Intelligent Fraud and Dispute Management Systems

Abstract: Fraud and dispute complaints in banking are often received through multiple channels such as online banking, mobile applications, customer service, and branch offices. Handling these complaints manually can lead to delays, incorrect case routing, duplicate complaints, inconsistent investigation, and difficulty in tracking case progress. The proposed Intelligent Fraud and Dispute Management System provides a centralized platform to manage fraud and dispute cases in an organized and efficient manner. The system collects customer and transaction details, validates the information, classifies the complaint based on its type, prioritizes cases according to their urgency, identifies possible duplicate cases, and assigns them to the appropriate investigation team. Investigators can access the case details, record investigation findings, update the case status, and take appropriate action based on the available information. The system maintains a complete record of each case from complaint registration to final resolution, allowing bank staff to monitor the progress and customers to receive timely information about their complaints. The proposed system helps streamline the overall case management process, minimize processing delays and errors, improve coordination between teams, and provide a more transparent and reliable way of handling fraud and dispute complaints.

Keywords: Financial Fraud Management, Dispute Management, Machine Learning, TF-IDF, Logistic Regression, Text Classification, Automated Complaint Categorization, Priority-Based Complaint Routing, Investigation Management.