AI-driven financial fraud: key risks and legal protections for financial institutions
Vitaliy Shpachuk et al.
What the paper says
Abstract Artificial intelligence (AI) has become integral to financial institutions operations. Implementing AI allowed significant improvement in service quality and enabled innovative customer solutions. At the same time, with all the advantages and positive aspects of using AI, it also creates additional risks, depending on who and for what it is used. In the hands of fraudsters, AI becomes a tool with which financial institutions and their clients are causing significant damage, and not only financial. At the same time, in scientific literature, this issue has been studied mainly from the technical, technological, and financial sides, with insufficient attention paid to the legal risks of this issue. This article addresses that gap by examining the legal risk landscape and protective measures for financial institutions in the context of AI-driven fraud. We review the key ways AI is used to commit fraud, analyse the existing UK and EU legal frameworks governing AI and financial fraud (including data protection and financial services regulation), and evaluate the mechanisms of redress available to clients and institutions. Our analysis highlights inconsistencies and challenges in the current legal approach, particularly in the UK’s principles-based framework, and underlines the need for more transparent accountability, robust risk management, and updated legal remedies to address AI-enabled financial fraud.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.