Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 30th Sept 2023, 08:24:14am CEST
Does IT help? Information Technology in Banking and Entrepreneurship
Yannick Timmer1, Sebastian Doerr2, Toni Ahnert3, Nicola Pierri4
1Federal Reserve Board; 2BIS; 3ECB; 4IMF
Discussant: Junli Zhao (Bayes Business School)
This paper provides novel evidence on the importance of information technology (IT) in banking for entrepreneurship. To guide our analysis, we build a parsimonious model of bank screening and lending. The model predicts that IT in banking can spur entrepreneurship by making it easier for startups to borrow against collateral. We empirically show that job creation by young firms is stronger in US counties that are more exposed to IT-intensive banks. Consistent with a strengthened collateral channel, entrepreneurship increases by more in IT-exposed counties when house prices rise. Regressions at the bank level further show that banks' IT adoption makes credit supply more responsive to changes in local house prices, and reduces the importance of geographical distance between borrowers and lenders. These results suggest that IT adoption in the financial sector can increase dynamism by improving startups' access to finance.
Borrowing from a Bigtech Platform
Jian Li1, Stefano Pegoraro2
1Columbia University, United States of America; 2University of Notre Dame, Mendoza College of Business
Discussant: Jing Zeng (University of Bonn)
We model competition in the credit market between banks and a bigtech platform which offers a marketplace for merchants. We show that, unlike banks, the platform lends to merchants based on their revenues and network externalities. To enforce partial loan repayment, the platform increases borrowers' transaction fees. Credit markets become partially segmented, with the platform targeting borrowers of low and medium credit quality. The platform benefits from advantageous selection at the expense of banks, reducing equilibrium welfare for intermediate-credit-quality merchants. When revenues, network externalities, or advantageous-selection rents are large, the platform does not value superior information about credit quality.
