Predict, Prevent, Protect
The increased availability of data today provides a great opportunity to use analytics. As such, human services IT systems are collecting greater amounts of electronic data with interfaces to external information sources. By capitalizing on available public- and private-sector data and advances in technology, human services organizations can better understand the characteristics and motivations of different client types and quickly tailor their responses.
The right application of analytics-driven compliance can help human services organizations:
Spot problems. By applying a predictive analytics lens across compliance activities, organizations identify high-risk and potentially erroneous or fraudulent claims at speed, and can focus on those clients and interactions that require the most attention.
Focus efforts. Continuous measurement, monitoring and review of client behavior patterns and the predictive models help determine the right strategies and resource allocation, matching the organization’s response to the needs of its clients.
Cut costs. Organizations can generate savings quickly through technology accelerators and real-time analytic data management. Leading human services agencies using predictive analytics are realizing more than 200 percent lift in their return on investment.
Boost business results. Predictive analytics can identify changing client behaviors and needs, giving organizations key information to enhance value and improve business results. Human services organizations using analytics are experiencing improved program integrity, leading to program savings of approximately 4 percent from the prevention of overpayments and erroneous payments.
Enhance quality of service. Predictive analytics enable organizations to proactively differentiate their response and service to clients.
Assess and adapt. The right compliance framework can help organizations assess the quality and fitness of any existing models, rules and analytic data, and augment current models to address other areas of concern, such as case selection criteria, identity theft and fraud.
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