Artificial Intelligence and Risk Management in Financial Institutions: Evidence from the UK Banking Sector

Abstract

Introduction: Artificial Intelligence (AI) has become a transformative force in the global financial sector, reshaping how institutions assess, predict, and mitigate risks. In the United Kingdom, major financial institutions have rapidly adopted AI-driven technologies to enhance operational efficiency and ensure regulatory compliance.
Objective: This study investigates the impact of AI on risk assessment and management among financial institutions in the United Kingdom, focusing on the extent of AI tool adoption and its influence on decision-making and compliance processes.
Method: A quantitative survey research design was employed. Data were collected from 150 banking professionals across five major institutions, Barclays, Halifax, Lloyds, Nationwide Building Society, and NatWest Bank, using a structured five-point Likert scale questionnaire. A total of 138 valid responses were analyzed using descriptive statistics.
Results: Findings revealed widespread adoption of AI tools such as chatbots, robotic process automation (RPA), credit scoring models, behavioral biometrics, and algorithmic trading. Respondents strongly agreed that AI automates critical aspects of risk management (Mean = 4.43), streamlines KYC and AML compliance (Mean = 4.41), and enhances fraud detection (Mean = 4.20). The results further indicated improved precision in risk modeling and decision-making processes (Mean = 4.30).
Conclusion: The study concludes that AI has significantly enhanced efficiency, accuracy, and transparency in risk management among UK financial institutions. However, concerns persist regarding algorithmic bias, ethical accountability, and data privacy. The study recommends that financial institutions adopt explainable AI frameworks and regulators develop ethical guidelines for responsible AI integration.