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Suspect Claims Detection

SAS® OnDemand: Suspect Claims Detection

Optimize auditor time and reduce service costs

Analyze service claim data to identify suspicious claims and service providers. Using dozens of automated analytic models built on the SAS Fraud Framework, the solution goes beyond traditional business rule engines to allow manufacturers and retailers to focus their auditors on the most likely sources of fraud. With the SAS Cloud Analytics delivery method, business results are gained rapidly with minimal IT investment distributed predictably over time.

Now that we're addressing suspicious claims activity, we're looking for other ways to use analytics to improve the consumer experience.

Julie Tisera
Consumer Experience Manager
GE Consumer & Industrial


Reduce service costs.

By denying or charging back for illegitimate claims, service costs can be greatly reduced. Illegitimate claims can decrease from service providers becoming aware of being monitored.

Maximize effectiveness of auditors’ time.

Auditors are able to focus on the claims and service providers with the highest probability of fraud.

Improve service network effectiveness.

Automated claim review uncovers patterns of inefficiency where service providers can improve their performance and enhance end-user satisfaction.

Analyze and optimize parts usage.

Automated analytics detect patterns of parts usage that can be utilized to retrain technicians and save parts costs.

Short time to implementation.

The solution is hosted on a secure, shareable and scalable infrastructure specifically designed for detection of suspect claims, without the up-front IT investment, staff and maintenance costs.


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Suspect Claims Detection
  • Scoring.
  • Data and text mining with predictive models.
  • Dispositioning.
  • Hosted solution.
  • IT and analytics expertise.
  • Flexibility.

Technical Information

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