Citation:

Rakesh Kopperapu. "Harnessing AI and Machine Learning for Enhanced Fraud Detection and Risk Management in Financial Services" International Research Journal of Economics and Management Studies, Vol. 3, No. 12, pp. 109-114, 2024.

Abstract:

The paper can go on to review the application of AI and ML to fraud detection and, in a wider context, to financial service risk management. AI-based anomaly detection and predictive modeling will, for enhanced risk assessment, be introduced into the GNN and XAI frameworks. Performance is investigated regarding each model through the precision score, the recall, and F1, which can take either supervising, unsupervised learning, or reinforcement. It addresses the challenges of data scalability, algorithmic bias, and regulatory compliance to underline hybrid model adoption gaps and real-world scalability. The following research can apply the thematic analysis of secondary data in order to propose effective AI and ML frameworks for fraud prevention and decision-making.

References:

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Keywords:

Artificial Intelligence (AI), Machine Learning (ML), Fraud Detection, Risk Management, Anomaly Detection, Predictive Modeling, Explainable AI (XAI), Graph Neural Networks (GNNs).