The conversation around subrogation has been changing. More insurers have begun to realize that subrogation increases the bottom line, lowering loss ratios and increasing revenue. In addition, a company that successfully handles subrogation will enjoy happier customers and increased retention.
The downside from this increased emphasis is that many insurers who are now interested in subrogation are learning that they don’t have the capacity to do it. Their legacy claims platforms don’t have the features, data, or integration necessary to perform subrogation in an efficient or scalable manner.
What’s the problem with legacy platforms?
Back when insurers adopted the systems that they’re currently using, many of them simply didn’t care as much about subrogation. So, part of the reason that insurers can’t perform subrogation as efficiently now is that their existing platforms don’t have fields designed to capture that information.
Without fields designed to capture subrogation data, claims adjusters will usually add their own notes – either as a comment on the case file or an actual handwritten note. Subrogation professionals then need to perform a process often known as “swivel chair input.” Here, they manually read another claims adjuster’s notes and then copy-paste or physically type them into their own platforms.
There are problems with swivel chair input. First, it takes the work of a skilled professional and adds a significant amount of basic data entry. Not good for employee morale. Second, it’s slow – in many cases as slow as an employee can type. Lastly, the process is open to errors when an employee makes a spelling mistake or pastes the wrong information to the wrong form. This can have a negative impact on the outcome of a claim.
Legacy subrogation platforms resist automation and artificial intelligence
The problems that make subrogation difficult for human employees also make subrogation difficult to automate.
One solution might be to set up a basic RPA process that grabs information from the claims platform and automatically drops it into the subrogation platform. Alternatively, employers could build an API bridge to do the same thing.
Here are a few problems with this approach:
Lastly, insurers could attempt to solve this problem on their own using AI, but here they fall into a different trap. Because they don’t have years of historical data in analytics-ready format, it becomes incredibly difficult to train an AI that handles even simple subrogation cases on its own.
How does Shift Technology solve subrogation with artificial intelligence?
Shift Technology has figured out a few ways to automate subrogation, resulting in better accuracy, higher revenue, and greater customer satisfaction.
First, we have been able to solve the historical data problem. We’ve gone beyond RPA and optical character recognition (OCR) to achieve natural language processing specialized for insurance documents. This means that we can automatically parse typed or handwritten notes from your claims adjusters – going back years and years – and turn them into analytics-ready subrogation data.
Second, our platform performs deep analytics on its own, automatically scoring cases on their suitability for subrogation and surfacing the best opportunities. This means that subrogation professionals just need to open their dashboard and they’ll automatically find a menu of high-scoring cases. From there, they can double-check to confirm the solution’s analytics and then take the recommended action, often with just a single click.
Subrogation is a difficult problem for insurers to solve on their own – but Shift Technology brings external data together with custom analytics to create a solution. With faster and more effective subrogation, insurers can boost revenue and delight customers, while leaving the shortcomings of legacy systems in the past.
For more information on subrogation and how Shift helps insurers make better decisions, request a demo today!