At Sprout.ai, we are proud to work alongside many of the world’s leading insurance providers, using our proprietary solutions to make real changes that benefit both our clients and their millions of customers. One thing we’ve noticed is that providers in diverse parts of the world face challenges that seem quite different at first glance. But often, they come down to the same root causes. Two recent projects, with clients in Chile and Japan, have brought this into sharp focus.
Tackling spiralling costs for a health insurance provider in Chile
The first project was with one of the leading health insurance providers in Latin America a business that processes more than a million claims every year. The company called us in to help them address two different but related challenges. The first was that claims processing costs were going through the roof. The second was that claims handlers were spending so much of their time on data entry that there was practically no opportunity for them to do anything else.
Our client was effectively treading water to process claims as quickly as possible. This constrained its ability to devote sufficient resources to activities like fraud detection and prevention. The result? Spiralling costs and ever-longer processing times.
Sprout.ai built a Straight Through Processing solution based on OCR and NLP technology to read claims data. We then trained it using historic claims data. This had the immediate effect of freeing up time for claims handlers to focus on the insights drawn out by the tool instead of being buried in repetitive data entry work. At the conclusion of the pilot, accuracy was at 97-99 percent (compared to the industry standard of 80 percent), while 70 percent more fraudulent claims were detected.
Reducing processing time for one of the largest insurers in Japan
Meanwhile, almost 11,000 miles away, we had a team working on a pilot project with a client in Japan. Here, the business’s new bespoke healthcare offering had resulted in a sharp increase in processing times due to its complexity – there were hundreds of different policy variations, exclusions and so on. The result was an average processing time of 30 days – 20 of which were being spent on data entry.
While the challenges here looked very different to those faced in Chile, the solution, once again, lay in automating a straight though processing solution to reduce the time being spent on data entry. Setting up the solution meant some late nights with teams from client and Sprout.ai working together to consolidate the necessary training data to get the pilot underway. But the results were certainly worth the effort.
Processing times were reduced by 90 percent to an average 2-3 days, while our client also observed significant cost reduction. All this came with no impact at all on accuracy, which at 96 percent was above average human levels.
Diverse problems, a single solution
The global insurance market faces a whole host of challenges, especially in these unusual times. Sprout.ai’s automation processes can contribute significantly to solving a range of these problems, increasing efficiency, reducing costs and allowing human experts to step away from the repetitive admin task and use their knowledge and experience to add real value.