Memic Sees Uptick After Utilising AI Prediction Model

The word from MEMIC, after they deploy some new AI predictive tools;

The MEMIC Group, a leading workers’ compensation insurance provider focused on delivering proactive risk management and claims solutions, has experienced a marked uptick in reserving accuracy following the implementation of an AI-enabled prediction model from Gradient AI, a prominent enterprise software provider of artificial intelligence tools for the insurance industry. In the wake of a six-month implementation performance analysis, MEMIC is seeing meaningful improvements in case-level reserves and accuracy – as well as earlier, more targeted claims intervention – through Gradient AI’s Total Incurred Prediction (TIP) model.

With claims environments exceedingly complex, MEMIC’s team felt that its conventional reserving approaches, while effective, had room to become more precise – especially at the individual case level. By expanding its established relationship with Gradient AI, MEMIC sought to hone the accuracy and timeliness of reserving decisions. It also hoped to bring its claims and underwriting performance into closer alignment.

Gradient AI’s Total Incurred Prediction model leverages advanced analytics to predict the total cost of claims earlier in their lifecycle, offer data-driven guidance for adjusters, and enable more consistent and accurate reserving decisions, among other benefits. For MEMIC, Implementing the TIP model involved a measured, cross-functional approach – including underwriting, claims, and actuarial leadership – to best ensure proper evaluation of the solution’s value propositions. Throughout the effort, both companies maintained a commitment to developing operationalizing solutions that consistently align with MEMIC’s needs and strategic goals.