In this Q&A series, Tim Morant, Chief Risk Assessment Officer at Munich Re Life US, explores the rapidly evolving risk assessment landscape with industry experts. 

This special edition of our series brings together insights from two distinguished experts at Munich Re. June Quah (JQ) leads the Automated EHR Summarizer initiative, applying her actuarial expertise and leadership in AI and machine learning to streamline complex health data for underwriting workflows. Katy Herzog (KH), with over 20 years of underwriting experience, heads the Pricing and Client Support team, driving innovation and optimization across underwriting programs and tools. Together, they engage in a dynamic conversation about the evolving landscape of risk assessment and the transformative role of technology in life insurance.

JQ: My career path seemed typical at the start. I heard about actuarial science in high school, studied math for my undergraduate degree, wrote actuarial exams, began my career in an actuarial student program at a large multi-national life insurance company, and qualified as an actuary, rotating through various areas ranging from pricing, valuation, corporate, and investments. I then took on a role at an insurtech start-up before joining Munich Re. I’ve been amazed at the variety of interesting work in insurance, where I’ve been constantly learning, making it a satisfying career so far. 

KH: As is the case for many underwriters, underwriting found me. As a new college graduate, I was applying for other jobs when an HR representative introduced me to the underwriting profession. A quick Google search sparked my interest, and I haven’t looked back since. After building expertise in production underwriting, I transitioned to project work, including R&D and innovation. I worked for a direct carrier for nearly 18 years before making the leap to reinsurance at Munich Re.

JQ: A major pivot point came when a former manager reached out, and I took the leap of faith to join their small start-up in a new area of predictive modeling and data science. This eventually led to my role at Munich Re, where I’ve had the opportunity to work on leveraging new data and models to improve how we manage and evaluate risks. There have been numerous times in my career when it would have been much easier to simply stay the course and keep doing the same thing. Instead, I am thankful for mentors and colleagues who encouraged me to step outside my comfort zone and take on stretch assignments. Over the last nine years at Munich Re, I have found it very rewarding to be a part of a forward-thinking organization working with enthusiastic client partners as we drive change in a time of rapid innovation in the industry.

KH: A few years into my career, I was able to participate in some non-production underwriting projects. I really enjoyed learning about and working with various disciplines, including actuaries, and big picture perspectives. However, it was difficult to fully dive in when production always took precedence. I was fortunate enough to have a manager who recognized the value of the non-production work and who dedicated more resources to take advantage of the innovation and rapid evolution that was coming our way. Together, we forged a plan to transition my role from production work with projects on the side to a full underwriting R&D and innovation role. One of the first projects I worked on was developing, executing, and monitoring a new underwriting program: Accelerated Underwriting.

JQ: Hands down, the trend that excites me the most is the increasing use of digital data sources, especially Electronic Health Records (EHRs), paired with the advancements in AI and technology. The industry has been moving towards non-fluid underwriting by relying on new data sources to improve the customer experience for several years now. While there is more data available, there are still challenges in using this data in underwriting. Look at EHRs – they are very comprehensive, containing all aspects of an individual’s medical history – but with this wealth of data comes the challenge of integrating to automate risk assessment and reduce the burden on underwriters. Imagine a future state of an insurance application process - digital data sources can pre-populate an application with complete and up-to-date medical information, which can then generate a risk assessment for the policy to be issued in near real-time.

KH: The pace of innovation in underwriting has been exciting, but I agree with June – what excites me most is the availability of digital health data, particularly EHRs. The quantity and quality of information continue to grow, and we’re seeing this reflected in the increasing adoption of EHRs in our industry.

KH: We should stay curious and open to possibilities. We should continue to look to other verticals and learn from their successes and challenges. While we want to move swiftly, we need to have proper governance frameworks in place so that we can drive progress strategically and responsibly.

JQ: Industry knowledge sharing, education, and awareness can help us keep abreast of innovation to understand the potential impacts on our business. A practical approach is to test new solutions on a small scale before expanding further, to collect and use data to develop metrics that will guide what decisions are made, and to continue monitoring post-implementation. As we adopt new approaches, we need to consider change management and have clear communication to build trust. Sometimes, the first attempt at using a new tool may not work as expected. This can be due to many reasons, ranging from misaligned expectations, a calibration error, or simply resistance to a new way of working. Strong collaboration and transparency across underwriting, actuarial, medical, data science, and technology teams, and the willingness to explore options are essential for success.

KH: New data and technology have enabled automation, but there has and will continue to be a need for human underwriters, whether it is for the more complex cases or the strategic direction and execution of underwriting and corporate initiatives. However, with automation, we’ve effectively removed a key component of training for newer underwriters. The cleaner, lower-risk cases that we used to train less experienced underwriters are now being handled automatically by rules and models. In addition, more experienced underwriters are dealing with new data and processes. These challenges have highlighted the need for effective development and change management to be successful in the future.

JQ: I have a similar sentiment as Katy. Talent acquisition, motivation and training, especially in the current environment of significant AI development, is definitely a challenge. AI language models are changing how we work on a daily basis; chatbots that can answer questions, draft our emails, summarize long documents, and simplify many more tasks. It’s both an exciting time and one of uncertainty: “How does this make my job easier?” versus “When will this take my job?” Once upon a time, a computer was a human person performing mathematical calculations. As history has shown, the types of work will change for the better. For our industry, it’s important that we continue to bring in talent and train them to have the skills needed for our core competency of risk assessment and the mindset to adapt to changing technology.

KH: Our insights are only as good as the data behind them. As we forge ahead with modern analytics and multivariate models, some of our legacy systems and processes struggle to keep up. For instance, when we consider monitoring, we rely on accurate and timely information. If we have inaccurate or lagging data, we risk falling behind or experiencing poor results.

JQ: While we have large datasets with historical mortality experience, shifts in lifestyle, behavior, and habits over time can adversely impact how risks will emerge in the future, for example, rising obesity rates. However, with life insurance, we only have one opportunity at the time of underwriting to assess and price the risk.

JQ: We can actively track trends, monitor our business, stay on top of research, and explore products or programs that can improve health and wellness to mitigate adverse trends. One example is that we now have new insights from activity data, sleep, and other data points tracked by wearables. This creates opportunities to increase engagement and awareness amongst our policyholders to make lifestyle choices that will improve their well-being.

KH: We need to be aware of the possible blind spots in the data. Once we’ve identified those risks, we can take steps to mitigate them. For monitoring, there are a variety of tools and third-party data sources that can be utilized to obtain a more comprehensive view. In addition, by engaging market experts such as reinsurance partners, you can benefit from others’ expertise and obtain additional data and a more holistic review.

JQ: My take on getting the basics right is that for every endeavor, we should always understand the problem we are trying to solve and the outcome we are trying to achieve. It’s also important to think of the value in terms of the problem at hand and to zoom out for the bigger picture. This is so that you don’t get caught up in the details or hype and lose sight of the overall goals. With life insurance underwriting, it's crucial to match the price to the risk so that insurance premiums are fair and competitive for the consumer, and the uncertain timing of death is priced adequately. With the increasing availability of data and new tools, it’ll become more and more important to understand the value and materiality of each data source or tool, and that the evaluation can vary by distribution channel and an individual’s risk profile. We want to optimize what data is used so that we can make an accurate risk assessment at the lowest cost.

KH: Ultimately, it is rooted in why we do what we do. We help people protect what matters most: their loved ones and livelihoods. We can do that successfully by building a strong foundation for long-term success. For underwriting and risk assessment, that means being able to assess risk accurately and responsibly, so that we can honor our promises.