AI POWERED PUBLIC WELFARE DISTRIBUTION FRAUD DETECTION SYSTEM

Abstract

This project presents an AI-driven public welfare fraud detection system integrated with machine learning technology. The system enhances welfare transparency and accountability by identifying fraudulent transactions. It ensures efficiency, reliability, and intelligent decision-making through artificial intelligence. The system uses financial transaction data and machine learning techniques to identify fraudulent patterns and classify transactions accordingly. Suspicious transactions are detected, improving overall welfare distribution integrity. Traditional welfare monitoring systems rely on manual verification, periodic audits, which can be time-consuming, inconsistent, inaccurate, or inefficient, leading to financial irregularities. These systems also lack intelligent fraud detection and accurate analysis of suspicious transaction patterns. There is a need for an automated, reliable, and cost-effective public welfare fraud detection system that can accurately identify fraudulent transactions and support transparent distribution of welfare benefits using artificial intelligence.