The Future of Life Insurance

Version 2023-04-17. Copyright © 2023 by Glenn S. Daily. All rights reserved.

I am optimistic about the future of life insurance in the U.S.

At first glance, this seems like a crazy thing to say. The life insurance marketplace is an ethical swamp. Too many of the products are junk. Regulators consistently fail to take simple steps that would help consumers understand what they're buying.

I discussed these problems years ago:

So why am I optimistic?

I'll focus on three people whose work I admire.

David Lau

Lau is the founder and CEO of DPL Financial Partners ( He was a top executive at an internet bank and an insurance company that developed annuities for registered investment advisors and fee-only planners.

DPL Financial Partners runs a curated product platform that primarily offers commission-free annuities. Subscribers pay an ongoing fee for access to the products and related analytical tools. DPL Financial Partners also earns a distribution fee for product sales.

A curated product platform solves the main problems with the U.S. marketplace:

  • High commissions

    Stripping out commissions and most of the other distribution costs from life insurance policies leads to high early cash values and a reasonable expectation of better long-term performance. How much better? Distribution costs for agent-sold policies typically amount to 15% to 25% of premiums on a present value basis. If you can limit that to 5%, you could expect to pay up to 20% less for the same death benefits, all other things being equal.

    That pays for a lot of fee-only advice. It also addresses the basic unfairness of having to pay a commission to get access to tax benefits that we all pay for as a society.

  • Limited product information

    The information that is currently available for retail life insurance products is generally superficial.

    With access to product pricing assumptions and an independent actuarial review, a curator can provide an upfront assessment of risk factors and an ongoing assessment of actual versus expected performance. Of course, the curator still has to comply with performative regulations, but there are few prohibitions on providing information that goes beyond what the regulations require.

    Consider indexed universal life, whose current popularity reminds me of novice gamblers in a casino making bets on a whim. The curator could explain the options budget that is available to create the indexed strategies, as well as the equivalent fixed interest rate that could be used for illustrations. It might also be possible to provide an economic valuation of the indexed strategies to measure the construction costs.

    For both indexed and variable universal life, simulation techniques are necessary to show the impact of the variability of asset returns on policy values.

    For hybrid life/long-term care products, multi-state modeling is necessary to separate the life insurance and long-term care benefits and to show the relationship to premiums paid.

    There are many opportunities for curated product platforms to differentiate themselves with advanced analytics.

  • Careless information design

    Information design is a fascinating field of study, filled with insights about how to present technical information meaningfully. Some companies have clearly put some thought into their graphics; others seem clueless. (Cluelessness clue: pie charts and pointless 3D graphs.)

    Conscientious curators will view information design as one of their responsibilities.

  • Misguided product design

    Many retail products violate basic principles of efficient design. One principle is to match policy loads and the company's incurred expenses with respect to timing and amount. Back-end loads lure consumers with the pitch that “all of your money goes to work for you immediately,” but the reality is that you are simply borrowing money from the insurance company at a high implicit interest rate to pay the upfront costs for distribution, underwriting, and issue. Actuaries know this, but they yield to the marketing people.

    Curated product platforms can draw attention to smart design, accompanied by consumer education.

  • Disincentives for fee-only advice

    Fee-only advice works fine for existing life insurance policies, but it is less viable as a business model for new coverage, especially for large cases. Whole life policies allow commission reduction through riders, but most universal life policies have no similar way to negotiate the agent’s commission. The fee for providing competent, unbiased advice is usually dwarfed by the agent’s compensation, and yet the fee-only advisor may bear more liability than the agent if something goes wrong in the future.

    By removing sales compensation from the picture, curated product platforms provide a friendly environment for fee-only advice.

Curators can differentiate themselves along the dimensions of product design, actual performance, transparency, analytical tools, information design, and marketing.

Curated product platforms will initially target the high-net-worth market and its fiduciary advisors. But the growing prominence of competing product platforms could lead to an organic shift in the retail market toward fee-based distribution and better product information.

Bobby Samuelson

Samuelson grew up in an insurance family. He was a well-known industry consultant before becoming a product development executive at two insurance companies. He now runs two ventures.

Life Innovators ( is a life insurance and annuity product design firm with actuarial and distribution expertise. They handle product development for several insurance companies, and they assess the merits of new ideas that are brought to them.

The Life Product Review ( is a subscription-based platform that provides product reviews and analysis as well as industry commentary.

I think of a service as something that I would miss if I didn't have it. I remember sources of information that are long gone: Best's Flitcraft Compend and Best's Policy Reports, Roger Blease's Full Disclosure, Joseph Belth's The Insurance Forum, the Tillinghast Universal Life Analytic Study, and the Society of Financial Service Professionals' Illustration Questionnaire. These were services, and I miss them.

Fortunately, vacuums do not last forever, and we now have The Life Product Review. I am a subscriber, and The Life Product Review meets my definition of a service.

With his own work experience and the product development resources of Life Innovators, Samuelson is well positioned to provide insightful commentary about the life insurance marketplace and the products in it. He can dig below the illustrations, product guides, company filings, and statutory accounting information to infer how a product works. This is the subterranean level where interesting due diligence lives.

Andrew Altfest

Altfest is the son of two distinguished fee-only financial advisors. He is the President of Altfest Personal Wealth Management and the co-founder and CEO of FP Alpha. FP Alpha ( has pioneered the use of artificial intelligence in financial planning.

Subscribers upload tax, legal, and insurance documents, and FP Alpha summarizes them and makes recommendations.

One user has said that FP Alpha is the future of financial planning. I believe it.

Consider this: In a three-generation, 12-member family, there are over 479,000 possible sequences of deaths. I have long wondered about the best way to craft an estate plan to cover all of these possibilities — and I left out marriage, divorce, new children, moving to a different state, and health changes. With AI, this should be easy, and you could even add the secondary goal of minimizing the total cost of necessary revisions as events occur.

Still, these are early days in the future of financial planning, and it's important to have realistic expectations about what AI can do.

For example, how would AI handle these real-world situations that I have encountered?

  • A company's illustration used cost-of-insurance charges that were significantly below the actual charges being made. After several months of back-and-forth communications, the company apologized for the inconvenience.
  • A company credited 4.0% interest on a universal life policy, and this was correctly shown on the annual statement. Their illustration said that the interest rate was 4.0%, but the projected values were really based on 4.5%, including a 0.5% bonus that was not actually being paid. The company admitted that its illustration was wrong.
  • A company's illustration said that the universal life policy would require a single premium of $1 million. However, the calculation factors in the policy contract translated into a single premium of $950,000. The company said that the illustration was correct and that one of the factors in the contract was wrong. The policyowner, an attorney, said that a contract is a contract, and the company eventually agreed.
  • A company's universal life policy has a complicated no-lapse guarantee with two sets of cost-of-insurance rates. A lower set of rates applies if the shadow account is positive. A much higher set of rates applies if the shadow account is zero or negative. This design imposes a severe penalty for mismanaging a policy.

Policyowners and their advisors probably have many examples to add to this short list.

Will AI catch mistakes in illustrations or policy contracts? Will it warn people about subtle traps to avoid?

The famous Turing test measures whether a machine truly acts like a person. In the advisory context, we can measure how close AI comes to acting like a knowledgeable advisor. It seems inevitable that the gap will narrow over time and, at least for some tasks, eventually disappear.

The gap could narrow quickly for smartly designed products distributed on curated product platforms. Those products should be easier to understand, and there should be fewer mistakes and pitfalls to highlight.

The gap may narrow much more slowly for advice about how to live in a dynamic world. How can I put myself in a position to have acceptable options later? Should I buy this policy now or wait for a future policy that may or may not materialize?

For precisely defined situations, AI can apply real options analysis to make a recommendation about how to create and manage optionality. But most dynamic situations are fuzzier, and good advice draws upon the advisor's life experience.

Curated product platforms, smart product design accompanied by useful information, AI-assisted planning…That is a future to be optimistic about.