Arefin Ahmed Sajib

Explainable and Cost-Sensitive Machine Learning for Fraud Prevention in U.S. Banking: Threshold Optimization, SHAP Explainability, and Fairness Analysis.

Credit card fraud is a major challenge for U.S. financial institutions. Banks need fraud detection systems that can identify fraudulent transactions, reduce false alarms for legitimate customers, and meet regulatory expectations. This study develops an explainable and cost-sensitive machine learning model for detecting...