Solution to Brain Drain in Insurance?

What was once science fiction is fast becoming a fact of today’s business world. Computers that mimic the human brain are already entering the workforce in the healthcare, financial services and retail sectors, among others. Like humans, cognitive analytic computers can understand “natural” language (such as English) and learn lessons from the data they analyze, as well as from the users who “mentor” them. In other words, the machines possess an artificial intelligence more powerful than anything seen before. Unlike humans, cognitive analytic systems can process, analyze and store enormous volumes of data at Internet speed. In addition to tapping conventional databases for the information needed to aid in decision-making, the machines are capable of scanning myriad emails, reports, articles, books and other sources of knowledge to deliver recommendations and reach conclusions beyond the ability of any one person or team of people. In a 2014 white paper on cognitive analytics, Rajeev Ronanki and David Steier of Deloitte Consulting note that in the healthcare industry, “[cognitive analytic] systems are being used to improve the quality of patient outcomes. A wide range of structured inputs, such as claims records, patient files and outbreak statistics are coupled with unstructured inputs such as medical journals and textbooks, clinician notes and social media feeds. Patient diagnoses can incorporate new medical evidence and individual patient histories, removing economic and geographic constraints that can prevent access to leading medical knowledge.” In financial services, cognitive analytics is used to recommend and execute trades and to also assist in fraud detection and risk underwriting. Many of us are familiar with less advanced forms of cognitive analytics. In the consumer electronics realm, examples include Apple’s Siri voice recognition software and the oral command interface used in the Xbox video game system. Virtual Decision-Making Assistance It doesn’t take much imagination or intelligence (human or artificial) to envision how cognitive analytics could revolutionize auto insurance, especially the claims sector. Cognitive analytic computing could be of enormous benefit to an industry that will see fewer claims adjusters in the near future, thanks to the number of veteran adjusters who are retiring or planning to retire. Cognitive analytics could empower the remaining adjusters with decision-making assistance that was previously inconceivable – decision-making based on huge volumes of data drawn from a near-infinite pool of sources. Not long from now, computers will be able to scan photos of accident damage and instantly retrieve historical data on how similar claims were assessed and settled in the past. For example, a computer could analyze a person’s injuries relative to where they were sitting when the accident occurred and how the injury was sustained. The systems could also be used in first notice of loss (FNOL). Imagine an intelligent learning system that can reference every text related to previous claims and outcomes, as well as every law and vehicle code from all 50 states, to deliver settlement information in milliseconds. Let’s say a customer submits an FNOL. “I was in a parking lot, but when I backed out of my space I hit someone driving past.” Based on the information provided, the machine could determine liability and assign fault. It could also decide whether the claim is best processed with the help of a human adjuster or via self-service. If a customer reports an accident that leaves a small scratch on the car and no injuries, the computer would automatically send a self-service text to the claimant’s cell phone so she could take photos of the damage and transmit them back to the computer. The machine would then analyze the photos and develop an assessment. Yes, the computing system could be that advanced – so advanced that it removes much of the human element from the process. 'Brain Gain' Instead of 'Brain Drain' Many adjusters in their 50s and 60s are retiring, which means a lot of valuable expertise and experience is leaving the industry. In fact, I’m probably a member of the last generation that remembers widespread use of full-service, multi-skilled adjusters – people who know every aspect of the business. Younger adjusters frequently work in silos. These compartmentalized workers are very skilled in certain things but don’t have the “Renaissance man” backgrounds that allowed their predecessors to wear “multiple hats” when the situations called for it. Thanks to the new technology, however, the older generation’s experience and know-how doesn’t have to be lost forever. That information and wisdom can be transferred to complex cognitive computing systems that instantly retrieve the data on every one of their past settlements. This will let the remaining adjusters use the machines as virtual assistants, calling on them to provide the most logical settlement paths to the best possible outcomes. If achieving the best outcomes to claims is the goal, then cognitive computing systems will prove to be an invaluable tool. With access to a virtual universe of prior decision-making (good and bad), cognitive analytics has the potential to help adjusters find the right solution to each and every auto claims case.