Creating healthier pharmacy co-pay programs
KPMG is helping a global pharmaceutical manufacturer use artificial intelligence to identify and respond to co-pay fraud.
Creating healthier pharmacy co-pay programs
KPMG is helping a global pharmaceutical manufacturer use artificial intelligence to identify and respond to co-pay fraud.
Client
A large global pharmaceutical manufacturer
Sector
Life sciences
Project
Pharmacy co-pay fraud monitoring solution
In the midst of efforts to keep medicine accessible and affordable, our client faced a growing challenge: rising levels of fraud in co-pay and coupon programs. Fraudulent claims can cost drug companies upward of tens of millions of dollars every year. Common risks include fictitious pharmacies, fictitious pharmacy claims, and reimbursement maximizers, in which pharmacies submit multiple claims for the same co-pay card or multiple co-pay cards for the same prescription.
What’s the solution? More collaborative monitoring between co-pay parties so that this pharma manufacturer can identify potential fraud earlier. This proactive approach uses insights from data and analytics that—with a few tweaks—also can provide profitable insights into other critical areas of the business.
KPMG will also work with the company to customize new AI applications in areas such as customer intelligence, profit analytics, and rebate leakage.
Approach
Like many pharmaceutical manufacturers, our client relies on its co-pay program vendor to monitor fraudulent pharmacy activity. However, the vendor had limited capacity to review and investigate pharmacies (approximately two investigations per day), when at least 300 pharmacies were engaging in fraudulent activities, according to the vendor’s estimates. This is a typical situation for most vendors. They have limited line of sight and few controls or programs for investigations.
Notified of yet another fraudulent attempt, this company asked KPMG to help it build internal capabilities so that they could identify fraud and respond proactively without having to rely solely on its co-pay vendor. Having worked with our client over many years, we built a custom solution tailored to the nuances of each of the company’s program and business needs, combining our deep industry experience and extensive forensic and analytics capabilities.
Our work was expedited by the KPMG Lighthouse team of data scientists and modelers, software and data engineers, and advanced analytics consultants. They used artificial intelligence technologies in the KPMG Ignite platform to rapidly aggregate relevant, available data from internal and external sources to analyze and detect fraudulent pharmacy activities.
Our pharmacy co-pay fraud monitoring solution allows for more collaboration between our client and its co-pay vendors. It enables them to proactively identify potential instances of fraud based on fraud indicators and patterns, perform follow-ups and investigations with vendors, and block pharmacies temporarily or indefinitely, depending on results from the analysis and investigation.
The solution and its underlying processes also can be incorporated into the co-pay vendor’s monitoring efforts to give the company control and 360-degree line of sight into high-risk pharmacies that should be investigated.
In the first week of beta testing, KPMG identified and confirmed four pharmacies that received approximately $1 million in fraudulent reimbursements in 2018.
Going forward, we will provide:
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KPMG’s solution provides the manufacturer with increased line of sight into co-pay and coupon programs not readily available to most pharmaceutical manufacturers. By the end of our engagement, they were able to:
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Don’t rely solely on co-pay vendors to detect fraud
They don’t have the bandwidth. By assessing your historical program data and building internal capability yourself, you can better collaborate with your vendors to root out fraud.
Leverage the data you collect to solve other business problems
You own the opportunity to do this and you should. Once you have the different data sources required for the fraud solution gathered in one place, you can apply a different lens to the data and gain profitable new insights for other areas.