- Instant application decisions substantially rising
- Underwriting and operations costs projected to drop
- Customer input and testing "critical" to AI processes
Banner Life credits its long-term AI strategy, with stringent human oversight, for its new standing as the largest U.S. term life insurance provider, as determined by the Life Insurance Marketing and Research Association (LIMRA).
Banner Life reached its highest annualized premiums of $239 million in 2025 and captured 13% of the U.S. life insurance market in the first quarter of 2026, according to
"Absolutely critical" to the success of Banner Life's AI strategy was that "everybody must be joined up in what is being built," including
The company began building its AI systems internally in 2019, and had data consolidated into one location by 2021, according to Holweger. When these efforts started, Banner Life could not make an instant decision for a fully underwritten policy. By 2022, each of the company's underwriters handled 67 instant decisions each month. Now that number is 109 per month, Holweger said.
Banner Life is also seeing lower costs per life insurance application, a decrease of 27% over the past three years, he added. The insurer's overall underwriting and operations expenses dropped 23% by the end of 2025, and Banner Life projects these expenses will drop another 16% by the end of this year, according to Holweger. "With those cost savings, it means we can maintain our competitive pricing," he said.
The insurer set up its AI to succeed by implementing optical character recognition (OCR) to help its underwriters process medical information. Machine learning is applied to underwriting processes to ensure that customer applications go to underwriters only when they are complete, with no information missing. Banner Life also uses machine learning in its underwriting rules engines.
"Humans have written the rules. Humans check [that] the rules are being correctly implemented. The rules allow for the instant decisions," Holweger said. "But the machine learning is then implementing the rules. But then, obviously, we check as well. Yet again, it's human in the loop, that the rules are being implemented correctly. That's what's driving the instant decisions."
More complex applications involving certain medical conditions or complicated financial situations are referred to human oversight as well, he added.
The company tests its machine learning processes before implementing or scaling them up. "You want to test and learn all the time and fail fast," Holweger said. "If it doesn't work, either change it or drop it. Is it working? If it is, we scale it. If it's not working, can we fix it? If not, let's try something else."
Banner Life's CEO sees AI as just one part of a digital transformation. "We've used digital transformation to be the easiest company to do business with, but there are a number of components to that, including data," he said. "
