Unmasking Banking Fraud: Unleashing the Power of Machine Learning and Explainable AI (XAI) on Imbalanced Data

Unmasking Banking Fraud: Unleashing the Power of Machine Learning and Explainable AI (XAI) on Imbalanced Data

Recognizing fraudulent activity in the banking system is essential due to the significant risks involved. When fraudulent transactions are vastly outnumbered by non-fraudulent ones, dealing with imbalanced datasets can be difficult. This study aims to determine the best model for detecting fraud by...

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Bibliographic Details
Main Authors: S. M. Nuruzzaman Nobel, Shirin Sultana, Sondip Poul Singha, Sudipto Chaki, Md. Julkar Nayeen Mahi, Tony Jan, Alistair Barros, Md Whaiduzzaman
Format: Article
Language:English
Published: MDPI AG 2024-05-01
Series:Information
Subjects:
fraud detection
machine learning
logistic regression
decision tree
SVM
XGBoost
Online Access:https://www.mdpi.com/2078-2489/15/6/298

Internet

https://www.mdpi.com/2078-2489/15/6/298

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