The impact of machine learning and big data on credit markets

39 Pages Posted: 22 Jul 2021

See all articles by Peter Eccles

Peter Eccles

Bank of England

Paul Grout

Bank of England

Paolo Siciliani

Bank of England

Anna (Ania) Zalewska

University of Bath - Centre for Governance, Regulation and Industrial Strategy; School of Management

Date Written: July 9, 2021

Abstract

There is evidence that machine learning (ML) can improve the screening of risky borrowers, but the empirical literature gives diverse answers as to the impact of ML on credit markets. We provide a model in which traditional banks compete with fintech (innovative) banks that screen borrowers using ML technology and show that the impact of the adoption of the ML technology on credit markets depends on the characteristics of the market (eg borrower mix, cost of innovation, the intensity of competition, precision of the innovative technology, etc.). We provide a series of scenarios. For example, we show that if implementing ML technology is relatively expensive and lower-risk borrowers are a significant proportion of all risky borrowers, then all risky borrowers will be worse off following the introduction of ML, even when the lower-risk borrowers can be separated perfectly from others. At the other extreme, we show that if costs of implementing ML are low and there are few lower-risk borrowers, then lower-risk borrowers gain from the introduction of ML, at the expense of higher-risk and safe borrowers. Implications for policy, including the potential for tension between micro and macroprudential policies, are explored.

Keywords: Adverse selection, banking, big data, capital requirements, credit markets, fintech, machine learning and prudential regulation

JEL Classification: G21, G28, G32, G28, 031, 033

Suggested Citation

Eccles, Peter and Grout, Paul and Siciliani, Paolo and Zalewska, Anna, The impact of machine learning and big data on credit markets (July 9, 2021). Bank of England Working Paper No. 930, Available at SSRN: https://ssrn.com/abstract=3890364 or http://dx.doi.org/10.2139/ssrn.3890364

Peter Eccles (Contact Author)

Bank of England ( email )

Threadneedle Street
London, EC2R 8AH
United Kingdom

Paul Grout

Bank of England ( email )

Threadneedle Street
London, EC2R 8AH
United Kingdom

Paolo Siciliani

Bank of England ( email )

Threadneedle Street
London, EC2R 8AH
United Kingdom

Anna Zalewska

University of Bath - Centre for Governance, Regulation and Industrial Strategy; School of Management ( email )

Claverton Down
Bath, BA2 7AY
United Kingdom
+44 0 1225 384354 (Phone)
+44 0 1226 384354 (Fax)

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