AFA2019会议论文（38）：FinTech Applications in Credit and Asset Markets

AFA2019会议论文（38）：FinTech Applications in Credit and Asset Markets

金融经济学 3天前

1. On the Rise of FinTechs – Credit Scoring using Digital Footprints

Tobias Berg, Frankfurt School of Finance & Management

Valentin Burg, Humboldt University Berlin

Ana Gombović, Frankfurt School of Finance & Management

Manju Puri, Duke University, FDIC, and NBER

Abstract

We analyze the information content of the digital footprint – a trail of information that people leave online simply by accessing or registering on a website – for predicting consumer default. Using a unique dataset of more than 250,000 observations, we show that even simple, easily accessible variables from the digital footprint can equal or exceed the information content of credit bureau (FICO) scores. The digital footprint complements rather than substitutes for credit bureau information and its discriminatory power for unscorable customers is even better than that for scorable customers. Our results have potentially wide implications for financial intermediaries’ business models going forward, for access to credit for the unbanked, and for consumer behavior in the digital sphere.

原文链接：

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=119

2. Fintech and Firm Selection: Evidence from E-commerce Platform Lending

Yi Huang, Graduate Institute of International and Development Studies

Ye Li, Ohio State University

Hongzhe Shan, Swiss Finance Institute

Abstract

As transaction and data hubs, e-commerce platforms are uniquely positioned to extend credit to users and have become leading players in FinTech. This paper provides the first evidence on how platform credit shapes the e-commerce market structure. Using data from Alibaba, we estimate the effects of platform credit on the allocation of customer attention, and consequently, the sales distribution of e-commerce merchants. We explore regression discontinuity and difference in difference settings for causal inference. We find that platform credit amplifies the selection of merchants by customers, and thereby, can contribute to platform prosperity especially through the cross-side externality.

原文链接：

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=2091

3. Does Crowdsourced Research Discipline Sell-Side Analysts?

Russell Jame, University of Kentucky

Stanimir Markov, Southern Methodist University

Michael Wolfe, Virginia Tech

Abstract

We examine whether increased competition stemming from an innovation in financial technology disciplines sell-side analysts. We find that firms added to Estimize, an open platform that crowdsources short-term earnings forecasts, experience reductions in short-term forecast bias relative to matched control firms. The reduction is greater when existing sell-side competition is lower, earnings uncertainty is higher, and Estimize coverage is less biased and more accurate. We also document an increase in short-term forecast accuracy and representativeness. We find no change in bias for longer-horizon forecasts or investment recommendations, suggesting competition from Estimize rather than broad economic forces drives our results.

原文链接：

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=1150

4. Winners and Losers of Marketplace Lending: Evidence from Borrower Credit Dynamics

Sudheer Chava,Georgia Institute of Technology

Nikhil Paradkar, Georgia Institute of Technology

Abstract

Does marketplace lending (MPL) benefit all its borrowers? Using comprehensive credit bureau data and MPL borrowers matched to non-MPL borrowers in the same ZIP code (or ZIP+4) with identical credit dynamics, we analyze credit profile evolution of borrowers on a major MPL platform, both prior to, and following, the loan origination. Consistent with the stated purpose for the loan, borrowers consolidate expensive credit card debt, leading to lower credit utilization ratios and higher credit scores in the two quarters after loan origination. But, during the same time period, they also receive additional credit from their existing bank relationships. Subsequently, MPL borrowers consume more credit, leaving them as indebted in credit card debt three quarters post-MPL loan origination as they were prior to borrowing on the MPL platform. Further, they experience a significant increase in credit card default occurrences in the months following MPL loan origination, with the effects more pronounced for subprime MPL borrowers. Our results highlight how MPL platforms substantially increase the probability of converting subprime (near-prime) borrowers into near-prime (prime) borrowers through credit card debt consolidation, and how the resulting “information cascade” to traditional banks could lead to some borrowers being worse off.

原文链接：

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=1792

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