The healthcare fraud and abuse management solution for payers from IBM supports a diverse range of fraud investigation and management both before and after claims payment, including prevention, investigation, detection and settlement.
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Fraud Detection Solutions from IBM
1. IBM Sales and Distribution Healthcare payers
Solution Brief
Fraud and abuse
management for payers
Prevent and detect fraudulent claims
To uncover fraudulent and abusive behavior, investigators must sort
Highlights through millions of individual claims to find suspicious behavior, often
relying on a pay-and-chase strategy—pursuing cases after claims have
● Support a diverse range of fraud already been paid. IBM has worked closely with healthcare investiga-
investigation before and after claims
payment tors to develop the fraud and abuse management solution for payers
with both proactive and retrospective detection capabilities.
● Sort millions of claims in minutes and
rank providers by degree of potentially
abusive behavior A sophisticated, comprehensive solution
Detecting suspicious claims activity—such as billing for services not
● Pinpoint claims most likely to be fraud-
ulent or erroneous with advanced algo- performed, billing more expensive claims than the actual service ren-
rithms and analytical models dered, overprescribing tests and medications, and requiring tests and
● Achieve rapid return on investment by
procedures that are not medically necessary—is a difficult data-
enabling investigators and auditors to intensive task. The fraud and abuse management solution for payers
become more productive from IBM supports a diverse range of fraud investigation both before
and after claims payment, including prevention, investigation, detec-
tion and settlement.
The solution can help you transform your fraud and abuse manage-
ment strategy by analyzing claims data using prebuilt fraud detection
models designed for the healthcare industry. These models have been
developed in conjunction with fraud investigators working in the field,
and include an updated library of 9,000 risk indicators that can be used
like building blocks to build new models or change existing ones.
Advanced algorithms developed by IBM Research can help pinpoint
claims most likely to be fraudulent or erroneous. Our analytical tech-
niques include evaluating nonstandard claims submissions and statisti-
cal outliers, identifying patterns of abusive claims submissions and
defining new provider segments to find previously unknown patterns of