Munich Re's Patrick Sullivan discusses how technology is changing the life insurance industry

Munich Re North America Life

Technology continues to transform every aspect of the insurance journey and line of business. From sales to underwriting to claims, insurtech is helping carriers provide policyholders with coverage that is personalized for their needs while making the insurance experience more transparent. One area where technology is expediting the underwriting process involves life insurance. In an interview with Digital Insurance, Patrick Sullivan, senior vice president of integrated analytics for Munich Re North America Life, discussed how insurers and reinsurers are utilizing new data sources and predictive analytics, and how technology is transforming the life insurance space.

Technology & underwriting
One area where insurtech is improving the process involves underwriting policies. "It used to be that to get a policy of any sizeable face amount, you had to do fluid testing and you had to get all of your medical records, and it took weeks….What's changed dramatically is a lot of the important medical information that is used in underwriting is now available online, with the applicant's consent, of course," shares Sullivan. Immediate access to information allows insurers to price and bind policies much more quickly and efficiently.

Artificial intelligence and machine learning are also playing a major role in expediting coverage decisions. Sullivan says that while making decisions based on vast amounts of data can be overwhelming for an individual, utilizing machine learning enables a company to quickly make a decision or determine if more information is needed.

For example, carriers have been using prescription histories for years, however this information combined with an applicant's past medical history is transforming the underwriting process because of the ability to access an individual's full electronic health records.

Sullivan also believes that technology has the ability to shorten the application process and allow companies to use machine learning to help make necessary assessments. "I think over time, we'll migrate more towards a paperless application, where someone will give their consent for the information to be pulled, and then it will really only be on an exception basis if the insurers needed a little more information that they would follow up with questions. I think that the technology will really make it much easier to get insured and I think if that's easier, more people will get insured, which is ultimately what our goal is in the industry."

Protecting information in a data-driven world
The increased use of AI and other technologies also create risks for insurers when it comes to protecting data and the personally identifiable information it contains. Sullivan agrees that cyber risk is a big concern and says the best defense against this risk involves three factors: Technology and leveraging the best capabilities available; utilizing cloud computing, which can limit the number of people who have access to information and a company's infrastructure; and having strong internal corporate security measures in place.

Despite the inherent risks, there are multiple benefits to employing predictive analytics and machine learning in the life insurance industry. "The biggest benefit," discloses Sullivan, "is just speed. If they have someone in their office or there's someone on the phone, they can walk them through an application in real time. Again, an instant decision…They don't have to spend all of that administrative time going back and forth with the applicant and the underwriting department, and getting medical records, which frees them up to spend more time developing business and talking to people about what their needs actually are, which is the main benefit."

One of the concerns arising from the use of machine learning involves the opportunities for bias, and Sullivan says this is top-of-mind for regulators as well. He explains that there are different efforts focused on how to regulate bias and test for it across the industry. Munich Re has spoken with regulators directly on the subject. "I think it's actually maturing towards a good place where bias testing and ensuring that your algorithms are not biased is table stakes. I think it's already there. I think bias testing is built in from the beginning." At Munich Re, a senior staffer oversees the company's bias testing for every model the company builds, which allows changes to be made as necessary.

The future of machine learning
According to the U.S. Bureau of Labor Statistics, approximately 50% of the insurance industry is expected to retire by 2036, leaving nearly 400,000 positions open and creating a significant talent shortage for the industry. While many have been concerned that machine learning will take over jobs like underwriting, the likely reality is that it will enable insurers to operate more efficiently as it handles more routine responsibilities and flags information for underwriters. "I think technology will serve up the data and index the data and say, 'This is a condition that you need to look at'…I also think that the technology will open up new opportunities for underwriters, they'll be case underwriter roles, but also innovation and strategy roles, and technology program roles, understanding how to assist risk and medical underwriting," says Sullivan.

He also sees a host of other benefits with this type of technology. "On the marketing side, I think that's where we'll probably see the most important impact of large language models. So, instead of approaching everybody with the same marketing message, insurers will be able to craft messages that are specific to the individual but do it at scale and make it more relevant. I that is already where we're starting to see large language models being applied like GenAI. I think there's more to do with prospecting and lead generation and the richness of the data, like being able to go to people proactively and saying, 'Look, here's an insurance offer that makes sense and is targeted and crafted to you.'"

Sullivan also believes that the ability to access medical information and databases online will create opportunities for better underwriting and pricing, especially concerning chronic conditions like obesity, coronary artery disease and diabetes. "Being able to understand the value of treatment programs and then being able to give them [policyholders] a better insurance price…will be tremendously beneficial."