Explainable Artificial Intelligence for Financial Fraud Detection: Bridging Transparency, Trust and Regulatory Compliance in Digital Banking Systems

M Ravi Kumar

Explainable Artificial Intelligence for Financial Fraud Detection: Bridging Transparency, Trust and Regulatory Compliance in Digital Banking Systems

Author(s)	M Ravi Kumar
Country	India
Abstract	The rapid growth of digital banking, mobile payments and online financial services has increased the speed, volume and complexity of financial transactions while simultaneously creating new opportunities for fraud. Highly accurate AI models, particularly ensemble and deep-learning models, can be difficult for customers, bank employees, auditors and regulators to understand. This creates a fundamental tension between predictive performance and explainability. Explainable Artificial Intelligence (XAI) offers a potential solution by providing understandable explanations for why an AI system has classified a transaction as fraudulent or legitimate. Techniques such as SHAP (Shapley Additive Explanations), LIME, feature importance, counterfactual explanations and graphical explanations can help financial institutions establish greater transparency and accountability. This research examines how XAI can bridge the gap between fraud-detection accuracy, transparency, customer trust and regulatory compliance in digital banking. The analysis shows that AI adoption was already substantial in financial services, while explainability was becoming an important governance requirement. IBM's 2023 Global AI Adoption Index reported that approximately 42% of large organisations had actively deployed AI, while financial services was the industry most likely to report active AI deployment. In India, 59% of surveyed large enterprises had actively deployed AI, and 94% of Indian respondents considered the
Keywords	Explainable Artificial Intelligence, Financial Fraud Detection, Digital Banking, SHAP, LIME, Banking Security.
Published In	Volume 5, Issue 6, June 2024
Published On	2024-06-07

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Explainable Artificial Intelligence for Financial Fraud Detection: Bridging Transparency, Trust and Regulatory Compliance in Digital Banking Systems

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