Transaction Fraud Detection System

Abstract

The aim of Transaction Fraud Detection System is considered to be one of the groundbreaking technological solutions in the new era of the modern insurance company as a method of securing against fraud. From the insurance categories, the platform uses modern artificial intelligence, and machine learning technology to auto detecting of fraudulent insurance claims. K-Means, Isolation Forest and DBSCAN algorithms are used by the system to process large datasets to find irregular patterns that represent fraudulent conduct. In addition to the logical dashboards and total fraud risk appraisal and adjustable reporting, operational performance is increased as well as decision processors. The platform provides a Fraud Detection that simultaneously results in an optimized fraud, lesser human mistakes and helps insurance providers minimize financial losses and bring higher levels of transparency while building a better trust relationship with the clientele. This way the insurance industry gets modern day protection because what the platform always does is stays up-to-date with the emerging fraudulent techniques that emerge as they are constantly learning and adapting to.