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Predictive analytics, behavioral economics and collective intelligence are key, per a new report.
State governments must protect against large-scale identity theft after adopting digital technologies, while still grappling with more traditional food stamp and Medicaid fraud networks, according to a new Deloitte University Press report.
Public funding for fraud and abuse prevention and enforcement is either stagnant or declining, depending on the state, particularly for political positions like auditor or inspector general.
Instead a “holistic approach” incorporating predictive analytics, behavioral economics and collective intelligence is required of state agencies, per the report:
Five strategies in particular are critical:
- Make data collection central to anti-fraud and waste strategies
- Create a learning system to respond to ever-changing threats
- Emphasize prevention to get the best return on effort
- Use “choice architecture” to encourage compliance
- Share intelligence to reduce intentional fraud
Identifying and compiling necessary data from state agencies, benefits programs and social media is step one of fraud and waste prevention, when it comes to transactions.
From there, implementing “adaptive” cyber defense systems that reconfigure based on that data, as well as human behavior, provides for unpredictability—optimal security. Fraudsters’ expenses go up trying to keep up, according to the report.
State agencies tend to pay claims first and attempt to recover those made in error later, when prevention is more cost effective. Forensics remain important to program integrity, but so too is a central repository of transactions.
The New Mexico Department of Workforce Solutions oversees unemployment insurance for the state and noticed it loses millions of dollars in improper payments annually, despite its electronic filing system. Applicants exaggerating claims account for most errors, per the report, so the agency tried A/B testing to develop questions more likely to solicit accurate answers from beneficiaries:
NMDWS found that targeted behavioral techniques applied at key moments effectively reduced improper payments. For example, claimants who receive a tailored pop-up message such as “Nine out of 10 people in your county accurately report earnings each week” are nearly twice as likely to self-report earnings. This directly translates to substantially lower improper payments.
The more complex a system, like Medicaid, the greater the need for collective intelligence to reduce abuses. Tennessee’s Medicaid program, TennCare, has its managed care organizations run private audits and then cross-references them to flag health providers under investigation by multiple anti-fraud units, for instance.
“Partnering with the MCOs to reduce fraud was critical to the results,” Dennis Garvey, TennCare program integrity director, told Deloitte University Press.
But states must be willing to go toe-to-toe with providers.
The full report, complete with a detailed roadmap to improving program integrity, can be read here.
Dave Nyczepir is a News Editor at Government Executive’s Route Fifty.
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