Insurance fraud is a significant issue that affects consumers, insurance providers, and society at large. It costs billions of dollars annually. Manual inquiry and rule-based systems, which are common traditional techniques for identifying and preventing insurance fraud, are sometimes time-consuming and ineffective.
In this video, we examine how artificial intelligence (AI) and machine learning can change the detection of insurance fraud. Machine learning algorithms can assist insurers in discovering fraudulent activity more quickly and accurately by evaluating vast volumes of data and identifying patterns and trends that may suggest fraud. Additionally, we go over the advantages of machine learning for detecting insurance fraud, including increased effectiveness, financial savings, and client happiness.
Finally, we give some instances of how machine learning is being employed in the insurance sector and share our opinions on how fraud prevention and detection in the insurance sector will develop in the future.
Checkout the projects that we discussed in this video:
Ensemble Machine Learning Project - All State Insurance Claims Severity Prediction: [ Ссылка ]
Insurance Pricing Forecast Using XGBoost Regressor: [ Ссылка ]
We hope you like this video and want to learn more, so checkout ProjectPro the only end-to-end project solution: [ Ссылка ]
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