Prateek Mahajan
Finance Ph.D. Student at UT Austin
NBER Graduate Fellow in Consumer Financial Management
CV | Google Scholar | LinkedIn
Email: prateek.mahajan@mccombs.utexas.edu
I will be on the job market during the 2026-27 academic year.
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Publications
Did FinTech Lenders Facilitate PPP Fraud?
(with John M. Griffin and Samuel Kruger)
Journal of Finance, 78: 1777-1827 (2023)
[SSRN Version] [Internet Appendix] [Replication Package]
In the $793 billion Paycheck Protection Program (PPP), we examine metrics related to potential misreporting including non-registered businesses, multiple businesses at residential addresses, abnormally high implied compensation per employee, and large inconsistencies with jobs reported in another government program. These measures consistently concentrate in certain FinTech lenders and are cross-verified by seven additional measures. FinTech market share increased significantly over time, and suspicious lending by FinTechs in 2021 is four times the level at the start of the program. Suspicious loans are being overwhelmingly forgiven at similar rates to other loans.
Cited by U.S. House Committee Report on PPP Fraud, PPP and Bank Fraud Enforcement Harmonization Act of 2022, and U.S. House Committee Report on Lessons Learned from the Coronavirus Crisis
Media Coverage: New York Times, Bloomberg, USA Today, National Public Radio, Washington Post, Atlanta Journal-Constitution, Miami Herald, CNN, NBC News, Fox News, and over 300 others
Is Fraud Contagious? Social Connections and the Looting of COVID Relief Programs
(with John M. Griffin and Samuel Kruger)
Review of Financial Studies, Forthcoming
[SSRN Version] [2024 WP Version (includes UI, EIDL, and ERC results)] [Internet Appendix] [Replication Package]
Fraud indicators within the Paycheck Protection Program (PPP), a major COVID relief program, are highly geographically concentrated. ZIP codes and counties with high rates of suspicious PPP loans are strongly socially connected, with evidence that fraud spreads spatially over time through social networks. Individuals in suspicious social media groups have higher rates of PPP fraud, and socially connected ZIP codes frequently use the same specific FinTech lenders, consistent with social networks influencing detailed loan decisions. Our findings suggest that more proactive data analysis is needed for fraud prevention, detection, and prosecution to prevent the social spread of fraudulent schemes.
Media Coverage: NBC
Did Pandemic Relief Fraud Inflate House Prices?
(with John M. Griffin and Samuel Kruger)
Journal of Financial Economics, 180: 104275 (2026)
[SSRN Version] [Note Regarding Figure 2] [Internet Appendix] [Replication Package]
Pandemic fraud is geographically concentrated and stimulated local purchases, with effects on prices. Recipients of fraudulent Paycheck Protection Program (PPP) funds significantly increased their home purchasing rate compared to recipients of non-fraudulent PPP funds, and house prices in high-fraud ZIP codes increased 5.8 percentage points more than in low-fraud ZIP codes within the same county. In a horse race, pandemic fraud is one of the largest and most robust factors explaining house price appreciation during COVID. ZIP codes with fraud also experienced heightened vehicle purchases and other consumer spending in 2020-21, with a return to normal in 2022.
Media Coverage: Wall Street Journal, Associated Press, National Public Radio, CNBC, Fox Business
Working Papers
(with Minjoo Kim and Zirui Wang)
Supported by funding from Real Estate Research Institute (RERI) and Brookings Institution, Hutchins Center on Fiscal and Monetary Policy
Using a large, novel set of property-level operating statements for multifamily properties, we analyze the drivers and consequences of rising insurance costs. We identify three forces behind this repricing: more aggressive pricing of local climate risk after 2018, rising reinsurance costs amplifying increases in exposed states, and homeowners-market frictions that spill over into commercial policies. Rent increases offset half of these costs on average, but this burden-sharing breaks down for larger, more recent shocks, lowering profitability and property values. Owners with larger and lower-risk portfolios obtain more favorable pricing, especially for high-risk properties, increasingly driving reallocation toward larger owners.
Is Auto ABS a Vehicle for Misreporting?
Using data on over 20 million auto loans from 398 auto asset-backed security (ABS) deals, I find signs of misreporting that are consistent with those found in other forms of ABS (such as RMBS and CMBS). Loans immediately below discrete LTV are found to be riskier. Borrowers/dealers are inflating book values of vehicles to lower LTV and overstating income to lower PTI and DTI. Differences in inflation across originators are persistent over time. Loans with misreporting are defaulting at increasingly higher rates post-COVID. The misreporting is partially priced at the loan-level in the form of higher interest rates, but investors do not appear to be compensated for the added risk at the deal-level.
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