Claim Analysis and fraud detection Using Business Intelligence

Fast and effective claim handling is the base for customer relationships in the insurance industry, but insurance companies also have to protect themselves from the fraud claims that they might be faced with time to time.

A new study from the Insurance Research Council (IRC) estimates that claim fraud and buildup added between $5.6 billion and $7.7 billion in excess payments to auto injury claims paid in the United States in 2012.

“The costs associated with auto injury claim abuse make auto insurance more expensive for everyone,” said Elizabeth Sprinkel, senior vice president of the IRC.

This has the insurance industry looking for a solution which can help them in identifying and handling the fraudulent claims. They require the raw data to be converted to intelligent information. Using BI and specifically, OLAP models and data warehousing technology, all the data can be gathered and managed at a single place. This information can be further used to design dashboards and reports, providing a clear picture of how and where the business is headed. In these dashboards it is possible to create data trends along with various aspects such as customer, time span and insured party.

Using these dashboards, an insurance company can drill down data to better understand the trends and patterns in claims. BI applications can even be used to identify the fraudulent transactions. If the trend of the claim or the payoff is unusual, they can further gain deeper insight and check the unusual claim pattern with other factors as agent, insured party etc.

A fraudulent claim can be easily identified through advance analysis of the claim data incorporated with other internal or external data, such as payment history. Different data mining tools incorporated into a solution can spot trends in claims and as fraudulent claims have uncommon trends, these can be sent for further investigation before payment are disbursed.

BI can crack down on insurance frauds by tracking trends using advanced analytics hence helping n reducing payout for fraudulent claims. This also brings in an added advantage to capping premiums, resulting in increased customer loyalty.

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Ankit Jain

Ankit Jain

A data warehousing and analytics engineer experienced in working with Qlikview, Qliksense and PowerBI reporting tools. Table tennis and music take up the rest of my day usually.