When we think about the phrase, Big Data, we sometimes think of another phrase: herding cats. With no disrespect intended toward our feline friends, they’re not the most manageable species in volume. The same can be said of data. While each datum doesn’t have a mind of its own like each cat does, managing data — to say nothing of taming it — can be particularly challenging. And when it comes to claims data, things can only get worse. Here’s why:
Technology begets data. Data begets more technology. So, we have the Internet yielding data. (Hello, IoT.) The IoT begets telematics. Telematics begets more data. That data provides information about the behavior of insured drivers, including the speeds at which and the conditions in which they drive. The good news is all that information can help personalize coverage pricing. (Happy underwriting manager.) The bad news is all that data and information has to be managed. (Freaked-out claims manager.) Aye, there’s the rub.
Given the challenges faced by the freaked-out claims manager (or self-insured group or TPA), we started thinking about how cool it would be if there were a claims-management system that featured incident-based management; logical screen arrangements; workflows; reminders for appointments, phone calls, court appearances, and due dates; reporting; and analytics.
More important, we daydreamed about a system that eliminated network folders and files (to say nothing of paper — organizing information by particular types of documents; enabling image files, videos, PDFs, and other file formats to be attached to each incident; and an activity log to track notes and actions taken, with reminders for upcoming due dates. After we got that far, we thought we might as well imagine a system that connects claims to policies, enables you to run reports by policy and policy period, and makes every change made by anyone, by the dates they’re made completely transparent and auditable.
Then we got completely carried away and fantasized about a system that would run reports run by user-determined filters — claim handlers, claims paid by amounts, dates, policy numbers, totals incurred, and more — that don’t require SQL or Boolean logic, all of which can be exported to Excel. We mused about dashboards that show types of accidents, incidents and frequency of particular types of accidents, claims for particular incidents by various time period, causes of those incidents, their costs, and more. We envisioned breadcrumbs to allow users to find their way back through the system and a Global Search that allows them to search the entire system, by incident or claim numbers, payment and payment amounts, dates and date ranges, times, locations, names — even down to the level of specific words.
We Didn’t Even Yawn
Finally, we went all out and spitballed a system that tracks salvage, recoveries, subrogation, various parties to incidents (drivers, passengers, adverse drivers, witnesses, pedestrians, attorneys), claims by type, vehicles, road conditions, types of injuries, wage details, and more, as well as completely customizable tags and drop-downs.
We were pretty tired after conjuring a system like this. But we had enough energy left to build it.