Fraudulent-Insurance-Claims-Detection-System

Fraudulent Insurance Claims Detection System using Random Forest algorithm is a powerful machine learning model that has been developed to tackle the problem of insurance fraud. This system uses a Random Forest algorithm, a popular ensemble learning technique, to effectively identify fraudulent insurance claims. The model works by analyzing a large set of insurance data, identifying patterns and trends that suggest fraudulent behavior, and predicting the likelihood of a given claim being fraudulent. This is achieved by training the Random Forest algorithm on a labeled dataset of both fraudulent and non-fraudulent claims, which allows it to learn to recognize the characteristics of fraudulent claims and make accurate predictions.