Determinants of default in p2p lending: the Mexican case

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Carlos Eduardo Canfield
صندلی اداری

Abstract

P2P lending is a new method of informal finance that uses the internet to directly connect borrowers with on-line communities. With a unique dataset provided by Prestadero, the largest on-line lending platform with national presence in Mexico, this research explores the effect of credit scores and other variables related to loan and borrower´s traits, in determining default behavior in P2P lending. Moreover, using a logistic regression model, it tested whether investors might benefit from screening loan applicants by gender after controlling for loan quality. The results showed that information provided by the platform is relevant for analyzing credit risk, yet not conclusive. In congruence with the literature, on a scale going from the safest to the riskiest, loan quality is positively associated with default behavior. Other determinants for increasing the odds of default are the payment-to-income ratio and refinancing on the same platform. On the contrary loan purpose and being a female applicant reduce such odds. No categorical evidence for differential default behavior was found for gender´s case-discrimination, under equal credit conditions. However it was found that controlling for loan quality, women have longer loan survival times than men. This is one of the first studies about debt crowdfunding in Latin America and Mexico. Implications for lenders, researchers and policy-makers are also discussed.

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Author Biography

Carlos Eduardo Canfield, Universidad Anahuac

Full time professor and researcher at Universidad Anahuac

Business and Economics Faculty

References

AGUILERA, A.; ESCABIAS, M.; VALDERRAMA, M. (2006) Using principal components for estimating logistic regression with high-dimensional multicollinear data. Computational Statistics & Data Analysis, v. 50, n. 8, p. 1905-1924.

AKERLOF, G. (1970) The Market for “Lemons”: Quality Uncertainty and the Market Mechanism. Quarterly Journal of Economics, n. 84, p. 488-500.

ALLEN, F.; SANTOMERO, A. (1997) The theory of financial intermediation. Journal of Banking & Finance, v. 21, n. 11, p. 1461-1485.

ARROW, K. (1973) The Theory of Discrimination. in Ashenfelter, O, & A. Rees (Eds.), Discrimination in Labor Markets, p. 3-33. Princeton University Press, Princeton, NJ,

BACHMANN, A.; BECKER, A.; BUERCKNER, D.; HILKER, M.; KOCK, F.; LEHMANN, M.; FUNK, B. (2011) Online peer-to-peer lending-a literature review. Journal of Internet Banking and Commerce, v. 16, n. 2, p. 1.

BENNARDO, A.; PAGANO, M. (2007) Multiple-bank lending, creditor rights and information sharing. University of Salerno Mimeo.

BERGER, S.; GLEISNER, F. (2009) Emergence of financial intermediaries in electronic markets: The case of online P2P lending. BuR-Business Research, v. 2, n. 1, p. 39-65.

BROWN, M.; JAPPELLI, T.; PAGANO, M. (2009) Information sharing and credit: Firm-level evidence from transition countries. Journal of Financial Intermediation, v. 18, n. 2, p. 151-172.

CAVALLUZZO, K.; CAVALLUZZO, L.; WOLKEN, J. (2002) Competition, Small Business Financing, and Discrimination: Evidence from a New Survey. Journal of Business, n. 75, p. 641-680.

CNBV. (2014) Normatividad CNBV. Retrieved July 20, 2016, from: http://www.cnbv.gob.mx/SECTORES-SUPERVISADOS/SOCIEDADES-DE-INVERSION/Paginas/Normatividad.aspx

DIAMOND, D. (1984) Financial intermediation and delegated monitoring. The Review of Economic Studies, v. 51, n. 3, p. 393-414.

DIAMOND, D; DYBVIG, P. (1983) Bank runs, deposit insurance, and liquidity. The journal of political economy, p. 401-419.

DIETRICH, A.; WERNLI, R. (2016) What Drives the Interest Rates in the P2P Consumer Lending Market? Empirical Evidence from Switzerland. Institute of Financial Services IFZ. Lucerne University of Applied Science working papers.

DORFLEITNER, G.; LEIDL, M.; PRIBERNY, C.; VON MOSCH, J. (2013) What determines microcredit interest rates? Applied Financial Economics. v. 23, n. 20, p. 1579-1597.

DUARTE, J.; SIEGEL, S.; YOUNG, L. (2012) Trust and Credit: The Role of Appearance in Peer-to-Peer Lending. Review of Financial Studies, n. 25, p. 2455-2484.

EMEKTER, R.; TU, Y.; JIRASAKULDECH, B.; LU, M. (2015) Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending. Applied Economics, v. 47, n. 1, p. 54-70.

FREEDMAN, S.; JIN, G. (2014) The information value of online social networks: Lessons from Peer-to-Peer lending (No. w19820). National Bureau of Economic Research.

GALLOWAY, I. (2009) Peer-to-peer lending and community development finance. Community Investments, v. 21, n. 3, p. 19-23.

GARCÍA, J.; GARCÍA, M.; VENEGAS, F. (2015) Administración del riesgo crediticio al menudeo en México: una mejora econométrica en la selección de variables y cambios en sus características. Contaduría y Administración.

GONZALEZ, L.; LOUREIRO, Y. (2014) When can a photo increase credit? The impact of lender and borrower profiles on online peer-to-peer loans. Journal of Behavioral and Experimental Finance, n. 2, p. 44-58.

HAND, D.; HENLEY. (1997) Statistical classification methods in consumer credit scoring: a review. Journal of the Royal Statistical Society: Series A (Statistics in Society), v. 160, n. 3, p. 523-541.

HERZENSTEIN, M.; ANDREWS, R.; DHOLAKIA, U.; LYANDRES, E. (2008) The democratization of personal consumer loans? Determinants of success in online peer-to-peer lending communities. Boston University School of Management Research Paper, v. 14, n. 6.

HOSMER, D.; LEMESHOW, S. (1989) Applied regression analysis. New York: John Wiley

HULME, M.; WRIGHT, C. (2006) Internet based social lending: Past, present and future. Social Futures Observatory, n. 115.

ITURBIDE, L.; CANFIELD, C. (2015) Una perspectiva académica sobre la participación en proyectos de financiamiento colectivo: las prácticas de Crowdfunding en México. Reporte Macroeconómico de México, v. 6, n. 9, p. 25.

JAPPELLI, T.; PAGANO, M. (2006) Role and effects of credit information sharing. In: BERTOLA, G.; DISNEY, R.; GRANT, C. (Eds.), Economics of Consumer Credit, p. 347-371. Cambridge: MIT Press, Cambridge.

KARLAN, D.; ZINMAN, J. (2009) Observing unobservables: Identifying information asymmetries with a consumer credit field experiment. Econometrica, v. 77, n. 6, p. 1993-2008.

KHWAJA, A.; IYER, R.; LUTTMER, E.; SHUE, K. (2009) Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending? Kennedy School of Government, Harvard University. HKS Faculty Research Working Paper Series RWP09-031.

LEE, E.; LEE, B. (2012) Herding behavior in online P2P lending: An empirical investigation. Electronic Commerce Research and Applications, v. 11, n. 5, p. 495-503.

LELAND, H.; PYLE. (1977) Informational Asymmetries, Financial Structure and Financial Intermediation. The Journal of Finance, n. 32, p. 371-387.

LEVINE, R.; LOAYZA, N.; BECK, T. (2000) Financial intermediation and growth: Causality and causes. Journal of monetary Economics, v. 46, n. 1, p. 31-77.

LIN, M.; PRABHALA, N.; VISWANATHAN, S. (2013) Judging borrowers by the company they keep: Friendship networks and information asymmetry in online peer-to-peer lending. Management Science, v. 59, n. 1, p. 17-35.

MARKIDES, C. (2006) Disruptive innovation: In need of better theory. Journal of product innovation management, v. 23, n. 1, p. 19-25.

MILLER, S. (2015) Information and default in consumer credit markets: Evidence from a natural experiment. Journal of Financial Intermediation, v. 24, n. 1, p. 45-70.

MORO, S.; CORTEZ, P.; RITA, P. (2015) Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, v. 42, n. 3, p. 1314-1324.

PAULY, M. (1974) Overinsurance and public provision of insurance: The roles of moral hazard and adverse selection. The Quarterly Journal of Economics, p. 44-62.

PENG, C.; LEE, K.; INGERSOLL, G. (2002) An introduction to logistic regression analysis and reporting. The Journal of educational research, v. 96, n. 1, p. 3-14.

PHELPS, E. (1972) The statistical theory of racism and sexism. The American Economic Review, v. 62, n. 4, p. 659-661

POPE, D.; SYDNOR. (2011) What’s in a Picture? Evidence of Discrimination from Prosper. com. Journal of Human Resources, v. 46, n. 1, p. 53-92.

RAVINA, E. (2012) LOVE & Loans. Effect of Beauty and Personal Characteristics in Credit Markets. Columbia Business School. The Working Paper, Finance and Economics. NY.

RUIZ-UGARTE, A. (2010) Lecciones de la crisis Subprime: ¿Es la titulización una opción para los mercados de préstamos P2P y de microfinanzas? BBVA Global Trends Unit BBVA Global.

SCHOLES, M.; BENSTON, G.; SMITH. (1976) A transactions cost approach to the theory of financial intermediation. The Journal of Finance, v. 31, n. 2, p. 215-231.

SCHWAB, S. (1986) Is Statistical Discrimination Efficient? The American Economic Review, v. 76, n. 1, p. 228-234.

SERRANO-CINCA; GUTIÉRREZ-NIETO, B.; LÓPEZ PALACIOS, L. (2015) Determinants of Default in P2P Lending. PLoS ONE: e0139427, v. 10, n. 10.

STIGLITZ, J.; WEISS, A. (1981) Credit rationing in markets with imperfect information. The American Economic Review, v. 71, n. 3, p. 393-410.

TOWNSEND, R. (1979) Optimal Contracts and Competitive Markets with Costly State Verification. J Econ Theory, n. 21, p. 265-293.

WAN, Q.; CHEN, D.; SHI, W. (2016) Online peer-to-peer lending decision making: Model development and testing. Social Behavior and Personality: an international journal, v. 44, n. 1, p. 117-130.

WEISS, G.; PELGER, K.; HORSCH, A. (2010) Mitigating Adverse Selection in P2P Lending–Empirical Evidence from Prosper. com. Ruhr-University Bochum, Department of Economics. Bochum, Germany: Available at SSRN 1650774.

YUM, H.; LEE, B.; CHAE, M. (2012) From the wisdom of crowds to my own judgment in microfinance through online peer-to-peer lending platforms. Electronic Commerce Research and Applications, v. 11, n. 5, p. 469-483.

ZENG, R. (2013) Legal Regulations in P2P Financing in the US and Europe. US-China Law Review, n. 10, p. 229.

ZHANG, J.; LIU, P. (2012) Rational herding in microloan markets. Management Science, v. 58, n. 5, p. 892-912.

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