The L&A Hub

Frank Chechel — VP and Head of Individual Life Underwriting at Gen Re, and an actuary who "fell into" underwriting a decade ago when a boss asked him to build an underwriting R&D team — makes the case that after a hundred years, underwriting is only just scratching the surface. He and Paul trace how COVID flipped accelerated underwriting from a nice-to-have experiment into an overnight mandate, why wellness programs went quiet during the pandemic and are now roaring back, and how to think about AI in three distinct layers: predictive models, generative summarization, and the still-early agentic frontier. Frank is refreshingly blunt about the limits — a document summary that's 95% accurate is "a good way to get fired," and the same alcohol-related case put in front of five underwriters can produce five different answers. His through-line: the robots are taking the easy declines and clean preferred risks, which makes the human underwriter's job harder, not obsolete. The future underwriter lives in the gray zone and is fluent in data. Along the way — standing-room-only GLP-1 webinars, why bad data management hamstrings even the best data scientists, and Gen Re's own Claude pilot building a unified underwriting knowledge base.

Josh Hershman has done something almost no one in insurance regulation has done: he's been a private attorney, a deputy commissioner, the executive director of an open-source data standards project, and the CEO of a life insurance company — all before Governor Lamont named him Connecticut's Insurance Commissioner. That resume gives him a vantage point on AI that most regulators don't have, and he uses it.

In this episode he explains how Connecticut is already running AI inside the department (a state Copilot license, financial-exam document review, letter drafting) and why the hardest part is change management, not technology. He borrows the EU's tiered, consumer-impact framework to argue carriers should "break some dishes" on internal use cases while moving carefully on anything that approves or denies a claim — but still moving. He and Paul get into why annuity illustrations are the single most tailor-made AI use case in the industry, how McCarran-Ferguson and the NAIC's slow "model act" machinery actually shape the rules, and why the word "testing" in the AI model bulletin is leaving carriers frozen.

Listeners come away with a regulator's actual map of what to build fast, what to build carefully, and what to bring to a statehouse versus the NAIC.

Chris Orestis has spent 30 years — first as a Capitol Hill and White House staffer, then as a three-time company founder — trying to fix the equation American families face when long-term care hits. In this conversation, he explains why only about 7 million long-term care insurance policies exist across a population of 340 million, why "care creep" quietly turns family members into unpaid full-time caregivers, and why Medicaid should be a family's payer of last resort, not their plan of first resort. He and Paul dig into the harder math underneath the headlines: the Social Security and Medicare trust funds' insolvency date has moved up from 2035 to 2032, and nothing meaningful will happen in Washington until after the 2028 election. Chris lays out the likely fix — higher earner contributions, means testing, and a possible increase to full retirement age — and makes the case that annuities, hybrid life/LTC and products are the industry's best answer to a shrinking safety net. The conversation closes on AI: why consumers are souring on bots, why AI-enabled fraud against seniors is exploding, and why verifying that an agent is a real, licensed human may be the industry's next big trust play.

Jeff Tulloch spent 25 of his 30 years in insurance at MetLife, where he built PlanSmart into one of the industry's first true enterprise financial wellness programs — reaching roughly 40% of the Fortune 500 and millions of employee interactions before he went independent five years ago. In this conversation, he traces the category from a static library of articles and videos that nobody opened ("it just sat there") to today's metrics-driven model, where vendors have to prove people are actually reducing debt, building emergency savings, or raising retirement contributions — not just logging in. He connects a PwC finding that 59% of employees are still stressed about day-to-day finances to a bigger claim: financial stress may be the root cause of the physical and mental wellness problems employers spend far more money trying to solve. Plus: the the turf standoff with a 401(k) provider that became a case study in complementary benefits design, why "Uber-level personalization" is coming for workplace financial education, and what three decades of watching brokers navigate benefit bloat taught him about what actually earns trust.

Tina Beckwith, CMO of LIMRA and LOMA, debriefs the inaugural Best Minds Retirement Symposium and explains why the industry can only fix the annuity perception problem together. She unpacks a counterintuitive discovery — that AI is scraping the industry's own myth-busting content and surfacing the myths as fact — makes the case for plain language over jargon, and argues annuity awareness should be always-on, not a single month.

Jane Vevea spent 20 years in life insurance before anyone would have called her a tech person. She started at Prudential in 2006 running a retention call center, wholesaled through the bank channel at PNC, got laid off, and made a sharp left turn into insurtech. That detour took her through White Swan, then Atidot — where she was predicting lapses, surrenders, and upsell opportunities using AI before most carriers had even thought to ask the question — and now to xAI, where she works as a finance domain expert on large language models.

This conversation covers the real friction in selling AI to insurance carriers (spoiler: it wasn't the actuaries who resisted), why retention AI surfaced uncomfortable ethical and legal questions the industry wasn't ready for, and what a bottom-up AI adoption strategy actually looks like inside a carrier. Jane also makes the case for why the skills AI can't replicate — creativity, human judgment, genuine relationships — are exactly the ones that were undervalued in insurance for decades. And she's blunt about what she fears most: an industry that feeds its biased past into AI models and calls the output progress.

References to artificial intelligence and automation in this discussion are intended to describe industry developments and operational concepts. AI tools may assist professionals, but they do not replace licensed advice, suitability reviews, best-interest obligations, or professional judgment.

Ryan Hinchey has one of the more unique résumés in the annuity business: actuary, Amsterdam expat, Silicon Valley insurtech veteran, and now SVP of Product Innovation at AmeriLife — one of the country's largest distributors of annuity, life, and health products. That arc turns out to be exactly the right background for what he's doing now.

In this episode, Ryan walks through the three models AmeriLife uses to partner with carriers on product development — exclusive, leverage, and proprietary — and why the best ideas increasingly come from the IMO level, not the home office. He explains how he stress-tests product concepts before a single line of pricing work gets done, using a "product blueprint" that forces a clear value proposition early. He also talks candidly about the lessons from his time at Health IQ: get the reinsurer on board first, go after mid-tier carriers before the big names, and be willing to put skin in the game.

On AI, Ryan is doing something genuinely interesting: using it to extract selling stories from wholesaler YouTube videos — structured intelligence on how real people pitch real products. Listeners come away with a sharper sense of what it actually takes to build an annuity product that distribution will move.

Wei Chen is an Associate Professor at the University of Connecticut School of Business and co-leader of the Digital Frontiers Initiative. Over the last three years he's made generative AI his mission — graduate courses, executive workshops, a textbook, and now a business novel modeled after The Goal and The Phoenix Project, set inside an insurance company.

His central argument: every serious conversation about AI and the workforce stops at the task level — which tasks AI can automate, which jobs are at risk. But tasks are only the bottom tier. The level that actually determines whether AI transforms an organization is the workflow: the connected chain of tasks that produces a business outcome. And the piece nobody's building is ownership — a named human who's accountable for the whole workflow, with the authority to stop it when something goes wrong.

The conversation covers Wei's TWO framework (Task, Workflow, Owner), the "validation tax" that turns AI adoption into theater, an Illinois regulatory compliance failure that illustrates exactly what breaks when no one owns the workflow, and why the only approach that works for high-stakes industries like insurance is one workflow at a time — not replacing all four jet engines at once.

This isn't a one-guest show. Paul brings together three of the industry's sharpest voices on retirement income — Joe Jordan, Ted Rosedale, and George Bain — for a roundtable on what's actually changing in retirement planning, and what isn't.

Joe Jordan frames the demographic shift hiding underneath every tech headline: the U.S. has more centenarians than any country on earth, the worker-to-retiree ratio is heading toward zero, and Social Security benefits are mathematically on track for a 20% cut by 2033.
Ted Rosedale explains why Social Security is the largest financial asset most Americans hold — and the most misunderstood — and how the new RSSA designation, now offered through The American College, is closing the advisor knowledge gap on 2,700+ claiming rules. George Bain makes the case that the $14 trillion in U.S. home equity is the leg of the retirement stool advisors keep ignoring, and that reverse mortgages have moved from "barbershop rumor" to legitimate planning tool.

The through-line: AI changes how advisors work. It doesn't change demographics, the cost of getting Social Security wrong, or the trust required to put a real plan in place.

Link to Joe: https://www.josephjordan.com/

Brian Poppe has done something rare in L&A: he started as an actuary, founded Mutual of Omaha's innovation practice as the entire department of one, served as Chief Data Officer, and now runs the company's life insurance P&L. That breadth is the lens for this conversation.

Brian walks through his four-phase AI adoption framework — awareness, helping individuals, redesigning processes, and AI talking to AI — and gives a refreshingly honest read on where carriers actually sit. (Spoiler: most claiming phase four are still in phase two.) He shares the story of a partnership he loved but had to kill because the timing of the offer to grieving families was wrong, why he flew his CTO to Silicon Valley for a "petting zoo tour" that became the foundation of Mutual of Omaha's cloud insurer, and where he thinks carriers will see the first real process redesign — back-office NIGOs, not underwriting.

Listeners will leave with a sharper way to evaluate their own carrier's AI maturity and a clearer sense of what real innovation looks like inside a Fortune 500 mutual.