New York Life | July 3, 2023
More than 6,000 people from across the insurance industry gathered at New York City’s Javits Center on June 7 and 8 to connect and discuss innovation in insurance. The annual event, Insurtech Insights USA, featured 400 speakers over two days, with panel titles ranging from “It Takes a Rebel” to “AI at the Forefront: Shaping the Future of Insurance.” In fact, in one way or another, many of the panels touched on how generative artificial intelligence (AI) is changing the industry.
This year, one noticeable trend was the heightened focus of technology startups and other industry participants on enabling insurance companies to provide better experiences for their customers. The point was highlighted by several corporate venture capital firms, including NYL Ventures.
New York Life was well represented at the event and participated in several panels as outlined below:
NYL Ventures’ Tim Del Bello spoke on this panel with fellow panellists from AXA Venture Partners, American Family Ventures, IA Capital Group, and BMI Capital International. The audience of technology entrepreneurs heard Tim say that NYL Ventures likes to see high growth driven by differentiated technology and a quality team in the start-ups they invest in. “We look for companies that we can add value to as part of New York Life,” he said.
“Data and analytics has always been a focus of New York Life Ventures. We’re excited about applying AI to all aspects of the insurance value chain–particularly with the recent advances in large language models,” Tim said. He also noted that it’s much tougher for startups to raise money than it was a few years ago, with capital markets significantly tighter. “We encourage our founders to control their own destiny with respect to financing their business,” he said.
Insurance Solutions’ William Mak spoke on this panel, noting that his team’s top priority around data is using it “to make it as easy as possible for our customers to apply for and buy life insurance.” He said that we’re developing AI models that use data to allow us to underwrite policies without having to take blood or urine samples from applicants. “The promise in the technology we’re seeing now with large language models (LLMs) is to enable the human underwriter,” he said. “It’s still a human-to-human relationships industry. Underwriting is a mix of science and art.”
William also moderated this panel, with speakers from RGA, Nationwide Financial, and DigitalOwl. He facilitated a stimulating discussion on how we might imagine generative AI solving the problem of enabling greater speed and capacity of human underwriters to improve the purchase experience for the customer.
He also led the speakers to explore how we can overcome some of the hurdles with using generative AI due to challenges inherent in the technology, such as hallucinations (making up false facts), “black box” (not showing its work), and data privacy concerns. Additionally, they discussed opportunities in our industry to ensure alignment with re-insurance partners and regulators, and to increase the ease of AI adoption by human underwriters.
On day two, New York Life Chief Analytics Officer Glenn Hofmann was joined by counterparts from USAA, Principal Financial Group, AgentSync, and FinTLV Ventures to discuss how to propel an organization forward using advanced analytics.
All the panellists agreed that there can be no successful analytics program without quality data and governance, and that it’s important to communicate the value of data models to get buy-in across the organization. It’s also important to bridge the gap with business areas and try to understand the problems they’re trying to solve. Glenn talked about the power of having dozens of machine-learning models informing decisions across the company and noted that “there’s three times as many models we could build that we haven’t gotten to yet.”
Each of the panelists talked about how they approach machine learning and AI in their organizations with some having a centralized model, others decentralizing the work across the businesses, and some using a hybrid model. Glenn talked about our approach, the success of our data science learning program, and the data science leaders group, which includes data scientists from various areas at New York Life.
Finally, the panel talked about use cases for analytics, and while they vary by company, the cases can be for distribution, marketing, underwriting, and service, to name a few. There are also models that triage data and transaction fraud and geospatial models that determine site locations and real estate investments. Glenn pointed out that generative AI allows for even more use cases.
Find out more about the Insurtech Insights USA conference here.
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