1、ADVANCED ANALYTICS IN BANKING Introduction 1 Current business challenges.2in banking industry How analytics manage these challenges.3 5 real world 10 xDS RPA use cases.4for analytics in banking10 xDS analytics practices.9 Conclusion.10About 10 xDS.11CONTENTSIntroductionFinancial institutions will be

2、 facing increasing challenges dealing with the changing compliance rules and scrutiny by public authorities,law agencies,statutory/regulatory bodies.Traditional and legacy tools are often cumbersome and time consuming to use for gathering and analyzing the data for business insights.Today,with sever

3、al advanced technology options available,significant number of organizations are investing money and efforts into unlocking their huge potential of data.The first step in the transformation pathway for building analytics capabilities begins with employing descriptive analytics techniques,which helps

4、 in reviewing the past performance of the organization.It further helps in understanding the hidden patterns that provides insights in terms of customer behavior,sales trends,product performance,risk patterns and others.Analytics offers key information needed to improve operational efficiencies and

5、boost profits,reduce information bottlenecks,greater customer insights and better decision making.In order to identify and act on risks in advance,advanced analytics techniques such as predictive modelling,machine learning,and forensic analytics are very effective.This also enables organizations to

6、have more powerful tools and technologies to predict sales trends,create what-if scenarios,identify and act on customer sentiment,segment customers for customized product promotions and so on.1Current challenges in Banking Industry Banking industry faces some really pressing problems such as:Difficu