| ActionOptimizer™ for Treatment Management |
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Optimize treatment decisions at the account level.
![]() ActionOptimizer for Treatment Management ("ActionSelect") is a predictive analytic solution that goes beyond just behavior scores and segment level strategies - it uses action scoring, advanced decisioning, optimization and simulation to predict a response to a set of actions, improving customer interactions that drive to a new level of efficiency and profitability. Action scoring leverages traditional, non-traditional and activity data sources to provide a true, multi-dimension view of a customer’s response to any given action or treatment. Using this information, ActionSelect uses rules and optimization to ensure the best action for each account is selected while considering the organization’s overall business objectives and resource constraints. Finally, champion/challenger and simulation are used to create and test strategies before implementation. This process decreases the time to production from months or years to just days. As a result, organizations can predict with much greater accuracy which actions will produce the most profitable treatment path to maximize your account management efforts. Fast answers to tough questionsBacked by proprietary predictive analytics, the ability to run multiple strategies simultaneously, and a user-friendly interface, ActionSelect can quickly determine:
With ActionSelect, organizations can predict a customer’s response to specific actions at the account level, increasing success and providing a powerful alternative to business-as-usual. BenefitsFrom activation and balance build, retention, credit line management and finally in collections, ActionSelect provides organizations with the ability to:
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ActionSelect allows us to precisely segment our early-stage delinquencies and identify which customers will pay without action, we can significantly reduce unnecessary phone calls to customers who have missed a payment in the past 30 days, but who are likely to pay without a call. 