Examining the Use of Alternative Data in Underwriting and Credit Scoring to Expand Access to Credit

17 Pages Posted: 14 Nov 2019

Date Written: July 24, 2019

Abstract

Over the last several years, a body of sophisticated algorithms commonly described as artificial intelligence (“AI”) and distributed ledger technologies have altered the financial market ecosystem, creating a new class of financial institutions – Fintech firms. Supplementing traditional credit underwriting data inputs and processes, fintech firms employ newer modeling techniques and consider a broader range of source data referred to descriptively (rather than normatively) as alternative data. These new inputs include information regarding consumers’ financial transactions, recurring payments history and a behavioral score based on social networking and digital-interface. Fintech firms include both the non-depository digital platforms that operate independently and platforms that partner with legacy banks to originate loans. Fintech firms servicing credit scoring and underwriting markets offer great promise but also present unique concerns.

Keywords: Fintech, Consumer Credit, Alternative Data, Credit Market Regulation, Cybersecurity, Blockchain

Suggested Citation

Johnson, Kristin N., Examining the Use of Alternative Data in Underwriting and Credit Scoring to Expand Access to Credit (July 24, 2019). Tulane Public Law Research Paper No. 19-7, Available at SSRN: https://ssrn.com/abstract=3481102 or http://dx.doi.org/10.2139/ssrn.3481102

Kristin N. Johnson (Contact Author)

Emory University - Law School ( email )

1301 Clifton Road, N.E.
Atlanta, GA USA 30306
United States

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