Data-Driven Cybersecurity Risk Assessment in FinTech: A Mixed-Methods Analysis of Breach Patterns, Vulnerability Factors and Financial Impact, 2008-2025

Abstract

: As FinTech has grown, digital financial platforms have become major targets for cybercriminals, yet most research on FinTech cybersecurity only describes incidents without measuring patterns or risk. In this study, I built a dataset of 47 publicly reported FinTech cyber incidents from 2008 to 2025, recording the type of company, attack method, records exposed, financial loss and root causes of each, and analysed it using statistical tests and a content analysis of incident narratives. Three clear patterns emerged. First, damage is highly uneven, with just three incidents accounting for almost 70% of the 1.69 billion records exposed. Second, attacks increasingly come through outside vendors and partners. Third-party involvement rose from zero incidents before 2020 to half of all incidents in 2023 – 2025, and ransomware caused six of the sixteen most recent cases. Third, crypto and DeFi platforms suffered far larger losses, with a median loss of US$290 million compared with US$26 million for other FinTech firms. My findings suggest that FinTech cyber risk now spreads through vendors and shared systems across the ecosystem rather than through attacks on single companies. Based on this, I propose a five-stage framework that FinTech firms can use to assess and prioritise their cyber risks.