Here’s How Artificial Intelligence Is Poised to Transform Insurance Underwriting for the Better

AI is poised to take the actionability of data and the accuracy of insurance underwriting to the next level. And that’s a win for everyone.
By: | January 28, 2019 • 7 min read

The words “artificial intelligence” might make you think of movies like The Terminator. Machines that learn like humans can be a frightening thought, especially if they look like Arnold Schwarzenegger and roam through Los Angeles wearing dark sunglasses and shooting machine guns.


But in real life, artificial intelligence has far more practical applications and is poised to forever transform insurance underwriting.

Imagine workers’ comp underwriters quickly analyzing thousands of pages of medical bills and health records to predict injury risks. Imagine commercial property underwriters seamlessly incorporating external data from city governments, regulatory agencies and news sources to get a clearer picture of a risk. Imagine a shipping company that’s charged more for premiums when sailing into bad weather or hostile territory.

“Artificial intelligence will fundamentally disrupt and transform insurance underwriting,” said Ari Libarikian, senior partner at McKinsey & Company. “Carriers are now able to better predict losses, provide advice and help customers prevent risks. AI is allowing that in a much bigger way than was ever possible before.”

Experts believe AI will soon deliver more accurate risk assessments, superior customer experiences and serious cost benefits for insurers. The insurance industry is investing heavily in the technology, filing 37 percent more machine-learning patents in 2017 than 2016, according to law firm RPC.

Accenture found that 63 percent of insurance executives say the industry will be completely transformed by intelligent technologies, and 53 percent are already using them in one or more business process. The firm estimates that investments in intelligent solutions could increase annual profitability for U.S. insurers by $20 billion.

“This space is changing so quickly that any carrier trying to do it themselves is probably not going to be fully successful.” — Ari Libarikian, senior partner, McKinsey & Company

Artificial intelligence has the potential to take underwriting from a detect-and-repair mindset to a predict-and-prevent philosophy. That means fewer educated guesses, more accurate information and not only making sense of treasure troves of data but using it as a competitive advantage. The AI revolution is coming, and underwriting will never be the same.

Data, Data, Data

The incoming AI revolution is fueled by an explosion of data. Low-cost data storage on the cloud, open-source technology, digital sensors on machines and worn by workers, and the overall digitization of business processes has created a landscape where data is far more available than ever before.

From a restaurant’s health inspection performance to a factory’s OSHA violation history, an incredible amount of data is currently available to underwriters — and machine-learning technology can analyze it to find red flags and help make more accurate underwriting decisions.

“There is no industry that has more data than us, but we don’t tend to deal with it well,” said Kate Browne, senior vice president of Swiss Re Corporate Solutions and a Risk & Insurance® Risk Insider. “Human beings just don’t have the ability to deal with the massive amounts of data we are getting now. That’s the competitive advantage of AI, being able to use this data deluge to make better decisions.”

Ari Libarikian, senior partner, McKinsey & Company

All that data, analyzed by AI, will make underwriting far more accurate than it is today. Imagine life insurance underwriters automatically incorporating information about your prescription drug history, gym club memberships, shopping habits and travel plans. Or commercial property underwriters analyzing public data to learn the locations of each plant around the world, the machinery used inside, the number of workers, their skill sets and OSHA violation history.

“Based on all that, we can get a pretty good sense of the risk. Do you form a complete picture from external data alone? Probably not, but you get part of the picture and it makes a difference,” said Libarikian.

AI can also help in underwriting risks where there isn’t much history — like cyber risk or weather risks. With AI and Big Data, you can churn through billions of scenarios and make educated predictions, said John Cusano, senior managing director in Accenture’s Financial Services Management Consulting Practice.


“It would be not only great for the industry but [also] great for the world. How are we going to deal with the increasing pace of new risks?” said Cusano. “We’ve got to get better automation and intelligence on how to write insurance for unpredictable risks.”

The influx of data plus the use of AI could make the customer experience far superior, too. Expect the number of forms and questions to decrease as underwriters let machine modeling do the heavy lifting. It could bring the timeline from months to seconds for some lines of insurance.

“Do you know how easy it is to deal with Amazon? That is what this technology will let us do,” said Browne.

Will AI Replace Human Underwriters?

The use of AI certainly comes with concerns. Companies using external data need to comply with privacy and regulatory rules. Still, in many cases, customers will offer information if it leads to more value, said Libarikian.

“They’re willing to sign away information about their gym membership knowing they’ll get a 10 percent reduction in premiums,” he said.

Another concern is computer system malfunctions. But Cusano said machine learning will likely lead to less danger in the long run.

“It would be not only great for the industry but [also] great for the world. How are we going to deal with the increasing pace of new risks? We’ve got to get better automation and intelligence on how to write insurance for unpredictable risks.” John Cusano, senior managing director, financial services management consulting practice, Accenture

“What’s more likely to miss something, a machine or a human, when you’re talking about millions of data points?” he said. “With all the data proliferation, if you’re not using machines, how are you really going to keep up and stay relevant?”

Despite experts’ confidence in AI, they don’t expect human underwriters to simply go away.

“You’ll still need human beings to apply judgment for complex cases,” said Libarikian, who expects the underwriting profession to soon incorporate far more data-science expertise.

Cusano agreed in part, saying that very structured lines like automobile underwriting can rely heavily on rules engines to make decisions, but agreed further that other lines will still need human interaction.

“For property and casualty underwriting, it’s a lot more complex, especially as you get into large property and large commercial where the machines are part of the process and slowly nipping away at some of the decision making,” said Cusano.

Tony Boobier, an independent consultant and author of Analytics for Insurance: The Real Business of Big Data, also said human underwriters aren’t going anywhere, especially those dealing with more complex or specialty lines.

“Maybe we need to think of it in a different way,” he said. “Imagine a profession called the ‘digital underwriter’ that works alongside expert AI systems to ensure all risks are accurately measured and priced.”

How to Prepare for the AI Revolution

The entire industry needs to get educated about artificial intelligence so they can be a part of defining the future, rather than leaving it in the hands of technology vendors — or simply losing out to more progressive competitors. One thing is crystal clear: Underwriters of the future will need data-science skills, and executives will need an open mind.

Kate Browne, SVP, Swiss Re Corporate Solutions

“As underwriters increasingly interact with automated AI systems, there will be a need for new skill sets to develop, such as open-mindedness and mental agility. And some of the old skills might become obsolete,” said Boobier.

“I think we can do this in a constructively critical way, rather than being negative about it. But at least we have the chance at this relatively early stage to contribute to the discussion and form it in the way we think best, rather than complain about it afterwards.”

Smart insurers are already creating chief analytics officer positions, buying more and more external data and building proprietary models. And they’re not going it alone. They’re working with tech startups that specialize in AI.

“This space [is] changing so quickly that any carrier trying to do it themselves is probably not going to be fully successful,” said Libarikian. “As a carrier you’re going to need to form an ecosystem of capabilities — some internal and some external.”

Another big need is getting people comfortable with changing their day-to-day workflows.


“People have been doing their job one way for years or decades and now they need to do things differently,” said Libarikian. “That’s the No. 1 roadblock to carriers capturing full value of this new technology. It’s not the science, it’s the human change management side of things.”

Libarikian suggests that carriers start small. Take one or two use cases and deliver them end-to-end. If it’s property insurance, get the data, build the model, get your executives on board and start to show real value. Then expand.

“Companies get in trouble when they try to take on too much too soon,” said Libarikian. “If you don’t deliver on the first opportunities really well, people come out of the woodwork and say, ‘I told you so, this stuff is all snake oil’ and then you lose the momentum in the organization.” &

Jared Shelly is a journalist based in Philadelphia. He can be reached at [email protected]

4 Companies That Rocked It by Treating Injured Workers as Equals; Not Adversaries

The 2018 Teddy Award winners built their programs around people, not claims, and offer proof that a worker-centric approach is a smarter way to operate.
By: | October 30, 2018 • 3 min read

Across the workers’ compensation industry, the concept of a worker advocacy model has been around for a while, but has only seen notable adoption in recent years.

Even among those not adopting a formal advocacy approach, mindsets are shifting. Formerly claims-centric programs are becoming worker-centric and it’s a win all around: better outcomes; greater productivity; safer, healthier employees and a stronger bottom line.


That’s what you’ll see in this month’s issue of Risk & Insurance® when you read the profiles of the four recipients of the 2018 Theodore Roosevelt Workers’ Compensation and Disability Management Award, sponsored by PMA Companies. These four programs put workers front and center in everything they do.

“We were focused on building up a program with an eye on our partner experience. Cost was at the bottom of the list. Doing a better job by our partners was at the top,” said Steve Legg, director of risk management for Starbucks.

Starbucks put claims reporting in the hands of its partners, an exemplary act of trust. The coffee company also put itself in workers’ shoes to identify and remove points of friction.

That led to a call center run by Starbucks’ TPA and a dedicated telephonic case management team so that partners can speak to a live person without the frustration of ‘phone tag’ and unanswered questions.

“We were focused on building up a program with an eye on our partner experience. Cost was at the bottom of the list. Doing a better job by our partners was at the top.” — Steve Legg, director of risk management, Starbucks

Starbucks also implemented direct deposit for lost-time pay, eliminating stressful wait times for injured partners, and allowing them to focus on healing.

For Starbucks, as for all of the 2018 Teddy Award winners, the approach is netting measurable results. With higher partner satisfaction, it has seen a 50 percent decrease in litigation.

Teddy winner Main Line Health (MLH) adopted worker advocacy in a way that goes far beyond claims.

Employees who identify and report safety hazards can take credit for their actions by sending out a formal “Employee Safety Message” to nearly 11,000 mailboxes across the organization.

“The recognition is pretty cool,” said Steve Besack, system director, claims management and workers’ compensation for the health system.

MLH also takes a non-adversarial approach to workers with repeat injuries, seeing them as a resource for identifying areas of improvement.

“When you look at ‘repeat offenders’ in an unconventional way, they’re a great asset to the program, not a liability,” said Mike Miller, manager, workers’ compensation and employee safety for MLH.

Teddy winner Monmouth County, N.J. utilizes high-tech motion capture technology to reduce the chance of placing new hires in jobs that are likely to hurt them.

Monmouth County also adopted numerous wellness initiatives that help workers manage their weight and improve their wellbeing overall.

“You should see the looks on their faces when their cholesterol is down, they’ve lost weight and their blood sugar is better. We’ve had people lose 30 and 40 pounds,” said William McGuane, the county’s manager of benefits and workers’ compensation.


Do these sound like minor program elements? The math says otherwise: Claims severity has plunged from $5.5 million in 2009 to $1.3 million in 2017.

At the University of Pennsylvania, putting workers first means getting out from behind the desk and finding out what each one of them is tasked with, day in, day out — and looking for ways to make each of those tasks safer.

Regular observations across the sprawling campus have resulted in a phenomenal number of process and equipment changes that seem simple on their own, but in combination have created a substantially safer, healthier campus and improved employee morale.

UPenn’s workers’ comp costs, in the seven-digit figures in 2009, have been virtually cut in half.

Risk & Insurance® is proud to honor the work of these four organizations. We hope their stories inspire other organizations to be true partners with the employees they depend on. &

Michelle Kerr is associate editor of Risk & Insurance. She can be reached at [email protected]