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1、Evolution of Artificial Intelligence in Finance IndustryPresentation by Nishitha KAI Scope in Finance Industry Repetitive and refundant processes Innumerous transaction cycles Abundant Paperwork Critical customer interactions Large historical Data Volumes Fungible products with extensive use of tech
2、nologyHistorical Evolution TimelineDecision support systems helped financial professionals analyze data and make informed decisions,while expert systems provided rule-based reasoning for tasks such as credit scoring and risk assessment.Neural networks,a form of machine learning,gained popularity for
3、 their ability to analyze complex data and identify patterns.Financial institutions started using neural networks for predictive modeling,including forecasting market trends,predicting stock prices,and assessing credit risk.The rise of algorithmic trading revolutionized financial markets,with AI-pow
4、ered algorithms executing trades at high speeds based on predefined rules and market conditions.AI-driven trading strategies enabled institutions to capitalize on opportunities and manage risks more effectively,contributing to the growth of automated trading systems.The emergence of robo-advisors de
5、mocratized investment management by offering automated,algorithm-driven portfolio management services retail investors.Robo-advisors leverage AI algorithms to create personalized investment strategies,rebalance portfolios,and provide financial advice at a fraction of the cost of traditional wealth m
6、anagement services.1980s2000s1990s2010sThe finance sector has a rich and extensive history with AI dating back tthe early 1980s.In 1982,Apex created PlanPower,an AI program for tax and financial advice offered tclients with incomes of over$75,000.In 1987,Chase Lincoln First Bank(now part of JP Morga