Using AI for underwriters could free up to 40% of your day

"The best advantage for brokers and end clients is speed and quality"

Using AI for underwriters could free up to 40% of your day


By Desmond Devoy

This article was produced in partnership with Accenture Amazon Web Services Business Group.

Desmond Devoy, of Insurance Business, sat down with Corey Barker, managing director in Accenture’s insurance practice and leader of Accenture’s Digital Insurance Solution Centre (DISC) for North America, to discuss how AI (artificial intelligence) is transforming how underwriters do their jobs.

Imagine if you, an insurance underwriter or broker, could just plug in a program and instantly free up 40% of your day?

It may not be as simple as download-and-go, but more companies are using AI (artificial intelligence) to free up time. One of the companies bringing this AI reality to life is Amazon Web Services (AWS), which is taking part in a joint investment with Accenture on this project.

“Recently, we completed an underwriting survey with almost 500 underwriters, and we found that up to 40% of underwriters’ time is spent on non-core and administrative activities,” said Corey Barker, leader of Accenture’s asset-led transformation for insurance.

“So, ultimately, we want to be looking at how we reduce that time. We also found that underwriters do their best to try and triage the submissions that they’re receiving, but ultimately they won’t get to all of them. So, sometimes as little as 10% of the submissions that some underwriters are receiving, they’ll actually be able to respond to.”

It is not just a matter of having more time available thanks to using AI, but also using that new time better for quicker underwriting turnarounds, which, for Barker, comes down to three core things.

“One is having easier access to data. Two is how can we inform decisions to speed up the process? And three, how can we help to triage better, faster, if there are certain risks that an underwriter is not going to want to write? How do we get that back to a broker as soon as possible?” asked Barker. “The best advantage for brokers and end clients is speed and quality. And ultimately, those lead to a better customer experience.”

All of which, by his estimate, can result in a 20 to 40% reduction in turnaround time for submissions and quotes.

“What’s the main goal in what we’re doing? It’s two things – it’s speed and it’s transparency,” Barker explained.

Making the business case

There are internal and external roadblocks for any company looking to add this technology to their offices, but building trust is the first and best way to implement these changes.

“It’s really understanding or helping underwriters understand how this can help them and build that trust and then, once that trust is built, that helps with some of that change management as well,” Barker said.

Of course, there is also the business case to be made.

Part of that business case is that AI could be beneficial in adding transparency to systems.

“If we’ve got full human decision, human manual-learning, we’re more prone to errors,” he said. “If we are ingesting information automatically, some of the data capabilities and these ingestion tools now, they’ve got a 90 to 95% success rate on some of the information that they’re pulling in. So, how do we make sure that we’re making those checks? And then, also, if we’re informing decisions, how do we make sure that we’re transparent on what the factors are informing those decisions?”

Data sharing?

AI could also allow for a limited amount of information sharing.

“If a broker’s done a certain amount of work, or analysis upfront, (they) understand a little bit more about the customer,” he said. “So, how do we establish what is an appropriate amount of sharable data between brokers and carriers and create a conduit in between that network?”

He used the example of how fraud in the payments industry requires multiple actors working together.

“That took an industry to tackle that issue. Banks were working together with credit card providers. I think there is a lot we can learn from the anti-fraud industry and how we can apply that to risk underwriting,” he said. “The next logical evolution on using AI is standardizing that information that gets shared and agreeing on some basic concepts that can be used for decisioning.”

And what about the piles of old folders gathering dust in a filing cabinet? There may be some informational gold to be found in those envelopes.

“How can we leverage technology to ingest all of that, all of those documents and infuse that data? Even if it’s just a data store that’s separate to the legacy system, it reduces the amount of manual rekeying,” he explained.

Future benefits

What may have seemed like science fiction a generation ago is reality now, and so Barker wants underwriters to keep an open mind as to what the future may hold.

“What we’ve found is that the carriers will benefit, either through the capacity they’re building at that particular moment, or even just the fact that they’re building this knowledge capability that can then be built on over time, and really thinking about data as an asset,” he said.

To find out more on Accenture and Amazon Web Services’ AI program’s intersection with insurance, click on

Corey Barker is leader of Accenture’s asset-led transformation for insurance.

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