Personalized Mortality Curve
A financial advisor had a good client who owned a life insurance policy on his father. Despite the fact that the insurance carrier was a top rated institution with a great reputation, this particular whole life policy had a high term blend to keep down the premium and it was encumbered by a loan which was effectively cannibalizing the policy.
Even when we procured new in-force ledgers showing the loan fully paid back in cash and the full premium paid out of pocket every year, the policy still could not support itself given the dramatic drop in dividends over the years and the death benefit eroded annually through age 90.
We performed numerous internal rate of return (IRR) calculations on a handful of different in-force ledgers assuming different loan management and premium options. The problem was that the IRR dropped precipitously after the 10 to 12 year horizon.
Here is the question; when is dad going to die? While no one can determine that we can bring tools to the table to make decisions on an informed basis as possible. With the introduction of the Premium Efficiency Analysis we created a personalized mortality curve and showed the policy owner dad’s personalized 50th, 70th, and 90th mortality assumptions and this greatly aided the policy owner in making decisions in regards to further funding the policy.
I was working with an advisor recently who is involved in a typical situation; given the current economic environment, he has a client who is struggling to, or at least questioning if he should, pay his life insurance policy premium payments. We have a 78 year old individual who is paying $66,000 a year for a $1,000,000 policy. The policy currently has a $125,000 cash value. One question on his mind was the benefit of borrowing the money to pay the premiums. While I am not going to nix the idea out of the gate, this is a good example of how one must be very careful in analyzing the alternatives at hand, which we determine to be:
- Cashing in the policy
- Selling it in the life settlement market
- Scratching to pay the premiums out of pocket
- Temporarily financing the premiums
There is a need and desire for the death benefit so the first option is not attractive. The policy simply does not fit the parameters of the settlement market so we scratch the second option. The economic attractiveness of options two and three, as with all life insurance transactions, varies substantively based on anticipated length of life. This is particularly important in the fourth option as the client could be “underwater” at some point. At any duration, the death benefit will be reduced by the accumulated loan and loan interest. We have to take into consideration the opportunity cost of the existing cash value which could be put to work in an alternate investment. We also have to use these numbers to warn against a certain element of the market which uses premium financing to promote “free insurance”.
When we look at standard mortality charts, the 50% percentile life expectancy is 13 years or age 91and the 85% life expectancy is 19 years or age 97 for this gentleman.
When we do the numbers, by the 8th year, the financed premium at 8% has accumulated a debt of over $700,000 leaving only $300,000 in death benefit. The cash value in an alternate investment could have grown at the same rate to roughly a quarter million dollars. I’ll call this the break even year. What we can take from this is that the premium can not be financed any longer than absolutely necessary or the transaction will be upside down.
If the premiums are paid out of pocket, the rate of return on the transaction from today moving forward is as follows:
6 yrs 19.2%
8 yrs 9.5%
10 yrs 4.4%
12 yrs 1.3%
14 yrs -0.6%
16 yrs -2.0%
Based on standard mortality tables, this entire transaction is a toss up. But is this insured someone who should be making decisions off of a standard mortality table? It turns out he has been unhealthy for quite some time and it doesn’t seem appropriate to assume normal life expectancy.
In order to bring meaningful and objective information to the table in order to allow informed decisions to be made, they hire us to research, create and present a client specific mortality curve. We retain the services of two life expectancy specialty companies and create our own personalized mortality curve based off of his complete medical file. The 50th percentile mortality for this gentleman turns out to be substantively closer at hand than that of the same aged gentleman who is “average” health.
This is a multi hundred thousand dollar decision. If this does not warrant some modest amount of attention, time and money to find meaningful data and analysis, I am not sure what does. Based on this information the client and his advisors can make much more informed decisions rather than a “gut feeling” decision which I see being made all too often and they can manage this transaction accordingly.