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Using non-traditional data for underwriting loans to thin-file borrowers: Evidence, tips and precautions
Journal of Risk Management in Financial Institutions,
1
(2),
165-180
(2008)
Abstract
Sustainable growth in underserved domestic markets has long been a challenge to lenders. Recent testing with non-traditional data in automated underwriting shows promise as a means to profitably extend credit to the ‘thin-file’ and ‘no-file’ populations without assuming undue risk. This area is in its infancy, and is fraught with risk and challenge. Despite the potential, lenders are advised to proceed with caution and should slowly test their way into this segment with the new methods. As this is a slow process, one of the key challenges is to get the needed commitment from the lending institutions. A prudent credit risk officer can harness the power of non-traditional data by taking a disciplined and methodical approach to testing and implementing. This paper demonstrates the value of non-traditional data as a powerful tool for consumer credit risk assessment while highlighting some of the potential risks and precautions that lenders need to think about before using these tools. Special emphasis is placed on paying attention to the capacity of these customers and creating a life cycle strategy for them that includes credit education. This paper presents some empirical test results, and outlines steps that should be taken by lenders to capture the full value of the data while mitigating risk.
Keywords: credit risk; non-financial payment reporting; thin-file; automated underwriting; alternative data; credit scoring
The full article is available to subscribers to the journal.
Author's Biography
Michael A. Turner is the president and founder of the Political & Economic Research Council (PERC). PERC is a nonprofit public policy research organisation focusing upon issues pertaining to consumer credit, community economic development and economic development. Dr Turner is an international credit reporting policy expert who has worked with industry and governments in more than 12 countries. He currently serves on the Advisory Committee for the Brookings Institution Urban Markets Initiative, and has just completed a two-year term on the US Department of Homeland Security’s Data Privacy and Integrity Advisory Committee. Dr Turner earned his PhD in political economy from Columbia University, and his BA in economics from Miami University.
Amita Agarwal is a director for Chase Credit Card Services, responsible for acquisition risk within the credit card portfolio. Her key responsibility is to maintain and manage all acquisition credit risk strategies across all the channels, products and partners. One of her goals is to continuously explore, test and bring in new opportunities in terms of new updated risk tools to make optimal acquisition risk decisions and create market expansions. Prior to Chase she was at GE Consumer Finance-America, as risk leader for their bankcard product, managing the life cycle risk for the product. Before that she worked for other credit issuers like Fleet Credit Card Services and Advanta. Dr Agarwal received her MA in mathematics in India and her PhD in mathematics/statistics from Syracuse University.
Citation
Turner, Michael A. and Agarwal, Amita (2008, March 1). Using non-traditional data for underwriting loans to thin-file borrowers: Evidence, tips and precautions. In the Journal of Risk Management in Financial Institutions, Volume 1, Issue 2. https://doi.org/10.69554/LCKE3812.
© Henry Stewart
Publications LLP
Publications LLP