Mitchell has launched Mitchell WorkCenter Assisted Review, the first integrated workflow solution to leverage artificial intelligence for the estimate review process.
By using visual computing to analyze photos, the solution uses machine-learning technology to help identify incorrect replace or repair decisions, helping insurance companies review more estimates in less time while refining estimating guidelines and consistency.
“Mitchell is extremely proud to announce the availability of Mitchell WorkCenter Assisted Review,” said Debbie Day, executive vice president and general manager for Mitchell Auto Physical Damage Solutions. “We are committed to helping our customers increase efficiencies and reduce costs. In less than a year after we first announced our assisted review project with Tractable, Ltd., we have developed an integrated artificial intelligence solution that will help to save thousands of hours of review time while leading to more accurate and consistent estimates.”
By reviewing millions of damaged vehicle photos, computers are trained to recognize vehicle damage and use computer vision to double-check repair vs. replace decisions. Mitchell WorkCenter Assisted Review uses this technology to quickly identify estimates that are potentially inaccurate, allowing carriers to more easily maintain estimate quality and consistency, be more selective about sending appraisers into the field, and improve cycle times and productivity.
“Early pilot tests demonstrated that A.I.-identified claims consistently reduced the amount of time for the audit and review function per claim by a substantial margin,” said Olivier Baudoux, vice president, Product Management and Strategy for Mitchell Auto Physical Damage Solutions. “WorkCenter Assisted Review is designed to provide insurers with a more targeted and efficient review of all claims.”
Mitchell WorkCenter Assisted Review helps insurers:
- Increase the volume and accuracy of claims review with little to no increase to review resources
- Improve claims outcomes by improving workflow, accuracy and cycle times
- Increase operational efficiency by improving and maintaining review accuracy even as claims volume increases
- Instill confidence in estimating with artificial intelligence technology with increasing consistency over time
- Better inform estimating rules with analytics gained from consistent estimate reviews
- Save reviewer time by identifying potential repair or replace errors
