Streamlining processes, fraud detection and other uses for AI in insurance

How insurers use AI to improve their practices

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The artificial intelligence revolution has changed the insurance industry, with insurers utilizing AI to streamline processes including claims, as well as to combat fraud.

There's clearly room for AI to help with insurers' operations. Capgemini research shows that underwriters spend 41% to 43% of their time completing administrative tasks, such as data entry and record keeping. This means that more time is spent on these manual processes than on core activities; only a third, 32% to 33%, of underwriters' time is spent on essential responsibilities like risk assessment and premium calculation, and 25% to 26% is allotted to agent-broker collaboration and sales activities.

Organizations that implemented AI, including automated and data-driven underwriting decision-making, show significant gains in speed, reduced expenses and improved target achievement when compared to other insurers, according to Capgemini. These insurers also see improvement in fraud detection and managing the costs of losses.

"One of the things that technology like artificial intelligence is doing is democratizing some of this knowledge," Caroline Bedford, chief executive at EDII, said on an In Send webinar. "Clearly, human skills, emotional intelligence and face-to-face relationships are indispensable. Absolutely. But we now have really great language models that can be specific to your organization, that can share knowledge with graduates or with people who are building experience."

AI-powered predictive models using photos of damage details from claims can predict losses more accurately and consistently, according to Don Jones, senior vice president, claims design and delivery at Allstate. For auto claims, this allows carriers to "get our customers back on the road faster, in terms of faster cycle times, more efficient processes, and making sure that we're accurately managing their claim," he added.

AI can help detect fraud in insurance, but this same technology can be used against insurers to submit fraudulent claims. Rather than using Gen AI to manipulate damage photos for claims, a bigger issue is its use for false identification of policyholders making claims. Synthetic IDs, which are fabricated identities that are not based on real people, are being used to make claims, Karen Jennings, a special investigations unit manager at American Family Insurance, told Digital Insurance's Michael Shashoua.

"They're misrepresenting their information to the insurance company to take out a policy, and then from there, depending on the carrier, either the claim is paid or they catch the red flags that it's not an actual person," Jennings said. "Each case is a different scenario."

Read more about how the insurance industry is utilizing AI.

How insurers are using Gen AI to fight fraud

Catching fraud requires a workflow that includes machine learning, predictive modeling and rules engines, Kimberly Harris-Ferrante, distinguished vice president and analyst at Gartner, told Digital Insurance's Michael Shashoua. Gen AI is useful because, she says, "you're going to package multiple technologies to do the analysis, the workflow, the decision mean, the calculation of risk. And because these technologies are new, they're more simplistic in how they're being spun in the industry."

Insurers are becoming more concerned about gen AI being applied to create fake images or content that can be used in claims, but their use of technology still has to catch up, according to Harris-Ferrante.

"A lot of insurance companies don't have modern fraud solutions. They're not running these state-of-the-art AI-based fraud solutions," she said. "Mainstream insurance companies are still running some rules that a special investigation unit built, that could be running internally. We haven't seen any best in class yet."

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Insurers look to Gen AI to block bad actors who use it for fraud

Hareem Naveed of Munich Re discusses ethical AI in life insurance

Hareem Naveed, associate vice president of integrated analytics at Munich Re Life, has a background in data science for social good. She received a degree in math and her fellowship and training were in data science applications for social good use cases at the University of Chicago.

On preventing bias in their models, Naveed told Digital Insurance's Kaitlyn Mattson: "We have a cross disciplinary team that includes people from risk management, legal, the business product owner and data scientists, and they just ask the right questions; no one's going to say, 'you can't do that because this is risky.' They're gonna say, 'Do you have the right controls? Did you review the documentation? Did you review the agreement?' That's the first place to start."

"Then when it comes to bias detection and mitigation, one of the things that we do is we think about the intervention," Naveed added. "The reason I mentioned scope is important is because nobody should be building a model just for the sake of it as an intellectual exercise, right?"

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Ethical AI in life insurance, Hareem Naveed of Munich Re

AI as an educational tool for underwriting

Forty-five percent of commercial and personal underwriters struggle to meet broker and customer expectations, according to Capgemini's 2024 World Property and Casualty Insurance Report, and manual processes and time-consuming tasks are significantly impacting underwriting efficiency.

In Send's webinar, "Finding, and keeping, the best underwriting talent", industry experts discussed the challenges and opportunities of managing talent in an industry preparing the next generation of the insurance workforce.

"In our community, we know that the best underwriting talent wants to ensure that they're joining a company that's future-focused, using the latest technology, working with the best partners and is able to provide all the tools and techniques that they're going to need," Caroline Bedford, chief executive at EDII, said on the panel.

Read more:

Can gen AI teach the next generation of underwriters?

Insurance agent takes pictures of damage to car after accident on smartphone

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How AI can benefit insurers and the insured

AI is an opportunity for the insurance industry to change everything from sales and retention to claims and underwriting, according to Don Jones, senior vice president of claims design and delivery at Allstate.

The insurer is focused on re-platforming systems to bring new products to market faster, he said, "and create consistently great experiences for our customers that are affordable, simple and connected." That means enabling customers to do a lot on their own, including choosing products, changing policies and filing claims.

To accomplish this, insurers have to show their employees that AI will enhance their careers through upskilling, Gwen Larkin, director of claims operations at American Family Insurance Group, told Digital Insurance's Michael Shashoua. This means giving them a stake in the changes AI will create, by letting them test its functions before implementation.

"That's part of what we've done at our company, really giving them this thing that we're introducing and letting them just play with it," she said. "How would they use it to enhance day to day work? So it feels less forced on them."

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AI impacts claims for insureds and insurers alike

Businessman with protective gesture and car, family, life, trave

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Using AI to enhance the insurance claims process

Integrating artificial intelligence directly into insurance claims processing is improving the industry's predictive analytics capabilities and ability to apply predictive models to processing claims, helping reduce the costs of claims and making it easier to apply staff resources, carriers' claims technology executives say.

"AI and its analysis of the data and its ability to identify patterns, can begin to judge sentiment across all the parties to a claim," Shawn Crawley, chief operation officer, American claims at Sompo International, told Digital Insurance's Michael Shashoua. This means detecting a claim's severity, possibility for litigation, or possibility of fraud, Crawley explained.

AI can analyze claims trends and data, supporting informed, data-driven decisions, according to Don Jones, senior vice president, claims design and delivery at Allstate. He cited handling of first notice of loss (FNOL) as an example.

Read more:

AI predictive capabilities find applications in insurance claims