Claims talent spread thin? No worries: digitize your claims triage

With talent spread thin in greying claims departments, insurers are looking to use AI to help digitize their claims triage process and other workflows.

Officially, it’s called “intelligent process automation” (IPA),” a combination of workflow processes, automation and artificial intelligence (AI) or machine learning.

Currently, IPA is able to learn from a company’s processes, rules and claims patterns to direct specific claims to an adjuster who has the most experience, skills or talent in that same area. “In any organization, there will be adjusters with different skills sets and experience that can handle certain types of claim files more efficiently, depending upon what the injury or claim profile may be,” explains Mathew Raymond, founder of Expeflow, a cloud-based, centrally-administered claims management platform for medical and healthcare claims.

Raymond cites an example drawn from Health Claims for Auto Insurance (HCAI), an electronic system for transmitting auto insurance claim forms between insurers and health care facilities in Ontario. In Ontario, third-party health care providers are required by law to submit their treatment plans for insurance claims to HCAI.

“We have all of these injury codes coming in from HCAI that have been entered into the insurer’s file,” as Raymond explains. “We know the demographics of the adjuster and the claimant; now you can learn which adjuster is handling which types of files, depending on the type of the insurance policy. IPA can help insurers direct the right file to the right adjuster. Maybe you have a claimant come in and an emotional impairment is an aspect of the file. That can now be handled by someone who has more experience with those types of claims.”

The AI component of the process takes IPA far beyond the realm of simple process automation, according to Expeflow CEO Terry Stepien.

In simple process automation, an insurer might hive off a portion of the claims process – a form collecting data on first notice of loss, for example – and then completely automate the process for collecting the data. No one in the company touches the form during the process, and the information gets processed very quickly.

The next step up is for the insurer to map out its workflows, identifying who does what. Essentially, the knowledge transfer from senior to junior adjusters is then digitized. “You’ve put the sequence of steps in that the [senior adjusters] may have had in their head,” as Stepien explains. “You’ve captured some of that knowledge and institutionalized it in the insurer, and now you can have more consistency across the force.”

At that point, the true value of AI is brought to bear.

“Once you have the information [related to businesses processes] in place, the system can start suggesting things to you that you may not have thought of,” says Stepien. “The system can start tracking best practices. It may say, ‘In other situations like this, you’ve done this with a person,’ or ‘This is the kind of question that you [as an adjuster] might ask.’ So, as an adjuster, you can see what’s coming next and start to get ahead of it.

“The real benefit of artificial intelligence here is being able to look at all of that knowledge you have, and based on the rules you give it, the system can say, ‘Here is the information that may be relevant to what you are looking at today,’ as opposed to the adjuster trying to find the little missing nugget in a vast sea of information.”