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Fraud Analytics – predicting and detecting swindlers at work

Fraud Analytics – predicting and detecting swindlers at work

Have you ever been a victim of fraud? Even if we have been fortunate enough to not be swindled ever, this is one of the things individuals and companies have to constantly bother about. Think, for instance, the difficult situation in which insurance companies and banks have to operate. Whereby, a fraudulent claim or transaction can not only cause financial loss, but also damage their credibility and customer relationships. What is there was a way to predict and detect frauds before they happen, and take preventive steps? Sounds like wishful thinking? Well, not exactly so. Welcome to the knight in shining armor, the growing field of Fraud Analytics that involves gathering and mining relevant data to catch discrepancies, interpret patterns and identify anomalies.
As depicted in the figure below, Fraud Analytics combines three activities – mitigating, discovering and investigating fraud – by utilizing past transactions and customer data, otherwise lying unused in databases.

In the insurance sector, for instance, fraud detection and prevention has become a business necessity now, with insurance providers building advanced in-house capabilities in this domain. For instance, HDFC Ergo, one of leading insurance providers in India has set up a dedicated department, Risk and Loss Mitigation, which included a Fraud Control Unit (FCU) that is supported by fraud analytics capabilities to trigger suspected cases.
As swindlers get smarter, enabled by technology, banking and financial institutions will be required to stay a step ahead. That’s where Fraud Analytics will prove to be the difference between being swindled or staying secure!

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