Reduce Warranty Claim Expense by Better Fraud Detection

In this study, we demonstrate how analytics is used to help manufacturers detect fraud in their warranty claims data. Traditional methods of adjudicating claims tends to be manual by an individual auditor that follows set rules and guidelines. Using analytics, the process is automated with the technology able to see patterns in the data an individual just can’t see. Types of fraud where analytics helps in detecting fraud include:

• Fictitious clients and/or claims,
• Double billing on replaced parts, and
• Excess or unnecessary repairs or parts replacement

While analytics is not meant to replace the current claims processing system, it should take a second pass against the data to find those unusual patterns and suspicious links that telegraph possible fraud.

The objective of this study is to present an effective method of controlling warranty claim costs. With estimates of 10% to 15% of warranty claims being fraudulent, the direct cost savings is significant. In addition, secondary effects such as lost revenue from stolen parts being resold, increased costs from additional security and insurance, and reduction in unnecessary field audits makes detection a clear winner.

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