The client is a large Insurance Company that provides Workers compensation Insurance policies to the workforce. The main challenge for them was to predict genuine vs. fraudulent claims. The company was not able to identify the fraudulent claims that were costing them billions of dollars in annual losses. The aim of this project was to rate the claims so that the Special Investigative Units (SIU) can process the cases according to the risk levels. After a detailed evaluation of their operation data, AI Labs (www.ailabsinc.com) used its proprietary Minsky AI Engine to build an optimized model using a combination of AI algorithms and prediction attributes. Based on this historical AI model, current customer claim data was used to predict if the claim could be fraudulent for each customer. This solution was developed and implemented in less than a week.
Typical Insurance Fraud Challenges:
How to minimize losses from fraudulent claims.
Adversely impacts the insurer’s relationship with its existing customers.
Has a significant impact on competitive advantage.
Excessive resource time wasted to check fraudulent claims manually.
Difficulty in identifying fraudulent vs. genuine claims.