Big Data and Artificial Intelligence in the Banking Industry

T. Robert Yu and Xuehu Song

Chapter 117 in Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning:(In 4 Volumes), 2020, pp 4025-4041 from World Scientific Publishing Co. Pte. Ltd.

Abstract: Big data and artificial intelligence (AI) assist businesses with decision-making. They help companies create new products and processes or improve existing ones. As the amount of data grows exponentially and data storage and computing power costs drop, AI is predicted to have great potentials for banks. This chapter discusses the implications of big data and AI for the banking industry. First, we provide background on big data and AI. Second, we identify areas in which banks can benefit from big data and AI, and evaluate their applications for the banking industry. Third, we discuss the implications of big data and AI for regulatory compliance and supervision. Last, we conclude with the limitations and challenges facing the use of big-data based AI.

Keywords: Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data (search for similar items in EconPapers)
JEL-codes: C01 C1 G32 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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