AI-Based Consumer Credit Underwriting: The Role of A National Credit Database

Artificial Intelligence in Finance: Challenges, Opportunities and Regulatory Developments (Nydia Remolina and Aurelio Gurrea-Martinez, eds., forthcoming 2023, Edward Elgar Publishing Ltd.)

22 Pages Posted: 21 Sep 2022

See all articles by Maayan Perel (Filmar)

Maayan Perel (Filmar)

Netanya Academic College

Ruth Plato-Shinar

Netanya Academic College, Israel

Date Written: August 17, 2022

Abstract

Consumer credit providers increasingly rely on algorithmic credit underwriting, deploying Artificial Intelligence (AI) tools such as Machine Learning (ML), to predict consumers' credit risk.

Lenders' turn to algorithmic underwriting was initially facilitated by credit data sharing regimes, originally established in the United States and which have now become prevalent in many other jurisdictions as well. A key player in these credit data sharing regimes is the credit bureau - a commercial entity that collects, processes and sells credit data and various services based on this data. ‘Credit scoring’ stands at the core of these services. Under this "commercial model" of data sharing, private credit bureaus operate independent credit databases, develop scoring models and sell credit scores to lenders who weigh them in their underwriting processes.

In contrast, under a "hybrid model" of credit data sharing regime, all credit data is centrally held on a national, supervised and strictly secured database, to which authorized credit bureaus enjoy exclusive access. The credit bureaus develop scoring models under strict regulatory supervision of the central bank, and sell these scores to lenders.

This chapter explores how the implementation of a hybrid data sharing model may impact the benefits and risks of AI-based consumer underwriting. The Israeli regime, which has recently implemented a national database, serves as a case study.

Keywords: Artificial Intelligence, AI, Machine Learning, ML, black box, privacy, discrimination, consumer credit, credit underwriting, credit scoring. credit data, banking, non-bank lenders

JEL Classification: K12, K23, E51, E58

Suggested Citation

Perel (Filmar), Maayan and Plato-Shinar, Ruth, AI-Based Consumer Credit Underwriting: The Role of A National Credit Database (August 17, 2022). Artificial Intelligence in Finance: Challenges, Opportunities and Regulatory Developments (Nydia Remolina and Aurelio Gurrea-Martinez, eds., forthcoming 2023, Edward Elgar Publishing Ltd.), Available at SSRN: https://ssrn.com/abstract=4192295 or http://dx.doi.org/10.2139/ssrn.4192295

Maayan Perel (Filmar) (Contact Author)

Netanya Academic College ( email )

1 Unisversity Street
Netanya
Netanya, 31905
Israel

Ruth Plato-Shinar

Netanya Academic College, Israel ( email )

1 University St
Netanya, 4223587
Israel

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