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Do FinTech Mortgage Lenders Fill the Credit Gap? Evidence from Natural Disasters

Published online by Cambridge University Press:  18 October 2022

Linda Allen ,
Yu Shan  and
Yao Shen
Linda Allen*
Affiliation:
Baruch College Zicklin School of Business
Yu Shan
Affiliation:
Syracuse University Whitman School of Management yshan03@syr.edu
Yao Shen
Affiliation:
Baruch College Zicklin School of Business yao.shen@baruch.cuny.edu
*
linda.allen@baruch.cuny.edu (corresponding author)
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Abstract

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After exogenous demand shocks caused by natural disasters, FinTech lenders are more responsive to increased demand for reconstruction mortgages than traditional banks and non-FinTech shadow banks. Both FinTech and traditional banks increase credit supply, but FinTech supply is more elastic without increases in risk-adjusted interest rates or delinquency rates. Comparing lending supply channels, banks respond to regulatory incentives to lend to damaged areas, whereas FinTech lenders supply more credit when traditional banks rely more on balance sheet financing and physical branch networks. Compared to traditional banks, FinTech lenders increase supply elasticity more aggressively in response to local competitive pressure.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 58 , Issue 8 , December 2023 , pp. 3342 - 3383
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

The article was previously circulated under the title “Do FinTech Lenders Fill the Credit Gap? Evidence from Local Mortgage Demand Shocks.” We thank an anonymous referee, Amber Anand, Tetyana Balyuk, Nilanjan Basu, Sandra Betton, Ayan Bhattacharya, Youngmin Choi, Jens Christensen, Gonul Colak, Erasmo Giambona, Jarrad Harford (the editor), Sonali Hazarika, Alan Hochstein, Armen Hovakimian, Michael King, Peter Koveos, John Krainer, Lawrence Kryzanowski, Evren Ors, Lin Peng, Matthias Petras, Toan Phan, Wenlan Qian, Rahul Ravi, Zenu Sharma, Ravi Shukla, Jun Wang, Yajun Wang, David Weinbaum, An Yan, Erkan Yönder, Jinyuan Zhang, and Dexin Zhou for their insightful and constructive comments. We also thank the conference and seminar participants at the 2021 China International Conference in Finance, 2021 International Banking, Economics and Finance Association Summer Meeting, 2021 China International Risk Forum, 2019 Northern Finance Association Conference, 2019 Financial Management Association Annual Meeting, 2019 Financial Management Association European Conference, 2019 Eastern Economic Association Annual Meeting, 2019 Fordham Annual Global PhD Colloquium, Baruch College, Syracuse University, Florida State University, and Concordia University. All remaining errors are our responsibility. Linda Allen acknowledges summer support from the Bert Wasserman fund.

References

Acharya, V. V.; Berger, A. N.; and Roman, R. A.. “Lending Implications of US Bank Stress Tests: Costs or Benefits?” Journal of Financial Intermediation, 34 (2018), 58–90.CrossRefGoogle Scholar
Agarwal, S.; Alok, S.; Ghosh, P.; and Gupta, S.. “Financial Inclusion and Alternate Credit Scoring for the Millennials: Role of Big Data and Machine Learning in Fintech.” Working Paper, available at https://www.stern.nyu.edu/sites/default/files/assets/documents/White%20Papers_0.pdf (2021).Google Scholar
Balyuk, T.; Berger, A. N.; and Hackney, J.. “What is Fueling FinTech Lending? The Role of Banking Market Structure.” Working Paper, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3633907 (2020).CrossRefGoogle Scholar
Bartik, A. W.; Bertrand, M.; Cullen, Z.; Glaeser, E. L.; Luca, M.; and Stanton, C.. “The Impact of COVID-19 on Small Business Outcomes and Expectations.” Proceedings of the National Academy of Sciences, 117 (2020), 17656–17666.CrossRefGoogle ScholarPubMed
Bedayo, M.; Jiménez, G.; Peydró, J.-L.; and Sánchez, R. V.. “Screening and Loan Origination Time: Lending Standards, Loan Defaults and Bank Failures.” Working Paper, Banco de Espana (2020).Google Scholar
Begley, T. A., and Srinivasan, K.. “Small Bank Lending in the Era of Fintech and Shadow Banking: A Sideshow?” Working Paper, available at https://pdfs.semanticscholar.org/ad26/c6cabf87210192a201d17b8eca6323536702.pdf (2021).Google Scholar
Berg, T.; Burg, V.; Gombović, A.; and Puri, M.. “On the Rise of Fintechs: Credit Scoring Using Digital Footprints.” Review of Financial Studies, 33 (2020), 2845–2897.CrossRefGoogle Scholar
Berger, A. N.; Bouwman, C. H.; Norden, L.; Roman, R. A.; Udell, G. F.; and Wang, T.. “Piercing Through Opacity: Relationships and Credit Card Lending to Consumers and Small Businesses During Normal Times and the COVID-19 Crisis.” Working Paper, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3829240 (2022).CrossRefGoogle Scholar
Berger, A. N.; Klapper, L. F.; and Udell, G. F.. “The Ability of Banks to Lend to Informationally Opaque Small Businesses.” Journal of Banking & Finance, 25 (2001), 2127–2167.Google Scholar
Bolton, P.; Freixas, X.; Gambacorta, L.; and Mistrulli, P. E.. “Relationship and Transaction Lending in a Crisis.” Review of Financial Studies, 29 (2016), 2643–2676.Google Scholar
Boot, A. W., and Thakor, A. V.. “Can Relationship Banking Survive Competition?” Journal of Finance, 55 (2000), 679–713.CrossRefGoogle Scholar
Buchak, G.; Matvos, G.; Piskorski, T.; and Seru, A.. “Fintech, Regulatory Arbitrage, and the Rise of Shadow Banks.” Journal of Financial Economics, 130 (2018a), 453–483.CrossRefGoogle Scholar
Buchak, G.; Matvos, G.; Piskorski, T.; and Seru, A.. “Beyond the Balance Sheet Model of Banking: Implications for Bank Regulation and Monetary Policy.” NBER Working Paper No. 25149 (2018b).Google Scholar
Calem, P.; Correa, R.; and Lee, S. J.. “Prudential Policies and Their Impact on Credit in the United States.” Journal of Financial Intermediation, 42 (2020), 100826.CrossRefGoogle Scholar
Chen, B. S.; Hanson, S. G.; and Stein, J. C.. “The Decline of Big-Bank Lending to Small Business: Dynamic Impacts on Local Credit and Labor Markets.” NBER Working Paper No. 23843 (2017).CrossRefGoogle Scholar
Cortes, K. “Rebuilding after Disaster Strikes: How Local Lenders Aid in the Recovery.” Federal Reserve Board of Cleveland Working Paper No.14-28 (2014).CrossRefGoogle Scholar
Cortés, K. R.; Demyanyk, Y.; Li, L.; Loutskina, E.; and Strahan, P. E.. “Stress Tests and Small Business Lending.” Journal of Financial Economics, 136 (2020), 260–279.CrossRefGoogle Scholar
Cortés, K. R., and Strahan, P. E.. “Tracing Out Capital Flows: How Financially Integrated Banks Respond to Natural Disasters.” Journal of Financial Economics, 125 (2017), 182–199.CrossRefGoogle Scholar
Dahl, D.; Evanoff, D. D.; and Spivey, M. F.. “The Community Reinvestment Act and Targeted Mortgage Lending.” Journal of Money, Credit and Banking, 42 (2010), 1351–1372.CrossRefGoogle Scholar
De Roure, C.; Pelizzon, L.; and Thakor, A.. “P2P Lenders Versus Banks: Cream Skimming or Bottom Fishing?” Review of Corporate Finance Studies, 11 (2022), 213–262.CrossRefGoogle Scholar
DeYoung, R.; Hunter, W. C.; and Udell, G. F.. “The Past, Present, and Probable Future for Community Banks.” Journal of Financial Services Research, 25 (2004), 85–133.Google Scholar
Dia, E. “How do Banks Respond to Shocks? A Dynamic Model of Deposit-taking Institutions.” Journal of Banking & Finance, 37 (2013), 3623–3638.CrossRefGoogle Scholar
Dlugosz, J.; Gam, Y. K.; Gopalan, R.; and Skrastins, J.. “Decision-Making Delegation in Banks.” Working Paper, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3155683 (2022).Google Scholar
Erel, I., and Liebersohn, J.. “Does FinTech Substitute for Banks? Evidence from the Paycheck Protection Program.” NBER Working Paper No. 27659 (2020).CrossRefGoogle Scholar
Fuster, A.; Goldsmith-Pinkham, P.; Ramadorai, T.; and Walther, A.. “Predictably Unequal? The Effects of Machine Learning on Credit Markets.” Journal of Finance, 77 (2022), 5–47.CrossRefGoogle Scholar
Fuster, A.; Plosser, M.; Schnabl, P.; and Vickery, J.. “The Role of Technology in Mortgage Lending.” Review of Financial Studies, 32 (2019), 1854–1899.Google Scholar
Gaudóncio, J.; Mazany, A.; and Schwarz, C.. “The Impact of Lending Standards on Default Rates of Residential Real Estate Loans.” ECB Occasional Paper No. 220 (2019).Google Scholar
Gopal, M., and Schnabl, P.. “The Rise of Finance Companies and FinTech Lenders in Small Business Lending.” Review of Financial Studies, 35 (2022), 4859–4901.Google Scholar
Jagtiani, J.; Lambie-Hanson, L.; and Lambie-Hanson, T.. “Fintech Lending and Mortgage Credit Access.” Journal of FinTech, 1 (2021), 2050004.Google Scholar
Jagtiani, J., and Lemieux, C.. “The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the LendingClub Consumer Platform.” Financial Management, 48 (2019), 1009–1029.CrossRefGoogle Scholar
Jiang, X. “Financing Competitors: Shadow Banks’ Funding and Mortgage Market Competition.” Working Paper, University of Southern California (2020).Google Scholar
Li, L.; Strahan, P.; and Zhang, S.. “Banks as Lenders of First Resort: Evidence from the COVID-19 Crisis.” Review of Corporate Finance Studies, 9 (2020), 472–500.Google Scholar
Sheldon, T. L., and Zhan, C.. “The Impact of Natural Disasters on US Home Ownership.” Journal of the Association of Environmental and Resource Economists, 6 (2019), 1169–1203.CrossRefGoogle Scholar
Tang, H. “Peer-to-Peer Lenders Versus Banks: Substitutes or Complements?” Review of Financial Studies, 32 (2019), 1900–1938.CrossRefGoogle Scholar
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