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Case study: MEMIC

Workers’ comp carrier is driving smarter claims & stronger underwriting performance with predictive analytics

The MEMIC Group is improving the accuracy and timeliness of case level reserves and enabling earlier and more targeted intervention on claims through AI

The challenge

As claims environments grow more complex, MEMIC identified an opportunity to improve:

  • Accuracy of case reserve estimates
  • Timeliness of reserving decisions
  • Alignment between claims and underwriting performance

Traditional reserving approaches, while effective, left room for greater precision and earlier insight, particularly at the individual claim level.