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FinTech Applications in Credit and Asset Markets

Paper Session

Saturday, Jan. 5, 2019 2:30 PM - 4:30 PM

Hilton Atlanta, 209-210-211
Hosted By: American Finance Association
  • Chair: Michaela Pagel, Columbia University

On the Rise of FinTechs – Credit Scoring using Digital Footprints

Tobias Berg
,
Frankfurt School of Finance and Management
Valentin Burg
,
Humboldt University Berlin
Ana Gombovic
,
Frankfurt School of Finance and Management
Manju Puri
,
Duke University and NBER

Abstract

We analyze the information content of the digital footprint – information that people leave online simply by accessing or registering on a website – for predicting consumer default. We show that even simple, easily accessible variables from the digital footprint equal or exceed the information content of credit bureau scores. The digital footprint complements rather than substitutes for credit bureau information, and is informative even for customers who do not have credit bureau scores. We discuss the implications for financial intermediaries’ business models, for access to credit for the unbanked, and for the behavior of consumers, firms, and regulators in the digital sphere.

Platform Credit and E-Commerce Market Structure

Yi Huang
,
Graduate Institute of International and Development Studies
Ye Li
,
Ohio State University
Hongzhe Shan
,
University of Geneva and 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.

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 a reduction in short-term forecast bias relative to matched control firms. Cross-sectional results consistently favor the disciplining hypothesis over the alternative that sell-side analysts use Estimize forecasts to improve their own forecasts. For example, we find a greater reduction in bias when the consensus includes a larger fraction of forecasts by analysts who enjoy close, mutually beneficial relationships with management but not when conditions conducive to use of Estimize forecasts exist. Finally, we find no change in bias for longer-horizon forecasts or investment recommendations, suggesting competition from Estimize rather than broad economic forces accounts for our results.

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

Sudheer Chava
,
Georgia Institute of Technology
Nikhil Paradkar
,
Georgia Institute of Technology

Abstract

Using comprehensive credit bureau data, we examine the credit dynamics of borrowers on a major marketplace lending (MPL) platform. Relative to their neighbors with identical ex-ante credit dynamics, but with unmet credit demand (those originating unsecured installment loans) from banks, MPL borrowers' credit card balances decline 42% (13%) post-MPL origination, but revert to pre-MPL levels within 4 quarters. Their credit scores increase 21 (14) points immediately after origination, followed by an increase in credit card limits. In the next two years, MPL borrowers' higher indebtedness results in 96% (65%) higher default likelihood, with the effects more pronounced for constrained borrowers.
Discussant(s)
Keith Chen
,
University of California-Los Angeles
Sabrina T. Howell
,
New York University
Jillian Grennan
,
Duke University
Boris Vallee
,
Harvard Business School
JEL Classifications
  • G0 - General