In general, there are three types of insurance claims:

  1. Simple, low-risk claims that can be handled by an automated system or by straight-through processing (e.g., a routine fender bender).
  2. Complex claims that are unexpectedly severe, have high indemnity or involve personal injury. These types of claims require a lot of attention from an adjuster and regular monitoring in order to resolve them.
  3. Claims that look like (1) but end up being like (2). In layman’s terms, “claims that explode.”

Getting in front of claims that explode

Claims that explode are inherently problematic, and even more so because they tend to emerge after a claim has stagnated for some time. From there, it’s a matter of trying to get off the back foot and mitigate any further risks, while also trying to resolve the claim expeditiously.

Predictive analytics can help mitigate these cases. First, insurers can leverage a model that examines an insurer’s database of claims closed in the past few years, and identifies common characteristics of claims that have exploded. Next, insurers can apply those characteristics (or combination of characteristics) to a new analytical model and scan existing claims for warning signs. By running the analytical model on a regular basis, insurers can identify claims that are likely to explode—while there’s still time to take action.

Having identified claims that are likely to explode, insurers can take immediate action to contain them, such as reassigning the claim to another handler, bringing in corporate intervention or defense counsel, applying specialized claim handling protocols and more.

In addition to getting in front of claims that explode, claims analytics can help insurers identify the action best suited to moving a claim forward. Join me next week as I discuss “claims like these” capabilities.

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