not always fully matched by corresponding assets,the overall net effect of low interest on the Solvency II capital ratio is often negative for insurers.As such,the 2018 stress test confirmed the vulnerability of the EUs insurance sector to long-lasting low interest rates.As explained above,life insurers typically derive part of their profits from the spread between their portfolio earnings and what they guarantee on insurance policies.During times of persistently low interest rates,life insurers investment income is expected to decline,calling into question whether insurers will still be able to meet contractually guaranteed rates to policyholders.The NAIC regularly conducts a study on the impact of the low interest rate environment on the life insurance industry in the US,including the effect on the net investment spread.59 Data have been gathered from 2006 to 2018 and the results are discussed in Chapter 2 of this report(Figure 2.2a).The data show a gradual decline in the life insurance industrys net portfolio yield over the period,reflecting the lower interest rate environment within which the industry had to invest its positive cash flows(premiums plus investment income less policy claims).The US life industry lost 62 basis points of net yield between 2006 and 2018.As many developed economies have had low interest rates for a considerable length of time,market players are already adapting to this new reality.These adaptations may create several risks and structural changes in financial markets.60 Investors searching for yields may pursue risky asset positions beyond their normal risk-bearing capacities.If the low-yield environment persists,demand for lower-rated and/or less liquid assets may increase in the hope of finding higher returns.According to a study conducted at the EIOPA level,the EU insurance sector has shown signs of such behaviour.61 Low interest rates may also prompt life insurers and pension funds to switch IF THE LOW-YIELD ENVIRONMENT PERSISTS,DEMAND FOR LOWER-RATED AND/OR LESS LIQUID ASSETS MAY INCREASE IN THE HOPE OF FINDING HIGHER RETURNS.24to unit-linked/defined contribution products,increasing the competition with investment funds,for example.62 Different types of investors may start to pursue similar investment strategies,looking for those few asset classes that still promise a decent return.This could,in turn,lead to crowded asset positions.This behaviour will make the insurance sector vulnerable when interest rates start to rise again.Increasing interest rates are expected to drive asset prices down,which means bond prices will fall.This may cause market participants to dispose of certain asset classes.The disposal of crowded asset positions could be combined with liquidity pressures.The degree of the insurance sectors vulnerability to rising interest rates is strongly linked to the business model of the insurer and the speed of this interest rate reversal scenario.It is generally agreed that a gradual rise in interest rates would positively affect the insurance sector because earnings(particularly for life insurance)and solvency would be expected to increase again.However,a sudden reversal in yields and asset re-pricing may materialise if market players start to reassess risk premia in light of low growth prospects,or collectively unwind potentially crowded asset positions.If this sudden reversal of yields is combined with lower structural market liquidity,several financial market players could suffer severe losses.The losses for the insurance sector would be even more pronounced if this scenario is combined with consumers insurance contracts lapsing.This could happen if consumers have better prospects elsewhere(banks and asset managers can react more rapidly to the changing interest rate environment),63 or if they lose their trust in insurers facing losses.The likelihood of such a sudden reversal in yields is being debated.However,following institutional investors search for yields and a potential build-up of crowded and leveraged positions in higher-yielding,lower-quality asset classes,even a gradual rise in interest rates could have a significant adverse impact on financial markets.As liquidity and spreads revert to previously observed levels,asset prices would be corrected,creating stress in these markets.Such stress,in combination with asset price misalignments,increases the likelihood of abrupt price reversals.As these reversals negatively affect different financial players at the same time,corrections could happen promptly and abruptly as investors try to look for the“same way out”in a market characterised by lower liquidity.The remainder of this section focuses on the potential impact on the insurance sector of a sudden reversal of yields.Where studies are available that could help assess this impact,the assumptions are described and the results are discussed in more detail.Measuring the quantitative impact on insurers of suddenly increasing interest ratesThere are various ways to measure the impact of increasing yields on the balance sheet andthe profitability of the insurance sector.Through a bottom-up stress test,supervisors can ask a sample of participating insurers to assess the quantitative impact of the scenarios using their models and projections.Supervisors can also assess the impact of a varying set of interest rate scenarios using their own top-down model,without having to involve the insurers themselves.EIOPA stress testIn its 2018 bottom-up stress test exercise,the EIOPA included an upward yield curve scenario.This scenario assumed an abrupt and sizeable reversal of the risk premia observed in global financial markets.As part of this scenario,the 10-year euro swap rates term structure shifted upwards by 85 basis points and by more than 100 basis points for currencies in other major advanced economies(such as the pound sterling and the US dollar).The increase in risk premia was then assumed to trigger further concerns about the debt sustainability of some EU sovereigns,widening the spreads of EU government bonds.Government bond spreads increased by 36 basis points on average.The economic uncertainty stemming from the abrupt change in yields would also trigger shocks in other financial markets(equity markets),64 along with an increase in lapses,as explained above.Lapse rates were assumed to increase by 20%for all non-mandatory life insurance products,assuming policyholders prefer to shift their investments away from such products.Higher-than-expected inflationary pressures were assumed to induce a shortfall in liability claims reserves in general insurance.This shortfall was triggered by annual claims inflation of 2.24%higher than assumed for non-life liabilities.In the upward yield curve scenario,total assets over liabilities in the EU insurance sector would drop from 109.5%to 107.6%.Excess assets over liabilities would drop by 32.2%.The scenarios impact would be driven by a significant drop in the value of assets(-12.8%for government bonds,-13%for corporate bonds 25and-38.5%for equity holdings).The technical provisions would only decrease by 17%(mainly driven by a decrease in life technical provisions),which means asset losses would outweigh liability gains.These drivers would cause the aggregate solvency capital ratio to drop by 57.2 percentage points to 145.2%.Six out of 42 participants would drop below a solvency capital ratio of 100%.Not taking into account the long-term guarantee measures on the mark-to-market balance sheet of Solvency II,which were designed to reduce the impact of short-term spread volatility,would result in 21 out of 42 participants dropping below a solvency capital coverage ratio of 100%.The upward yield curve scenario demonstrates that EU insurers would be vulnerable not only to prolonged low interest rates,but also to sudden increases in yields.The scenario also illustrated how a sharp and sudden increase in yields,driven by a revaluation of the risk premia,higher lapses in insurance contracts and increasing non-life claim costs due to higher inflation,can have a substantial negative effect on the capital position of EU insurers.Banque de FranceTwice a year,Banque de France publishes a report on risks,vulnerabilities and strengths in the French financial system.65 A chapter is dedicated to risks facing financial institutions,including the French insurance sector.In June 2017,the report noted that the unprecedented low interest rate environment was eroding the margin and return of insurers by forcing them to rethink their traditional business models.Based on this finding,the report highlighted that,whether the low-yield environment continues or whether it comes to an abrupt end,both scenarios represent a considerable risk to the French insurance sector.In the event of a 200 basis points increase in long rates,French insurers rate of return would remain at a level that was relatively equivalent to the rate offered by a new player entering the market,who would not be stuck with a legacy bond portfolio.As insurers portfolios are still largely composed of bonds with high nominal yields and long durations,they would be able to benefit from these bonds for quite a while.However,if the low interest rate environment persists,older higher-yield bonds would need to be replaced with new,often lower-yielding,bonds.If interest rates suddenly increased,a new player entering the French market would be able to offer more attractive guaranteed rates,potentially triggering policyholders to switch products.Current market players would have to use profit-sharing and capitalisation reserves to maintain their attractiveness and prevent policyholders from moving out of non-unit-linked contracts to invest in higher-earning or more liquid savings vehicles.This strategy will be more difficult to apply the longer the low-yield environment persists.The different scenarios projecting the rate of return on insurers investments are set out in Figure 3.2c.The Banque de France study clearly illustrates the link between the duration of the low-yield environment,the dynamics of a sudden interest rate shock and the risk of lapses in policyholders insurance contracts.The longer the low-yield environment persists,the more impact a sudden increase in interest rates may have as insurers could be“stuck”in low-yielding investments,whereas other saving alternatives(bank deposits,investment funds)may be able to adapt more swiftly to the new interest rate environment.This,in turn,could trigger a significant number of lapses in policyholders contracts.The impact on insurers would then strongly depend on the surrender behaviour of policyholders.The vulnerability of an insurance contract to surrender is linked to many factors:Is there a fiscal penalty in case of surrender?Do policyholders need to pay a surrender penalty?How high is the difference between the rate guaranteed/obtained in the current contract and the rate that can be obtained in other saving alternatives?THE UPWARD YIELD CURVE SCENARIO DEMONSTRATES THAT EU INSURERS WOULD BE VULNERABLE NOT ONLY TO PROLONGED LOW INTEREST RATES,BUT ALSO TO SUDDEN INCREASES IN YIELDS.26The results of the study underlined the sensitivity of several prudential metrics to insurers assumptions regarding policyholder behaviour.As such,Banque de France recommended that insurers test different sets of surrender assumptions within the framework of their own risk and solvency assessment.This should help inform insurers about their vulnerability to surrender risk under different scenarios and improve the management of this risk.US Federal ReserveThe US Federal Reserve also conducted a study on how life insurers would be affected bythe economy moving out of the current low interest rate environment.A top-down model ofinterest rate risk in Hartley et al.(2016),as compared with the bottom-up analysis presented above,was used to measure the effect of an increase in interest rates on the performance of life insurers in the US.66 The model includes a broad stock market return factor to control for changes in the overall economy,as well as a 10-year Treasury bond return factor.The coefficient on the Treasury bond returns is the measure of interest rate sensitivity.The model is estimated using a two-year rolling window of weekly returns data.The model in Hartley et al.was updated to include data from 2004 to 2019.As seen in Figure 3.2d,the coefficient on the Treasury bond returns(left axis)is negative.While it is significant after 2011,it is not statistically different from zero before 2011.A negative coefficient means that negative Treasury returns(an increase in Treasury yields)generally translate into positive returns for insurers.According to the model,an interest rate increase would be good for insurers.For example,a hypothetical increase from 2%to 3%in the 10-year Treasury bond yield would generate a positive return for insurers of 8.1%.67The negative correlation between Treasury returns and insurers returns(or positive correlation between Treasury yields and insurers returns)arises because the duration of life insurers liabilities is longer than the duration of their assets.This means that when yields increase,the decrease in the present value of assets is smaller than the decrease in the present value of liabilities.Figure 3.2c:Projected return on assets68 in the event of an increase in interest rates(%)69Source:2018 IAIS survey27The model of interest rate sensitivity indicates that,based on historical data analysis,moving out of the current low interest rate environment would be beneficial for life insurers.Higher interest rates would increase the discount rate and reduce the present value of cash flows.Since insurers liabilities have a longer duration than their assets,this works in favour of insurers.However,under certain circumstances this correlation can change.An increase in interest rates might indirectly decrease the value of the companies insurers invest in,reducing the value of the insurers capital.For example,companies in a deteriorated financial condition with high leverage might lose value if the cost of debt increases.For insurers heavily invested in these types of companies,an increase in interest rates might result in a significant loss of capital.An increase may also make insurance savings products less attractive for policyholders.These products are usually structured to generate returns above those of safe investments like government bonds but below those of risky investments like stocks.If safe investment returns increase after a rise in interest rates,the relative attractiveness of insurance retirement products for policyholders might decrease.Steady and slow changes in interest rates may be easier for insurers,and the distressed companies they invest in,to handle.For example,insurers would have enough time to launch products that are competitive relative to other safe investments in the new interest rate environment.The leveraged companies that insurers invest in would be better able to adjust their borrowing over time,reducing the negative effects on their capital and on insurers investment portfolios.Policyholders facing higher risk from deteriorated insurance assets and lower-than-expected returns on insurance policies might withdraw their retirement balances.If enough policyholders withdraw,insurers will struggle to pay these balances.Policyholders anticipating liquidity problems might hurry to withdraw their funds before insurers assets are exhausted,triggering runs on insurers.Furthermore,these runs might force insurers to sell assets at a discount,further affecting their stock price and accelerating the runs.The US economy has not experienced rapid increases in interest rates in recent years,and those that did take place in the past occurred before insurance statutory data were available.This makes it difficult to measure the relative magnitude of these countervailing forces.However,the model shows that,in a context of slow-moving interest rates,an increase in yields would either be neutral or positive for insurers.In short,an orderly and slow move out of low interest rates would likely increase insurers stock prices.However,a sudden rise in yields might cause harm if the incentives to withdraw early trigger insurance runs.Bermuda Monetary AuthorityThe Bermuda Monetary Authority(BMA)has developed an in-house model for interest rate stresses.It relies on a statistical technique called Figure 3.2d:Life insurers interest rate sensitivity(20142019)Source:Hartley et al.2828principal component analysis.Using this method,the time series of risk-free interest rates of different maturities and the yields of corporate bonds from different rating classes70 are broken down(decomposed)into factors.71 These factors have smaller dimensions than that of the time series72 in question and are able to perfectly predict the time series that have been decomposed.The principal component analysis method is designed to provide 100curate in-sample forecasts that reproduce the decomposed time series.At the same time,these factors can be treated as random variables and projected forward.Once these factors are projected,they can be recomposed to produce forecasts about the time series from which they were created.In the BMA model,the factors are fitted with a vector autoregression model,which accounts for correlation between factors.Once the vector autoregression model has been estimated,it is simulated forward for 12 months.At the end of this period,the factors are recomposed back into risk-free interest rates and corporate bond yields for different rating classes.Because risk-free rates are given in discrete maturities,a set of techniques is used to create smooth curves for all maturities.Initially,for maturities of 20 years,for example,new data points are added(interpolation)between the 15th and 30th year to close an important gap in the US yield curve.73 The end product is a collection of risk-free curves and corporate bond yield forecasts for rating classes from AAA to non-investment grade.Figure 3.2e shows 100 sample US risk-free curves,produced by the BMA model.The model produces multiple curves,from regular increasing curves to inverted ones.The relative frequency of each curve is based on historical data and,as can be seen in Figure 3.2f,most curves increase with an inversion at shorter maturities.Based on the 10,000 curves produced,the mean curve,the median curve,the 10th percentile curve and the 95th percentile curve can be estimated.These are the four main scenario curves.In addition,the same mean,median,10th percentile and 95th percentile yields for corporate bonds are produced for different rating classes.Since there isnt a curve with different maturities of corporate bond yields for each rating category,the assumption is that shifts in the yield curves of corporate bonds are parallel for all maturities.The mean risk-free curve is produced by averaging 10,000 projected risk-free rates for every maturity.The median curve is produced by taking the median of 10,000 projected risk-free rates for every maturity.Similarly,the 10th and 95th percentile curves are respectively the 10th Figure 3.2e:Samples of risk-free curves(%)Source:BMA29Figure 3.2f:Projected risk-free curves(%)75Source:BMAFigure 3.2g:Projected sovereign bond portfolio returns(%)Source:BMAand the 95th percentile of the projected 10,000 rates for each maturity.Figure 3.2f gives an overview of these curves.Based on the scenarios of risk-free curves in Figure 3.2f,the asset portfolios of Bermudas(re)insurers are stressed.These scenarios are applied to large commercial property and casualty(re)insurers(class 3B/4 insurers).In addition to the stress of changing yields,a stress scenario of equity portfolios and credit migrations,including defaults and rating upgrades and downgrades,is also considered.For the purposes of this section,only stress scenarios from risk-free interest rate changes are covered.In Figure 3.2g,the results of the stresses on the portfolio of sovereign assets held by Bermudan(re)insurers are shown.Figure 3.2g demonstrates that the average and median curve have very little effect on the valuation of the sovereign portfolio of assets held by all(re)insurers.This is due to the fact that the average projected yield curve does not change significantly from the base yield curve used at the beginning of the simulation.74 For the 10th and the 95th percentile curves,significant valuation changes are observed.The 10th percentile curve is below the base yield curve,so bonds would be valued higher as a result.The 95th percentile curve is higher than the base curve;therefore,bonds decrease in value after revaluation.For the 95th percentile curve,we can observe that,except for a few outliers,most portfolio decreasesstand at about 5%.As shown in Figure 3.2f,these portfolio changes correspond to a 30Figure 3.2h:Projected corporate bond portfolio returns(%)Source:BMA31150 basis points shift upwards for the risk-free yield curve.This is an extreme scenario given that the 90th percentile yearly increase in the federal funds rate has been around 127 basis points since 2000.76These results are driven by the short durations of assets held by(re)insurers in Bermuda.These firms,which are mostly active in the property and casualty space,have liabilities of short duration and therefore require short duration assets to match.In addition to sovereign bonds,(re)insurers are also active buyers of corporate bonds.As was done in the previous exercise,the shocks for corporate bonds different rating classes are applied,assuming constant credit spreads.77 The results can be found in Figure 3.2h.As with the sovereign bond portfolio,the mean and median curve have very little revaluation effects on the corporate bond portfolios of (re)insurers for all rating classes.The 95th percentile curve produces losses between 2%and 5%on average.However,there are outliers because some companies have long duration corporate bonds to match liabilities in the casualty business,and some may be conducting life business as well.Overall,the revaluation effects are different between rating classes,as specific (re)insurers prefer certain durations for specific rating classes.From the above example,AA and BBB-rated securities are preferred by a few longer-term (re)insurers.The impact of the portfolios revaluation on the companies solvency was estimated using a rough measure of the probability that assets would be lower in value than liabilities.For all companies that were stressed,this probability was estimated to be zero.Although it is a rather crude measure,the results of the exercise show that,on average,the revaluation effects are manageable after a sudden increase in interest rates in the Bermudan property and casualty sector,although some outliers may need extra supervisory attention.Although at higher interest rates there are revaluation effects and fixed-income portfolios lose value,as the older bonds mature and (re)insurers purchase new ones with higher coupon rates,their investment income would improve and the revaluation effect would be a temporary strain that does not significantly affect the longer-term survival of the firm.Of course,this is more relevant for property and casualty (re)insurers that do not have to lock in bonds for long durations.3.2.3 ConclusionsInterest rate risk affects insurers in different ways.Changing interest rates may,depending on the valuation regime applied,impact both asset and liability valuations of insurers,which in turn influences the value of the company.Interest rates can also determine the behaviour of policyholders in terms of lapsed life insurance contracts.As insurers invest in assets that are sensitive to interest rates,their profitability is determined by the way in which interest rates move.For insurers selling life insurance products with a guaranteed savings component,interest rates are considered one of the main drivers of the viability of their business model.The current macroeconomic environment indicates the likelihood of a continued low-yield environment in many developed economies.As a result,insurance supervisors have tried to measure the negative impact of this environment on the profitability and/or solvency of the insurers active in their markets.Many of these studies have pointed to the vulnerability of life insurers should this low-yield environment continue.Although economists may disagree on the length of the continuation of the low interest rate environment,many insurance supervisors have found it worthwhile to explore the consequences of a reversal of the low-yield environment.It is generally accepted that a gradual rise in risk-free interest rates will positively affect the profitability and solvency of life insurers,but sudden increases may trigger several adverse consequences.Increasing spreads as a result of a possible revaluation of risk premia and/or a direct increase in observed defaults may,depending on the valuation regime,directly negatively affect the solvency of insurers.Increasing yields may also trigger lapses in contracts if policyholders seek investment alternatives with a better return.A GRADUAL RISE INRISK-FREE INTEREST RATES WILL POSITIVELY AFFECT THE PROFITABILITY AND SOLVENCY OF LIFE INSURERS,BUT SUDDEN INCREASES MAY TRIGGER SEVERAL ADVERSECONSEQUENCES.32This disadvantages insurers that are“stuck”with recently bought low-yield assets.These analyses and studies have helped the supervisory community understand the different effects rising interest rates may have on insurers and be wary of suddenly increasing interest rates,even in a macroeconomic environment characterised by low yields across all maturities.3.3 CURRENT CHALLENGES IN THE LIFE INSURANCE INDUSTRYLow interest rates have put significant pressure on life insurers by reducing investment yields,sometimes below guaranteed rates.This has been a common feature internationally,with long-term yields in many developed economies declining fairly consistently since the mid-1980s,although the effects on local insurers differ.Because of the perceived effect on insurers solvency and profitability,it is becoming increasingly accepted that the life insurance industry itself is changing.Insurers have been pursuing different strategies to adapt to the changing macroeconomic environment.In some cases,strategies are straightforward,such as lowering the interest rate guarantees on life insurance portfolios or changing the asset allocation.Other,more radical,strategies affect insurers entire business models,such as decisions by some mixed insurers to no longer sell certain life insurance products or to put parts of the business in run-off.At the same time,other players,such as private equity firms and asset managers,have taken over life insurance portfolios.This special topic looks at data across several jurisdictions to examine two trends observed in the life insurance industry.In Europe,a growing share of the market is being captured by unit-linked insurance,but there is mixed evidence that the shift is driven by interest rates.In the US,however,the more notable change has not been a shift to a lower volume of guaranteed products,but rather an increased number of private equity firms that have purchased insurers to invest in illiquid or exotic assets.3.3.1 Unit-linked Insurance ProductsUnit-linked insurance products(ULIPs)are hybrids,consisting of a traditional life insurance policy and a capital appreciation component in the form of an investment plan.In several jurisdictions,such as the US,they may be called annuities.The policyholder still pays a premium,but this amount is split to cover life insurance and investments in equity and debt instruments to earn market-linked returns.The investment vehicle portion is similar to a mutual fund,where all premiums received are pooled together and invested.The policyholder holds fund units and the net asset value is regularly reported.The market risk of the ULIP is solely borne by the policyholder,although some products offer guarantees or minimum rates of return.Figure 3.3a:10-year government bond yields from selected jurisdictions(19852017)Sources:Thomson Reuters(DE,FR,IT,JP),OECD(UK),Federal Reserve Board(US),authors calculations33In the US,these products are referred to as separate accounts and assets are typically invested in mutual funds.However,not all annuities are linked to separate accounts.ULIPs,sold mainly by insurers,have several distinct features.Policy premiums benefit from several charge deductions,which can help companies manage their tax expenses and costs.The ULIP market has developed to offset decreasing interest rates and limit the pressure on life insurers to match guaranteed payout rates.This has also affected the insurance-investment proportion of ULIPs,with the latter increasing its relative share over time.ULIPs can also be split into contracts with and without guarantees.A product with investment guarantees establishes a minimum limit on the unit value held or the contract value.These may take the form of a capital guarantee,a minimum return guarantee or guaranteed payouts.On the other hand,ULIPs without guarantees have their value determined solely based on the performance of the underlying assets.As the ULIP market has grown,assets under management linked to the investment portionof the premiums are now mainly directly managed by asset managers.The EIOPA has found that less than 3%of ULIP assets are directly managed by insurance undertakings,while in-house asset managers(within the same group as insurers)manage 69%of these assets and external asset managers manage 28%.78 This allows the insurer to keep making decisions regarding the insurance contract,while investment decision-making is deferred to the asset manager.The relative share of unit-linked premiums presented in Figure 3.3b shows an increase between 2015 and 2016 of 4%,which is a 6.4%increase in nominal terms.With markets now operating in a low-for-long interest rate environment(see Chapter 1),insurers are shifting towards ULIPs in response to the economic pressure they are under.To increase their profits through higher income inflows,private equity companies are targeting life insurers for mergers and acquisitions,particularly in the US.3.3.2 Jurisdictional DevelopmentsIn the UK,since 1985,unit-linked business has risen from below 37%of premiums written toa peak of nearly 82%.There has been a steep decline in premiums for non-linked business,both with and without profit participation.In the UK,the decline in the share of premiums was gradual for non-profit business(generally immediate annuities)in the 1990s,largely following the path of long-term interest rates.After 2000,however,the share of premiums was volatile but largely flat.After 2016,bulk purchase annuities,which tend to have large single premium payments,began to grow in popularity,which accounts for some of the volatility.Figure 3.3b:European Economic Area life premiums by type of contract(2015 LHS and 2016 RHS)Source:Insurance EuropeUnit-linked,22%Unit-linked,26%Non unit-linked,78%Non unit-linked,744The trend in the UK for with-profits business has moved in the opposite direction.Premiums for with-profits products grew over the 1980s and 1990s,although market share was broadly flat.The widely publicised failure of Equitable Life in 2000,combined with widespread miss-selling of mortgage endowments in the 1990s,largely discredited with-profits products in the UK.In 2003 alone,new business premiums declined by nearly 56%and fell by another 45%by 2011.In Germany,the share of unit-linked business has grown in 18 years,from representing less than 7%of premiums written to just under 19%,coinciding with premium growth of nearly 300%.While the share of premiums for ULIPs has grown quickly over the last 18 years,as shown below,it still represents a fairly small portion of the German life insurance market.Figure 3.3c:UK non-linked,non-profit,with-profit,and unit-and index-linked premiums share(19852018)Source:Bank of EnglandFigure 3.3d:UK non-profit gross written premiums(19852018)Sources:Bank of England,OECD,79 authors calculations35Italy is an outlier in that,rather than a steady upward trend in unit-linked business,there was a major contraction in the volume of premiums written during the financial crisis,which cut premiums for unit-linked business by nearly two thirds.Since the financial crisis,unit-linked premiums have grown to their previous size,but they still only represent a third of insurance business(by premium share)in Italy.In the largest European jurisdictions(the UK,Germany,France and Italy),gross written premiums for ULIPs are closely linked to the local stock index,with correlation coefficients exceeding 0.85 for the UK,0.9 for France and Italy,and 0.75 for Germany.Figure 3.3e:Germany non-linked,non-profit,with-profit,and unit-linked premiums share(20002018)Source:BaFinFigure 3.3e:Italy non-linked,non-profit,with-profit,and unit-linked premiums share(20042018)Source:IVASS36Figure 3.3g:UK unit-linked premiums share,FTSE 100(GBP million,19852018)Sources:Bank of England,Thomson Reuters,80 authors calculationsFigure 3.3h:France unit-linked premiums share,CAC 40 average(EUR million,20052017)Sources:ACPR,Thomson Reuters,81 authors calculations37Figure 3.3i:Germany unit-linked premiums,DAX 30 average(EUR million,20002018)Sources:BaFin,Thomson Reuters,82 authors calculationsFigure 3.3j:Italy unit-linked premiums,FTSE-MIB average(EUR million,20042018)Sources:IVASS,Thomson Reuters,83 authors calculations3838This relationship is understandable given that rising equity markets would make unit-linked products more attractive to policyholders.As equity markets have grown,interest rates have fallen.In general,this would reduce the guarantees that insurers could offer on non-linkedproducts,making those products less attractive.Other than France,the correlation with interest rates is quite strong in Europe,and it appears that both interest rates and equity markets are affecting premiums for unit-linked business.The US had a noticeable increase in annuity premiums in 2018,with direct written premiums up 12.4%and fixed annuities contributing the most growth.As seen in the UK,there is not much of a correlation between annuity direct written premiums and the S&P 500 in the US(see Figure 3.3k).The US has not experienced the consistent correlation observed in Germany,France and Italy.Premiums in 2016 and 2017 were noticeably lower than 2015 levels.The US Department of Labors proposed fiduciary rule may have accounted for the decrease in 2016 and 2017.Under the fiduciary rule,financial advisers who handle retirement accounts must act in the best interests of their clients and charge compensation considered to be“reasonable”.They must also disclose this compensation to their clients.The vast majority of annuities are sold on commission,which largely explains why many advisers have moved away from annuity sales due to the uncertainty around the rules on compensation.Figure 3.3k:US annuity direct written premiums vs S&P 500(USD billion,20092018)DWP=direct written premiumsSource:NAIC39Figure 3.3l:US separate account values vs S&P 500(USD billion,20092018)Source:NAICSeparate account values indicate ULIP activity in the US,but not all annuities are linked to separate accounts or are equivalent to unit-linked products.Although separate account asset values have grown steadily over the past 10 years,there was a 9cline in 2018.This is primarily due to the decline in equity markets,which most separate account assets are invested in,at the end of 2018.On 15 March 2018,the US Court of Appeals for the Fifth Circuit issued a decision vacating the Department of Labors fiduciary rule in its entirety.However,since the regulation of annuities by insurers is state-based,the states are updating their regulations to be consistent with the Department of Labors proposed standards.84 Increased certainty around annuity sales regulation contributed to sales growth in 2018 and projected growth in 2019.Insurers have been quick to launch new lines of fee-based annuities,which are designed to comply with the fiduciary rule.These annuities do not sell on commission but rather are included in an advisers fee-based accounts.The NAICs data support growth projections,showing a significant 9.5%increase in annuity direct written premiums in the second quarter of 2019(year over year).According to the Life Insurance Marketing and Research Association,this record growth will continue the associations midpoint forecast predicts a 5%increase in sales in 2019.Sales could jump more than 20%over the next five years to$280 billion.S&P has a more conservative forecast,expecting direct life,annuity,and accident and health premiums and considerations,including renewal business,to grow 3.1%in 2019 and3.7%in 2020.When considering consumer demand,another factor that may contribute to increased annuity sales is persistent low interest rates.As investment yields and spreads decline,insurers continue to look for avenues of growth and annuity sales are a viable solution.Demographics also play a role the NAIC continues to see many people from the“Baby Boom”generation(born between 1946 and 1964)moving into retirement.40Annuities offer retirees and near retirees the ability to create secure,guaranteed lifetime income from their investments,which makes them an in-demand retirement product.Increased annuity sales have put traditional asset managers under competitive pressure.Many investors see annuities as a win-win product guaranteed income or death benefit and an opportunity to invest in capital markets.This,combined with annuities being invested in separate mutual funds typically managed by asset managers,has led to some mergers and acquisitions in the insurance space.Historically,merger and acquisition activity in the life industry was anticipated to increase in tandem with interest rate increases,which made insurers more attractive investments.However,recently the number of merger and acquisition deals has Figure 3.3m:Annuity sales(USD billion,Q1 2018 Q1 2019)Source:LIMRA Secure Retirement InstituteFigure 3.3n:Life and health transactions;price-to-book-value multiples(20072018)Source:Deloittes 2019 Insurance M&A outlook41declined as rates have declined.That said,while there was a decrease in the number of deals,there was an increase in deal values in 2018,as shown in Figure 3.3n.Low interest rates have forced insurers to reassess their core 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