Building windows

Orange County Business Journal: Stress Test Your Life Insurance

Stress Test Your Life Insurance

by Gordon Schaller and Scott Harshman

This article appeared in the February 22, 2011 issue of the Orange County Business Journal.

Click here to view this article as a pdf.

The life insurance industry has utilized technology over the last 30 years to create new hybrid financial/life insurance products. Life insurance can be an efficient tool to provide liquidity for a family, business, charity or to fund estate taxes. Most people who purchase life insurance rely on their financial advisor to design the product to meet their objectives with a high degree of certainty. Universal life and variable universal life are two such products which have substantially replaced whole life as the sales leaders. Volatile financial markets and negative returns have highlighted a major design risk in variable universal life – negative investment returns, coupled with increasing mortality costs as insureds age, can force a policy into a death spiral from which it may not recover. As discussed below, Monte Carlo analysis can be used to measure the likelihood of policy failure – at the inception of the policy or anytime during its life.

Universal life products seem simple: pay premiums into the policy, and after sales and term insurance charges and some other expense items, the balance of the premium goes into a “cash value” account which earns a current rate of return (crediting rate) declared by the insurance company. However, the long-term ability of a universal life policy to remain effective past life expectancy to the actual date of death depends on the ultimate balance of these credits and debits. When crediting rates were high (12-14% in the 1980s), although not guaranteed, this seemed obvious. By the 1990’s the actual crediting rate had declined to 7-8%. This highlighted the fact that "premiums" calculated by computerized insurance illustration systems were not guaranteed – only the underlying minimum crediting rate (usually 4%) was guaranteed.

As interest rates continued to decline and the stock market began its bull run in the 1990s, variable universal life became the next "big thing" in life insurance. As with universal policies, variable universal life allowed the owner to choose a "premium," and also allowed the owner to direct the investment of the net cash value. This created an opportunity to capitalize on surging equity returns.

The “rising tide lifts all ships” stock market obscured an important technical issue in variable life. Negative investment returns and significant volatility, combined with increasing mortality costs at older ages, can create a fast-acting, negative domino effect on the sustainability of variable life policies. Subsequent positive investment performance – even if robust – seldom repairs this problem.

Statistical analysis can help determine the probability that a variable universal life policy will fulfill the client’s expectations. Conventional insurance policy illustrations require use of constant performance assumptions. Since this never occurs, the illustration is compared with a random application of actual, volatile monthly returns of the last 50 or more years (a "Monte Carlo" analysis). The analysis is done 1000 separate times producing a certain number of randomly calculated hypothetical illustrations in which the policy sustains to age 100; the remaining number do not sustain to age 100. Suppose the result was 450 successful and 550 unsuccessful outcomes. A 45% chance that the policy will pay the death benefit as expected is never acceptable. Reversing this approach can determine the required "premium" either when the policy is acquired, or while it is in force, to achieve the desired success ratio.

When properly designed and managed, life insurance is unique in its ability to deliver cash just when it is needed. However, much confusion exists about the difference between guaranteed, contractual policy provisions and the appearance of a substantially more aggressive policy illustration. Each policy alternative must be analyzed in comparison with the policy owner’s "insurance style," including his or her risk tolerance, timeframe, and basic asset allocation. Once a policy is acquired, it is critical to review the performance and sustainability of that policy regularly with a financial advisor. Stress testing your policy will provide a realistic picture of a policy’s condition and determine whether financial remediation is in order.

About the Authors
Gordon Schaller is a prominent Orange County tax and estate-planning attorney. A partner at Jeffer Mangels Butler & Mitchell LLP, Gordon focuses his practice on taxation issues, estate planning, business succession, charitable and wealth management services and trust and estate litigation. His 30 years of experience in wealth management, and his intimate knowledge of financial, estate and tax structures, helps him add value to every client’s unique situation. Contact Gordon at 949.623.7222 or

Scott Harshman is an experienced tax and estate-planning attorney in Orange County. A partner at Jeffer Mangels Butler & Mitchell LLP, he has extensive experience in tax, trust and estate matters and business planning for high net-worth individuals, including wealth transfer planning, income tax planning, corporate and partnership taxation, business succession planning, and international estate and tax planning. Scott also has expertise in the structure and formation of nonprofit entities. Contact Scott at 949.623.7224 or

About Jeffer Mangels Butler & Mitchell LLP
Jeffer Mangels Butler & Mitchell LLP (JMBM) has one of California’s most active trusts & estates practices in full-service law firm. Our trusts & estates practice focuses on estate planning, wealth transfer planning, trust administration and the resolution of trust disputes. Our clients include individuals, family offices, and public and private charitable organizations. From our offices in Irvine, Los Angeles and San Francisco, we serve our clients’ interests worldwide. For more information go to