This study empirically investigates the performance of Elastic Machine Learning, an industrial, unsupervised anomaly detection tool, in the identification of fraudulent behavior in banking transactions. Using AI-generated datasets that were designed to simulate realistic banking environments,...

We propose a quantitative framework to track systemic risk arising from cyber vulnerabilities of the U.S. financial system. Synthesizing financial, economic, cyber, and network data that covers thousands of financial institutions and technological firms, we develop an index that tracks...

As Thailand's financial sector accelerates its digital transformation, cybersecurity has transitioned from a mere technical support function to a strategic imperative that governs operational risk and financial stability. This study empirically examines the efficacy of cyber risk controls and...

The paper synthesizes global experiences and key lessons in the regulation and supervision of cyber risk in the financial sector. It draws on the IMF’s financial stability surveillance and technical assistance work. It underscores the increasing frequency and complexity of cyber threats. These...

Investment in cybersecurity in an interconnected banking system has public-good properties: positive externalities can generate systemic underinvestment. Using confidential supervisory data from the European Central Bank, we first identify "laggard" European banks that underinvest relative to...

This study investigates the evolving trajectories of romance fraud offenders in Ghana through a longitudinal qualitative design grounded in actor-network theory. Drawing on interviews with sixteen self-identified scammers conducted over a four-year period, the research traces how individuals...