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<\/a>\nWith claims environments exceedingly complex, MEMIC\u2019s team felt that its conventional reserving approaches, while effective, had room to become more precise \u2013 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.<\/p>
\nGradient AI\u2019s 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 \u2013 including underwriting, claims, and actuarial leadership \u2013 to best ensure proper evaluation of the solution\u2019s value propositions. Throughout the effort, both companies maintained a commitment to developing operationalizing solutions that consistently align with MEMIC\u2019s needs and strategic goals.<\/p>
\n\u201cOur shared goal was to incorporate our Total Incurred Prediction solution not as a mere \u2018model delivery,\u2019 but something that binds and underpins various aspects of MEMIC\u2019s workers\u2019 comp claims assessment strategies,\" said Stan Smith, CEO of Gradient AI. \u201cThis thoughtful, collaborative approaches has helped MEMIC steadily build value via the TIP model even while it maintains its day-to-day focus on execution. This type of organic, perpetual improvement-minded launch approach helps ease the transition through both continuity and continued progress.\u201d<\/p>
\nOne area of particular focus was gauging potential under- or over-served claims as they relate to the National Council on Compensation Insurance (NCCI) Experience Modifications. Also known as X Mods, the calculations are a key aspect of determining pricing strategies for workers\u2019 comp coverage.<\/p>
\n\u201cWe went live with this enhanced process in May 2025,\u201d said Matt Harmon, Senior Vice President of Claims for the MEMIC Group. \u201cA six\u2011month post\u2011implementation study demonstrated that reserve adjustments driven by TIP insights resulted in more timely updates to X Mods and improved accuracy in experience\u2011based policy pricing at renewal.\u201d<\/p>
\nBeyond the initial objective, MEMIC Group identified several additional use cases for the TIP model across multiple functional areas. These include evaluating open claims at the individual policy level when an account leaves MEMIC, toward the goal of estimating future claim costs and profitability; analyzing claims within a policy to identify potential future development and inform renewal pricing strategies; and assessing claims associated with catastrophic loss events to provide earlier estimates of ultimate loss severity. The tools also review open claims across multiple policies when evaluating potential commutations or settlements with reinsurers for a specific accident year.<\/p>
\nFrom an underwriting standpoint, MEMIC also has benefitted from earlier evidence of favorable trends in X Mods, and stronger alignment between claims outcomes and underwriting results. In its totality, the Gradient AI\u2019s TIP model meaningfully contributed to MEMIC\u2019s revenue growth in the first quarter of this year.<\/p>
\nFor MEMIC, the TIP model also is paying dividends at the organizational and change management levels. By embedding predictive analytics into daily decision-making, the solution supports a more proactive, data-driven culture that helps distinguish MEMIC from many competitors.<\/p>
\n\u201cImproved reserve accuracy has given MEMIC underwriters greater confidence in renewal pricing decisions,\u201d said Harmon. \u201cIn many cases, this has supported more appropriate premium levels that more accurately reflect underlying risk. These changes have had a favorable impact on both revenue and overall profitability, while supporting fair and transparent pricing for customers.\u201d<\/p>
\nAbout Gradient AI<\/b><\/p>
\nGradient AI is a leading provider of proven artificial intelligence (AI) solutions for the insurance industry. Its full-cycle platform improves loss ratios and profitability by predicting underwriting and claim risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation.<\/p>
\nUnlike other solutions that use a limited claims and underwriting dataset, Gradient AI\u2019s software-as-a-service (SaaS) platform leverages a vast industry data lake comprising tens of millions of policies and claims. It also incorporates numerous other features including economic, health, geographic, and demographic information. Customers include some of the most recognized insurance carriers, MGAs, MGUs, TPAs, risk pools, PEOs, and large self-insured employers across all major lines of insurance. By using Gradient AI's solutions, insurers of all types achieve a better return on risk. To learn more about Gradient AI, visit: www.gradientai.com<\/b><\/a> or follow on LinkedIn<\/b><\/a>.<\/p> \nAbout The MEMIC Group<\/b><\/p> \nThe MEMIC Group includes MEMIC Indemnity Company, MEMIC Casualty Company, and its parent company, Maine Employers' Mutual Insurance Company. All companies are rated \"A\" (Excellent) by A.M. Best for financial strength and stability.<\/p> \nMEMIC is licensed to write workers' compensation coverage across all 50 states. They partner with more than 22,000 employers and support approximately 1 million of their employees through proactive safety services and compassionate injury management. Their teams are committed to helping workplaces thrive, from Maine to Florida and beyond.<\/p> \nIn January 2026, The MEMIC Group acquired The Dakota Group\u00ae<\/sup> including Risk Administration Services Inc. For more information, visit www.memic.com<\/a>.<\/p>