Munich Re: How are GLP-1 medications and AI technologies impacting life insurance?

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Global obesity has tripled since 1975, but newer medications such as glucagon-like peptide-1 (GLP-1) medications could potentially reverse this trend and ultimately reduce obesity-related morbidity and mortality rates, according to new research from Munich Re's Life Science Report 2025.

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GLP-1 agonists like semaglutides, more commonly known as the brand names Ozempic and Wegovy, and tirzepatide, under the brand name Zepbound, are approved for weight loss management in adults and are approved to treat a number of medical conditions such as type 2 diabetes, high blood pressure or cholesterol, cardiovascular disease and obstructive sleep apnea. Munich Re also notes that studies of GLP-1 medications reveal benefits for some metabolic diseases like polycystic ovary syndrome (PCOS) and obesity-related cancers.

The study leveraged a de-identified dataset that included selective medical and prescription information on 41 million adults in the United States. Data spanned from 2015 to Jan. 1, 2025. 

Munich Re's webinar, "Turn Evidence into Excellence," held Jan. 29, 2026, shared further insights into the study, including how GLP-1 agonists and AI technologies have impacted life insurance underwriting.

Timothy Meagher, vice president and medical director at Munich Re, Canada, in using AI to better understand health and mortality rates, said, "Underwriting will be improved, and insurability should expand."

Munich Re's research reveals that GLP-1 medications yield 0.2% to 0.5% annual mortality improvement, realized over a 20-year period, and studies show 15% to 21% weight loss outcomes – an unprecedented result. A projection of data analysis shows a 21% mortality reduction for non-severely obese individuals 40% mortality reduction for severely obese

individuals in the general population over the next two decades.

Meagher shared that AI can help predict and identify subtypes of type 2 diabetes, as revealed by Stanford Medicine researchers, and that when used in biomedical research, AI can provide accurate predictions of  biomolecular interactions that would enable more rapid development of drugs. Maegher also emphasized the significance that AI will have in analyzing data of health records.

"By analyzing thousands upon thousands of electronic health records, and looking at people's natural history over multiple years, you can actually begin to predict what that trajectory is going to look like way sooner than we possibly could…" stated Meagher. "Inevitably, what we will see here is improved mortality. We certainly are going to have vastly enriched electronic health records and that's the practical aspect of this that will be important for insurers."

By analyzing electronic health records, images and biomedical information, AI technologies will also provide researchers with new predictive associations that redefine health.

"We're also going to get a better understanding of what 'health' is. We have a very vague notion of health, when we underwrite 50 years old we treat them all the same. We use underwriting to try and pair it down and make it more accurate," explained Meagher. "But we use chronological health as a starting point, and I think we will see biological age coming in and supplementing chronological age as an underwriting element."

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