From fast tracking claims to spotlighting fraud, predictive analytics continues to provide increasing value to claim operations. Predictive analytics enables companies to develop operational efficiencies, enhance customer service, and increase cash flow by maximizing recovery opportunities.

Simply stated, predictive analytics is a way to project outcomes (with a certain level of probability) based on patterns derived from historical events. A key benefit of this strategy is that it can be a one-size-fits-all application. If there is a business question to be resolved with underlying data, then predictive analytics can provide insights not previously recognized.

While fraud detection and fast tracking claims are currently the most popular applications, predictive modeling can be very useful for subrogation. For example, predictive analytics can help managers provide solutions to minimize subrogation leakage and speed up the recovery process. Before starting, however, managers should determine what functionality predictive modeling will serve. Will it be used to provide real-time guidance from the first notice of loss as a means to improve upfront subrogation reorganization? Or will it be used to uncover errors in underlying processes by identifying missed opportunities? The answer to these questions will shape the way processes should be implemented and data prepared.