Machine Learning for Fraud Detection in Insurance and Retail: Integration Strategies and Implementation
Keywords:
Machine Learning, fraud detectionAbstract
Modern machine learning methods have transformed insurance and retail fraud prevention. The ML-based fraud detection techniques, their implementation difficulties, and their security and fraud preventive effects are examined in this work. This work explores ML fraud detection methods in order to create useful applications and fraud avoidance strategies.
Complicated insurance policies and retail fraud techniques need greater knowledge. While traditional fraud detection is quite effective, sometimes it lags behind fraud tactics. Mass transactional and behavior data enables machine learning methods to detect fraud. ML models suit complicated fraud as they can learn from new data.
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