Insurance Fraud Analytics

Value: Arrest claim fraud, reduce pay-out costs

Risk management has always been an integral part of the insurance business. Firms succeed through their ability to identify and manage risks facing their clients. Successful insurers not only understand risk clearly, but also dynamically use available insights to handle exposure to risk through measures aimed at avoiding or preventing losses and screening, pre-empting and pricing them-in in the underwriting process.

Fraudulent claims are a serious financial burden and impact the financial health not only of insurers, but also of innocent people seeking effective insurance coverage. Predictive analytics can help in insurance fraud detection by uncovering the likeliness of frauds arising in medical billing, life insurance, claims and other areas of the business.

Data scientists today can leverage complex and sophisticated capabilities such as predictive modeling, text mining, database searches, anomaly detection and network link analysis to create an advanced and powerful fraud analytics engine.

Our experts can help check claims fraud by:

  • Identifying duplicate claims.
  • Flagging up suspicious transactions for a detailed follow-up.
  • Decrease insurance fraud losses by detecting and preventing fraud before claims are paid leveraging an advanced fraud modeling engine.
  • Persistently improving historical models to address changes in insurance fraud trends.
  • Determining dealers/agents with a high numbers of claim payouts.
  • Attaining fewer false positives that translate into greater customer satisfaction.
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