The pandemic restrictions left Kevin Combes and his team at Aon with time on their hands, but they didn’t want to just sit around twiddling their thumbs and instead looked for areas in their business where they could improve on existing processes.
After a bit of initial collective thinking they finally settled on trying to innovate and reinvent the claims review process.
The initial desire to reinvent this vitally important process was born out of the team at Aon wanting to innovate at a time when work was being curtailed by the restrictions brought in to combat the Covid-19 pandemic.
Within the context of the whole market, in a single year we are talking about in excess of 70 million hours being spent on manually reviewing claims.
Combes said that the team initially came together to discuss what areas of insurance had missed out on the innovation drive that has been sweeping through the insurance industry in recent years, before they all settled on the claims review process.
“It’s a process that has never really evolved at all, and I’ve been in the insurance industry for more than a minute — it’s more than 30 years now,” he said. “And I can tell you that claim reviews today are handled exactly like they were when I was a rookie starting out.”
The first thing Combes and his team did was to sit down and assess just how much time was being spent on reviewing claims, and it is fair to say that he was staggered by the results of the research.
“Within the context of the whole market, in a single year we are talking about in excess of 70 million hours being spent on manually reviewing claims,” Combes said.
Combes was, however, confident that the amount of time spent on reviewing claims could be drastically reduced while at the same time delivering better results for clients, so his team went about interviewing and surveying clients to get to the root of the problem.
The research took in around 114 of Aon’s clients, covering every industry vertical Aon operates in as well as firms ranging from $250 million of annual revenue to $100 billion and up to get a full picture of the issues.
“We felt like we had got a pretty good insight as to the kind of value that was being delivered, and quite frankly there's a pretty big value gap from our clients’ perspective on what we've been doing,” Combes said.
Combes said that this was a “double whammy” with excessive amounts of time being spent on a process that was delivering nothing more than marginal levels of value.
Things needed to change. Drastically.
A Profound Absence of Data
Combes and his team continued to trawl through the client feedback to find a solution, and the first thing that stood out was a lack of data and insight.
“There was a profound absence of data and analytics strategies around the selection of claims that were being reviewed,” Combes said. “So if a client was driven primarily by financial motives, and they were reviewing claims specifically to address financial concerns, we should be looking at the data to highlight those outlier claims that may be coming off the rail that potentially could play substantially into much more severe costs.”
Ultimately, the results of the survey and interviews highlighted three key motives as to why a client might want to review a claim: financial, operational, or administrative.
Once Combes and his team had found this spark of inspiration, they set about creating a tool that could deliver the insights needed to better select claims that fitted into these three key review areas.
This was complicated work that needed to take in the idiosyncrasies of not only individual business lines, but also all of the different regions around the world in which Aon and its clients operates.
It soon became clear to Combes that there was a further issue they would need to resolve — a fundamental lack of best practice guidance across the whole of the industry.
“That ranged from everything from we don't like the way adjusters simply replay status reports back to us all the way up to we don't like the preparation, we don't like the manner in which it was conducted, we don't like the deliverables,” Combes said. “There was a whole litany of things that were problematic, but to which there was never any unified set of best practices to guide better behaviour.”
To combat this, Combes started working with 17 of the largest carriers in the P&C market space and the biggest third-party administrators globally to help come up with a unified set of best practices Aon could use with their clients.
The curation of all this information took course over the course of two months and was collected using a dedicated website where everyone involved in the project was able to collaborate collectively.
This led to Combes coming up with a three-stage set of best practices for the claims review process.
The first stage centred around the beginning of the process, and focused on gaining a clear understanding of the client’s objective for reviewing a claim, something that Combes said was vital for extracting more value out of the review process.
“If we don't understand what the client's objective is, then there's little chance that we're actually going to be working to help them succeed with that objective,” he said. “That level of understanding is a critical first step.”
The second stage of Combes’s three-step best practice guide is the process for selecting the claims that will be reviewed, before finally moving on to the actual review itself.
The importance of these final two stages centred around effectively selecting the right claims based on the key objective of the client — whether that be financial, operational or administrative — and then improving the efficiency of the process by removing steps that were not focused on this objective and therefore had no material impact on the outcome of the review.
Building for the Future
Since establishing these best practice guides, Combe’s has spent the better part of nine months directing a team to build a data tool that can help put these ideals into practice.
Combes said that the aim of this technology is to help Aon’s claims review teams to perform better in three key areas: isolating data that can improve alignment with the client’s objectives when selecting claims for review, capturing additional data so that Aon can better advocate on behalf of its clients, and building a backend so that all this data can be plugged into the review itself.
Artificial intelligence is a key component of this tool, which is currently in user testing at Aon, and Combes said that the insight delivered by these algorithms can help improve the overall decision-making process.
“I would say that 80% to 85% of the time, the selection criteria that our clients use to conduct claim reviews are very arbitrary,” Combes said. “So they might be based around some kind of financial threshold such as reviewing all open claims where the incurred value is greater than $50,000.
“I've argued for years that that's a mistake, because you can make a couple reasonable assumptions about large claims without getting yourself in too much trouble. One is that the more expensive claims are going to be handled by a higher calibre technician to start with, so you should have more comfort that that claim is probably okay.”
Aon’s new tool will remove the arbitrary nature of such claims selection and add an additional layer of intelligence to the process.
“This new tool is able to conduct a very quick severity analysis, then apply some machine learning algorithms that are going to speak to the predicted severity of any claim,” Combes said. “As soon as soon as the application has a chance to adjust the data, then the model is going to tell us, hey, of these 500 open claims, these 50 claims are likely to be significantly more severe than the incurred values presently set.
“That gives us much better control over what gets sent to a client and how we're articulating value to that client.”
“The primary benefit of this project has always been about improving the outcomes for our clients,” Combes added.
