Life Settlement Valuation

Most life settlement investors value a life insurance policy by obtaining an LE from an LE provider and backing out the survival curve from the Society of Actuaries (SOA) 2008 VBT Table. They then use this survival curve to determine yearly expected cash outflows(premiums and maintenance expenses) and cash inflows (death benefit proceeds). These cashflows are then discounted at the desired gross yield the investor wants to earn (13% to 18%) to derive a purchase price for the policy. However, this method of valuation fails to account for a number of key factors:

The efficacy of using a life insurance mortality table for life settlement

This is of utmost importance given that the SOA VBT 2008 Table is based on over 30 years of life insurance experience in which an insured is underwritten once and his mortality experience is kept track of over time. The life settlement industry is profoundly different from this. In life settlements, an insured is constantly being underwritten after policy acquisition as investors attempt to gauge market value for their policies. Doing so in combination with a life insurance mortality table subjects the valuation to the select and ultimate transition probabilities of a life insurance table which do not accurately depict life settlement mortality experience. This results in both accounting practices and tertiary policy sales that severely devalue the investment even when there have been no changes in the health of the insured (i.e. the underlying value of the investment has not changed).

The true survival curve of the insured

Life settlements are in part an arbitrage investment on the health status of the insured relative to his health when he purchased the policy. If the insured’s health was “Super Preferred” when he purchased the policy and is now “Substandard”, the premiums required by the investor to keep the policy in force are low relative to health of the insured. Backing out a survival curve from an LE assumes that the shape of the survival curve for each individual insured is the same. This approach fails to accurately value the investment since the policy is valued based on the expected cashflows derived from the backed out survival curve—not the LE. Hence, even if the LE is correct, the valuation can be materially off.

The risk of the investment

Even if the mortality assumptions are correct, this method of valuation does not accurately capture the risks of investing in the policy. While a policy may have a high value today, the value may be drastically different a year or two from now. Not accounting for these risks at purchase of the policy can also lead to drastic losses. To put it in simple terms, if a policy has a 10% chance of returning a $1,000,000 death benefit gain and a 90% chance of losing $50,000 in premiums, the expected value of the investment at time 0 is $55,000. Just because the value is positive does not mean the policy should be purchased as this value does not account for the risk. Furthermore, a year from now those probabilities could be drastically different—especially if the true survival curve is taken into consideration.

The point at which to lapse the policy

Current valuation practices assume that investing in the policy until the maturity date of the policy creates maximum value. This is often false. For most policies, there comes a point in the future at which the premiums are increasing faster than the expected death benefit proceeds. Including cash flows after this point in the valuation—or even worse paying premiums on policies after this point—materially lower the true worth of the investment.

At Colva, we utilize the most sophisticated and advanced actuarial methodologies to accurately value your investment on both a policy and portfolio level.

Contact us at to discuss how an actuary from Colva Insurance Services can help you maximize the return on your investment in Life Settlements.

With the help of Colva’s unique expertise you won’t just be purchasing policies at a 13-18% yield; you’ll actually be earning those yields too.

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