Research
[ Job Market Paper ]
Open Banking and Customer Data Sharing: Implications for FinTech Borrowers (2023)
[Latest version click here]
JFI/FIRS Ph.D. Student Paper Award, the Financial Intermediation Research Society (FIRS) Annual Conference 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 2023 • ECB Forum 2023 • SAFE Household Finance Workshop 2023 • Bank of Canada 2023 • DGF German Finance Association 2023 • Federal Reserve Bank of Philadelphia 2023
Regulatory Reference: Proposed rule on Personal Financial Data Rights, Consumer Financial Protection Bureau, U.S.
Open banking allows loan applicants to easily share payment data with prospective lenders during loan applications. In theory, this could broaden credit access by reducing information asymmetry but may also lead to price discrimination that exploits individuals’ preferences and behavioral traits. This paper studies the impact of open banking on prospective borrowers and lends empirical support to the sizable benefits of data-sharing driven by improved inferences about borrower credit quality. Using loan application data from a leading German FinTech lender in consumer credit, I show that applicants with observably higher credit risk (with lower credit scores) are more likely to share data. By exploiting the variation of data sharing choices from observably similar applicants, I document that data sharing increases loan approval rates, reduces interest rates, and is associated with lower ex post default rates. These findings suggest that open banking can enhance credit allocation efficiency and reduce adverse selection.
Cybercrimes on the Ethereum Blockchain (2023) with Lars Hornuf, Paul P. Momtaz, and Ye Yuan
Revise & Resubmit, Journal of Banking and Finance
Best Paper Award, Annual Boca Corporate Finance and Governance Conference 2022
Media coverage: Duke FinReg Blog, Decrypt, CoinTribune
We propose a taxonomy of cybercrime on the Ethereum blockchain and examine how cybercrime impacts victims’ risk-taking and returns. Our difference-in-differences analysis of a sample of victims and matched non-victims suggests that victims increase their long-term total risk-taking and earn lower risk-adjusted returns in the post-cybercrime period. Victims’ long-term total risk-taking increases because they increase diversifiable risk in the long term. The increased diversifiable risk correlates with victims’ withdrawal from altcoins after cybercrime. 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, both on the victim and the cybercriminal side.
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