Research
Open Banking and Customer Data Sharing: Implications for FinTech Borrowers
[Latest version click here]
Open banking enables loan applicants to easily and securely share bank transaction data with lenders. In theory, this can expand credit access by reducing information asymmetry, but it may also facilitate price discrimination. Using data from Germany’s largest fintech lender in consumer credit, I examine who shares data and how this affects lending outcomes. Observably riskier applicants for whom information asymmetry is greater are more likely to share. Data sharing improves approval and pricing through better risk assessment and is associated with lower ex post defaults. However, non-disclosure leads to negative inferences, with implications for privacy-conscious applicants.
WFA Brattle Group Ph.D. Candidate Award for Outstanding Research 2024 • JFI/FIRS Ph.D. Student Paper Award 2023 • Best Ph.D. Paper Award, Future of Financial Information 2023 at HEC (sponsored by BlackRock) • Best Paper in Digital Finance, the DGF German Finance Association 2023 • Finalist, the ECB Young Economist Prize 2023
Selected Presentations: NBER on Innovative Data in Household Finance 2022 • Bank of England 2023 • Swiss Winter Conference on Financial Intermediation 2023 • Future of Financial Information 2023 • SFS Cavalcade NA 2023 • FIRS Ph.D. Session 2023 • ECB Forum 2023 • SAFE Household Finance Workshop 2023 • Bank of Canada 2023 • DGF German Finance Association 2023 • Federal Reserve Bank of Philadelphia 2023 • OFR Rising Scholars Conference 2024 • WFA 2024 • NBER SI 2024 • EFA 2024
Regulatory Reference: Proposed rule on Personal Financial Data Rights, Consumer Financial Protection Bureau, U.S.
Cybercrime on the Ethereum Blockchain with Lars Hornuf, Paul P. Momtaz, and Ye Yuan
Forthcoming, Journal of Banking and Finance
We examine how cybercrime impacts victims’ risk-taking and returns. The results from our difference-in-differences analysis of a sample of victim and matched non-victim investors on the Ethereum blockchain are in line with prospect theory and suggests that victims increase their long-term total risk-taking after losing part of their wealth, leading to lower risk-adjusted returns in the post-cybercrime period. Victims’ long-term total risk-taking increases because they increase diversifiable risk due to victims’ post-cybercrime withdrawal from altcoins. At the same time, the reduction in risk-adjusted returns correlates with increased trading activity and churn, due plausibly to managing cybercrime exposure. In the cross-section of Ethereum addresses, we show that the most affluent victims take a systematic approach to restore their pre-cybercrime wealth level, while the least affluent victims turn into gamblers. Finally, a parsimonious forensic model explains a good part of the addresses’ probability of being involved in cybercrime, on both the victim and the cybercriminal side.
Best Paper Award, Annual Boca Corporate Finance and Governance Conference 2022
Media coverage: Duke FinReg Blog, Decrypt, CoinTribune
Work in progress
"Risk and Returns of Liquidity Provision in Decentralized Exchanges"
(with Igor Makarov and Antoinette Schoar)
"Securitization and Specialization: the Role of Fintech and Online Banks in a Segmented Market"
(with Laura Bottazzi, Chiara Farronato, and Loriana Pelizzon)
Other work
A Multidimensional Approach to Trade Policy Indicators, (2018) IMF Working Paper with Diego A. Cerdeiro
[Box 1.6 in IMF 2018 World Economic Outlook] [Box 3.7 in WTO 2018 Report on G20 Trade Measures]
We present and discuss a set of indicators to help assess countries’ trade policies. The indicators relate to three policy areas – trade in goods, trade in services, and FDI. Given concerns about the direction of global trade policy, we also consider a set of more granular measures that reflect the evolution of countries’ policies since the 2008 financial crisis. We propose a simple approach to present the multidimensional aspects of trade policy that, by shedding light on relative openness across areas, can facilitate policy discussions. In the cross-section of countries, we find a diversity in the type of measures adopted, both between and (since the 2008 financial crisis) within policy areas, lending support to the approach based on multiple indicators. The indicators’ time series suggest that advanced and, especially, emerging economies are moving toward more open regimes over time, although recently progress has, with some exceptions, slowed across the board. Lastly, our findings also call for stronger efforts to objectively quantify the different aspects of countries’ trade regimes. More data, both across countries and in terms of policy areas that significantly affect trade, are needed for better-informed policy discussions.
The Revised EBA-Lite Methodology, (2019) IMF Policy Paper No. 19/026 with Mitali Das (lead) and others
The Methodology review identified three broad areas for improving the EBA-Lite methodology: (1) expanding the fundamentals and policy determinants in the CA and REER regressions to better capture the external balance of EBA-Lite countries; (2) identifying alternatives to regression models for external assessments of large exporters of exhaustible commodities; and (3) a revised approach for the assessment of external sustainability in highly indebted economies. Accordingly, the revised methodology consists of three modules: 1) Regression Module 2) Module for External Assessments of Exporters of Exhaustible Commodities 3) Module for the Assessment of External Sustainability