Fraudulent Claim Modeling

Insurance Claims Decrease Costs Reduce Risk
Minimize unwarranted payouts and unnecessary investigations by delivering reliable fraud detection models with AI.
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Problem: Predicting Insurance Claim Fraud Can Be Difficult 

Insurance claim fraud could be costing you millions. Industry wide, insurance claim fraud cases account for billions in lost revenue. No insurer is exempt from insurance claim fraud. It is critical for an insurer to build and deploy AI fraud detection models. 

AI allows an insurer to accurately predict the legitimacy of claims, which significantly reduces not only unwarranted payouts but also unnecessary and costly investigation of innocent claims. Ultimately, this leads to a positive customer experience.

Solution: Preventing Insurance Fraud with AI 

AI learns patterns associated with fraudulent claims from historical cases of fraud and applies the patterns learned to new claims to assess their likelihood to be fraudulent. For insurers without historical claims fraud data, AI can help as well. An anomaly detection model can be built to help narrow down a list of potential fraudulent claims; human interpretation then can validate the flagged claims. The anomaly detection model also enables early identification of new fraudulent schemes. Having an accurate and reliable fraud detection model and an anomaly detection model is essential to minimizing your organization’s chance of being victims of claim fraud. 

The resulting benefits are multifold. First, the model predictions facilitate an insurer to prioritize their valuable investigative resources on only those claims that are highly likely to be fraudulent. The more focused process improves the return on investment in claim fraud investigation. In addition, an effective monitoring system enabled by anomaly detection minimizes the chance of being manipulated by fraudsters with new fraud schemes. More importantly, you optimize customer satisfaction by not challenging innocent claims. 

In short, with AI fraud detection modeling, you save time, money, and resources while getting much better results. 

Why DataRobot: The Fraud Detection Modeling You Need 

AI models for claim fraud can take a long time to build if done manually. However, claim fraud schemes can change very quickly which makes the models in production outdated. Therefore, it is essential to be capable of developing and updating these models with agility. DataRobot makes all of these imperative tasks easy by automating the model training and retraining process. This significantly reduces the model development and deployment cycle, ensuring that you have the most accurate model in production all the time. That’s the smart, efficient way forward for your business.

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Insurance companies are using machine learning and AI to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from underwriting to marketing in order to make data-driven decisions to lead to increased profitability.