Abstract
Financial services institutions are adopting artificial intelligence and machine learning-based solutions for accessing credit quality, market surveillance, fraud detection, and many more areas. It enables institutions to make better decisions, better compliance management, better customer interaction, and conduct surveillance and stress testing. Investors use artificial intelligence for developing portfolios by stock selection and asset allocation optimization for higher expected returns. We have analyzed the use of artificial intelligence by financial service institutions and its impact on service areas. We have reviewed existing and legacy methods used by financial institutions for various aspects of financial decisions such as security technical analysis, portfolio management, etc. Applications of artificial intelligence and machine learning have changed the overall approach in financial analysis and decision-making domain. This paper emphasizes on use of artificial neural networks for predicting time-varying expected returns of financial time series and to optimize portfolio management.
Index Terms: Artificial Neural Networks, Portfolio Optimization, Securities Analysis, Artificial Intelligence.
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