FinTech Lending and Cashless Payments
August 31, 2021 Yao Zeng

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Paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3766250


Recap

On 31st August 2021, Professor Yao Zeng from Wharton Business School joined us in a Luohan Academy Webinar to discuss the rise of Fintech lending and the role of cashless payment technologies play in it.


Prof Yao Zeng began the talk with his observation on the difference in screening abilities of traditional banks and fintech lenders. Traditional banks produce credit information from both sides of the balance sheet, including loans and deposits. Borrowers signal their credit worthiness through two channels, the income they deposited into banks and stable loan repayments to banks. Then banks have inside information and soft information in relationship banking. However, for fintech lenders there is only one side that really generates information, because borrowers do not deposit their money into fintech lenders, which is a typical case in the United States, but not in China. As a result, Fintech lenders must collect information from alternative channels. In this paper, Prof. Zeng claims the additional channel is that fintech lenders collect outside or hard information through reliable payment process, as all the data and information is distilled into the transaction processes.


He presented a theoretical model that shows synergy between fintech lending and cashless payments, which is similar to Milgrom's (1981) "unraveling argument". In the model, there is a risk-neutral firm and a risk-averse financier who both operate in competitive markets. Firm is privately informed about its type and the financier has a prior belief of the firm's type. Firm can choose payment method, whether to apply for a loan, and then lender make a lending desicion, including the credit amount and interest rates.


In equilibrium, financing price can be decomposed into three components: the baseline price, an information-revealing effect, and a risk-reducing effect. Comparing to the benchmark case where a lender offers uninformed financing price, additional information from strategically choosing digital payment and accumulating transaction data leads to more accurate credit inference. The model implies several hypotheses, among which the most important is that a firm is more likely to be granted a loan and enjoy a lower interest rate in expectation. The intuition is that information-revealing effect on average is zero, but the risk-reducing effect is always positive, even for the lemon borrowers.


In the empirical part, they use the data provided from Indifi, one of the top three Indian Fintech lenders focusing on SME loans. The date includes loan-level data including loan amount, interest rate and default status, and application-level data like applicant characteristics. In the baseline regression, they explain the loan approval decision with the share of verifiable cashless payments, and find a significantly positive effects, which supports the first hypothesis. Several heterogeneity tests strengthen their prediction that only verifiable information matters for loan approval.


In order to address the endogeneity issue, they used borrowers' relationship with the chest bank as an instrument variable by taking advantage of the 2016 demonetization act in India. The first stage regression suggests that borrowers who open their bank account at the chest bank are more likely to use cash payments. In the second stage regression, Prof. Zeng explains the loan approval on the predicted values by the share of cashless payments, and found significantly positive coefficients, which supports the main argument.


During the webinar, participants including Prof Yiyan Yang from Utoronto, Prof Zhiguo He from Chicago Booth, Luohan academy economists Dr. Xijie Gao, Dr.Yingju Ma, and Dr. Qing Han, etc., all contributed by giving very insightful and helpful comments.


Dr. Yao Zeng is an Assistant Professor of Finance at Wharton School, University of Pennsylvania. Dr. Zeng works on the intersection of asset pricing and corporate finance with a focus on financial intermediation. His research has been published on Journal of Finance, Journal of Financial Economics,Review of Financial Studies. Dr. Zeng received Ph.D. in Economics from Harvard University in 2016 and was on the finance faculty of the University of Washington Foster School of Business from 2016 to 2020.

Luohan Webinar is a regular event of the Academy purported to provide a platform for world-class scholars to present their frontier research and exchange views on digital technology and digital economy, among other related themes. We believe that truth can only be uncovered through open and critical discussions.




If you would like to give a presentation in a future webinar, contact our Senior Economist Dr. Wen Chen (wen.chen@luohanacademy.com). For other inquiries, please contact: events@luohanacademy.com.


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