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: 22nd Dec 2024, 11:48:19am CET
1University of Lausanne, Switzerland; 2Swiss Finance Institute, Switzerland; 3Lisbon Accounting and Business School ISCAL, Portugal; 4University of Basel, Switzerland
Discussant: Chi-Yang Tsou (University of Manchester)
We construct a heterogeneous-firm growth model of the data economy, where data, crucial for business optimization, is at risk of being damaged and destroyed by cyber criminals. Digitally-savvy firms invest in in-house cybersecurity, which can be used to improve the quality of their other products, and trade cybersecurity protection with non-digitally-savvy firms. We use the model to study the impact of cybercrime risk on firm innovation and aggregate growth. Theoretically, we find that cyber-crime unequivocally leads to reduced knowledge stocks, decreased productivity, and slower overall economic growth for all firms. Cybercrime risk mitigates some of the adverse effects as it ex-ante prompts digitally-savvy firms to pursue digital innovation that enhances productivity in other domains. We then test the theoretical prediction using several unique data sets on firms’ in- vestments in cyber-protection. Empirically, we observe increased innovation rates in response to higher cyber-crime risk, driven primarily by data-intensive firms and by firms which intensively pursue in-house cybersecurity protection rather than third-party cybersecurity delegation.
Welfare Effects Of Open Banking; Data Versus Collateral
Mohammad Lashkar, Anastasios Dosis
ESSEC Business School, France
Discussant: Uday Rajan (University of Michigan)
Open banking can alter the information structure of the loan markets by furnishing fintechs with more financial data on their customers and enhancing their screening capabilities. We investigate the welfare implications of open banking by constructing a model of a loan market with adverse selection. In this market, a fintech, reliant on information technology to assess borrowers' credibility, competes with a traditional bank that employs collateral to differentiate between various borrower types.
Our primary finding is that enhancing the fintech's monitoring capacity through the provision of free access to borrowers' information may not necessarily lead to improved welfare. This suggests that complete data sharing (granting the fintech full access to borrowers' data) is not always the optimal solution and could potentially reduce welfare. Specifically, when the bank is sufficiently proficient in utilizing collateral, partial data sharing might be the preferred option.
