Pricing and claims feedback cycle

One of the most frustrating situations for insurance claims teams at present is the inability for their repair network to source replacement parts in a timely manner. This has a big impact on the cost of managing that claim, with the length of time a replacement vehicle is provided one of the major factors.

There's only so much insurance pricing teams can do to model this increase in cost. Price increases due to inflation are a blunt tool, and not always applicable. Whilst ML techniques have become almost unbelievable accurate (we can build market models that predict 1/5th of the customer base to within 1% of their actual price) they still lack the specificity and knowledge that claims teams can provide. Models can only be trained on historic data, and any sudden change in the landscape can never be predicted.

The link between pricing and claims teams has never been more important, but it is one area we regularly see a disconnect. If the claims team understands that parts for popular models of cars are hard to source then why is the pricing team not reacting to this information? Better communication could have resulted in better responses - for both the company and their customers.

For example temporarily suspending making sales to new customers of a popular but hard to source car model would ease the supply burden on existing customers. Their claims would be quicker and cheaper to service, meaning that you don't have to increase prices as much to cover the additional cost of a vehicle waiting for parts to be replaced. You lose some sales you would have made a loss on, and the customers get lower prices and a better claims experience.

So a question to my colleagues in pricing and claims teams - what would you like to see improved in how you work together? Maybe you have faced some problems in the past that are starting to happen again? Also will I ever be able to get midjourney to create pictures of people with the right number of fingers?


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