HYBRID MONEY LAUNDERING DETECTION IN BANKING

Abstract

Money laundering is one of the major financial crimes affecting banking institutions worldwide. Criminals use advanced digital technologies and online banking platforms to hide illegal financial activities, making traditional detection systems less effective. The rapid growth of electronic transactions, mobile banking, and international fund transfers has increased the complexity of identifying suspicious activities. To overcome these challenges, a Hybrid Money Laundering Detection System combines Machine Learning techniques with rule-based analytical methods to improve detection accuracy and reduce fraudulent financial transactions. The proposed hybrid system integrates supervised learning algorithms such as Decision Trees, Random Forest, and Logistic Regression with traditional banking rules and transaction monitoring systems. The system analyzes customer transaction history, transfer frequency, transaction amount, account behavior, and geographical transaction patterns to Int. J. Engg. Res. & Sci. & Tech. 2026, ISSN 2319-5991 Vol. 22, No. 2, 2026 https://ijerst.org/index.php/ijerst 2923 identify abnormal activities. By combining statistical analysis and intelligent learning models, the proposed system can efficiently detect suspicious financial activities in real time. The system also minimizes false positives, which are common in conventional antimoney laundering systems. Banking institutions can use this system to improve financial security, comply with government regulations, and reduce operational risks. The hybrid model continuously learns from newly generated transaction data, thereby increasing detection efficiency over time. The implementation of the proposed system helps financial organizations automate fraud investigation processes and strengthen cyber financial security. Experimental results show that the hybrid approach provides higher detection accuracy compared to existing standalone machine learning or rule-based systems. Therefore, the proposed Hybrid Money Laundering Detection System offers a reliable, scalable, and intelligent solution for modern banking environments.