Role of Artificial Intelligence in Fraud Detection and Financial Risk Management

The rapid digitalisation of financial services has created enormous opportunities for banks, financial institutions and businesses, but it has also increased their exposure to fraud and financial risks. Conventional fraud detection systems, which mainly depend on predefined rules and manual investigation, are increasingly challenged by sophisticated and rapidly changing fraudulent activities. Artificial Intelligence (AI), particularly Machine Learning (ML), Deep Learning, Natural Language Processing and anomaly detection, provides financial institutions with new ways to identify suspicious patterns, assess risks and respond to potential threats in real time. This paper examines the role of AI in fraud detection and financial risk management, with particular attention to its applications in banking and digital financial services. The study is conceptual and descriptive in nature and is based on primary data and secondary information obtained from academic literature and reports of financial and international institutions. The paper discusses how AI can improve transaction monitoring, credit risk assessment, anti-money-laundering activities, cybersecurity and predictive risk management. The study argues that AI should not be viewed as a complete replacement for human judgement. Rather, the most effective approach is likely to combine AI-driven analysis with human expertise, appropriate governance and continuous monitoring. The paper concludes that responsible and explainable AI can significantly strengthen the ability of financial institutions to prevent fraud and manage financial risks while maintaining customer trust and financial stability.

Artificial Intelligence, Fraud Detection, Financial Risk Management, Machine Learning, Banking, FinTech, Explainable AI, Cybersecurity

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