Federal Reserve

FEDS Paper: “Harvest Now Decrypt Later”: Examining Post-Quantum Cryptography and the Data Privacy Risks for Distributed Ledger Networks

09/30/2025 Federal Reserve Central banks

Jillian Mascelli and Megan RoddenThis paper analyzes the risks posed by future-state quantum computers, specifically the “harvest now decrypt later” (HNDL) risk. We review foundational concepts of quantum computing to address the present and ongoing threat of HNDL to currently protected data. We use the Bitcoin network as an illustrative example to study the implications of HNDL for distributed ledger cryptocurrency networks that rely upon traditional cryptography.

FEDS Paper: Can LLMs Improve Sanctions Screening in the Financial System? Evidence from a Fuzzy Matching Assessment

09/29/2025 Federal Reserve Central banks

Jeffrey S. Allen and Max S. S. HatfieldWe examined the performance of four families of large language models (LLMs) and a variety of common fuzzy matching algorithms in assessing the similarity of names and addresses in a sanctions screening context. On average, across a range of realistic matching thresholds, the LLMs in our study reduced sanctions screening false positives by 92 percent and increased detection rates by 11 percent relative to the best-performing fuzzy matching baseline.

FEDS Paper: Parallel Trends Forest: Data-Driven Control Sample Selection in Difference-in-Differences

09/29/2025 Federal Reserve Central banks

Yesol Huh and Matthew Vanderpool KlingThis paper introduces parallel trends forest, a novel approach to constructing optimal control samples when using difference-in-differences (DiD) in a relatively long panel data with little randomization in treatment assignment. Our method uses machine learning techniques to construct an optimal control sample that best meet the parallel trends assumption. We demonstrate that our approach outperforms existing methods, particularly with noisy, granular data.

FEDS Paper: Financial Stability Implications of Generative AI: Taming the Animal Spirits

09/26/2025 Federal Reserve Central banks

Anne Lundgaard Hansen and Seung Jung LeeThis paper investigates the impact of the adoption of generative AI on financial stability. We conduct laboratory-style experiments using large language models to replicate classic studies on herd behavior in investment decisions. Our results show that AI agents make more rational decisions than humans, relying predominantly on private information over market trends.

IFDP Paper: Imperfect Information and Slow Recoveries in the Labor Market

09/25/2025 Federal Reserve Central banks

Anushka MitraThe unemployment rate remains elevated long after recessions, a persistence that standard search-and-matching models cannot explain. I show that noise shocks—expectational errors due to the noise in received signals about aggregate shocks—account for much of this sluggishness. Using a structural VAR, I find that absent noise shocks unemployment would have recovered to its pre-recession level six quarters earlier over 1968–2019.

FEDS Paper: Virtue or Mirage? Complexity in Exchange Rate Prediction

09/25/2025 Federal Reserve Central banks

Rehim KilicThis paper investigates whether the “virtue of complexity” (VoC), documented in equity return prediction, extends to exchange rate forecasting. Using nonlinear Ridge regressions with Random Fourier Features (Ridge–RFF), we compare the predictive performance of complex models against linear regression and the robust random walk benchmark.

IFDP Paper: Clean Money, High Costs?

09/25/2025 Federal Reserve Central banks

Viktors StebunovsA cornerstone of the law-and-finance literature is that stronger institutions reduce financial intermediation costs. Using global data on cross-border payment costs, I show this relationship can reverse in heavily regulated sectors. Anti-money laundering risks have larger cost effects in advanced economies with strong enforcement than in developing countries with weak enforcement, despite the former having lower underlying risks.

FEDS Paper: Automated Credit Limit Increases and Consumer Welfare

09/24/2025 Federal Reserve Central banks

Vitaly M. Bord, Agnes Kovacs, and Patrick MoranIn the United States, credit card companies frequently use machine learning algorithms to proactively raise credit limits for borrowers. In contrast, an increasing number of countries have begun to prohibit credit limit increases initiated by banks rather than consumers.

IFDP Paper: Core Inflation in the Advanced Economies: A Regional Perspective

09/19/2025 Federal Reserve Central banks

Daniel O. Beltran and Julio L. OrtizWe explore differences in the dynamics of core inflation between Europe and North America using a Bayesian time series filter that decomposes the level of core inflation in the major advanced economies into regional, global, and country-specific components. We find a prominent role for both regional and global factors. Historically, the two regional components have at times diverged.

FEDS Paper: One Policy Rate, Many Stances: Evidence from the European Monetary Union

09/19/2025 Federal Reserve Central banks

Manuel González-Astudillo, Diego VilánA challenge for conducting monetary policy in a currency union is the diverse economic conditions among member states. Such disparities can drive natural interest rates apart, thereby undermining the stabilizing role of a unified monetary policy.

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