In a recent webinar, Niels Thoné, Co-Founder and Chief Growth Officer (CGO) of Sprout.ai (Sprout), and Joanne Richardson, former Health Director at AXA, sat down to discuss the challenges in the insurance market today, and how AI can be used to overcome these in a results-led approach.
In this blog post, we have summarised the webinar into a few key aspects.
Common goals and ongoing hurdles
It’s clear that customers, providers, and shareholders have a common objective: they all desire the best outcome in the most accurate and efficient way possible. However, at a time when customers are at their most vulnerable, they must face a process that is notorious for being clunky, outdated, and prone to errors and fraud, waste, and abuse (FWA).
Whilst simple claims may be processed very quickly, a more complex one can take up to 25 days or more to process.
Innovation is clearly a priority for the insurance industry, both in improving standards of customer service and also in providing access to digital services, such as symptom checkers and prevention of authorised push payments (APPs).
However, addressing the issues with claims is often seen to be too expensive and complicated due to the age and bespoke nature of many existing health claims systems.
Rising costs affect health insurance
Following the global pandemic, people are increasingly turning to private insurance as they realise how long the waiting lists for treatment in the state system are becoming. Now, it’s up to insurance companies to react accordingly. However, the current global crisis is fuelling inflation.
This puts pressure on claims costs, which is reflected in increasing prices. What’s more, it’s not yet clear how high medical inflation will go. Regardless, it’s clear that there’s no time to waste by waiting to see what these effects will be; this approach risks losing customers as cover becomes less affordable, or profits are reduced in what is already a low-margin business.
Insurers must find ways to reduce costs in the short term, whilst improving the processes themselves in order to make the most of the silver-lining opportunity that the pandemic has presented.
Solutions through technology
This is where groundbreaking solutions come in. According to Niels, Sprout’s ultimate goal is ‘to provide a frictionless insurance claim experience for everyone in the world’. Through a unique multi-modality use of computer vision, machine learning (ML) and natural language processing (NLP), the Sprout team have developed an AI program that can be easily implemented by top insurers.
A key reason that the claims process is so clunky is due to the sheer amount of unstructured data involved with one claim – the claims team has to sift through pages of handwritten notes and memos to process a single claim. It’s no wonder, therefore, that this can take up to 25 days. With technology, this can be reduced to three, at an accuracy rate of 96% (which is 3% greater than the human eye).
Through a combination of computer vision, ML and NLP, software programmes can extract claims data before structuring, understanding, and triaging it in a cohesive way, all whilst checking to avoid FWA.
With these solutions, insurance companies can significantly improve the experiences of their customers without changing or replacing their existing claims systems and data structures. This, on top of the superhuman levels of accuracy, is what makes such solutions so attractive to insurance companies, and why there is no excuse for being slow on the uptake of innovation from legacy systems.
On the whole, there were two main takeaways from this webinar for listeners: that health insurance providers want the claims process to be just as painless as customers do, and that tech solutions are key to bringing these processes up to date and making them easier for customers, medical providers, and insurers.