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September 10, 2025LatIAOpen Access

Ethical AI for Personalized Banking: Addressing Bias and Fairness Challenges

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The proposed framework shows improved fairness in decision-making without significantly impacting model accuracy.
Bias metrics indicate measurable reductions in disparate impacts across demographic groups under the new system.
The methodology integrates bias-aware data collection and explainable AI techniques, promoting transparent communication.
Embedding ethical principles into AI ensures regulatory alignment and builds public trust in banking technologies.

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This study develops a framework to address bias and fairness in AI-driven banking, highlighting transparency and regulatory compliance.

Muthu Selvam (2025) studied this question.

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