LifeSelect
TM
Fasano Associates’ top priority is providing
Accuracy, Consistency and Professionalism in
estimating life expectancies!
Re-print excerpt the December issue of the Fasano eNewsletter 2010.
Investors Need to Focus on Actual to Expected Analysis Issues by Michael Fasano
It has been over two years now since the 2008
Fasano Life Settlement Conference, when I first
called for Best Practices for Life Expectancy
Underwriters to include disclosure of Actual to
Expected performance results on a consistent,
transparent basis. The discussions continue
and therefore I believe it is important to address
some of the issues that have been raised. The
unfortunate reality is that LE Underwriters have,
and I suspect will continue to, put out A to E
results that don’t reconcile with the significant
LE spreads that exist in the market. Investors
will therefore need to become more proactive in
reviewing our Actual to Expected performance.
In this paper I will cover issues involved in the
calculation of Actual deaths, Expected deaths and
the appropriate Mortality Table.
Actual Deaths
The calculation of Actual deaths is fairly
straightforward. We can run our database against
the Social Security Administration’s Master Death
File (MDF) to identify recorded deaths and then
make an assumption about deaths that have
happened but not yet found their way into the
MDF, which we refer to as IBNR, i.e., incurred
but not reported deaths. Some have argued
that all underwriters should use the same IBNR
assumptions, but I don’t agree with that view. The
fact is the IBNR experience of the different LE
underwriters may not all be the same. I believe
that if LE underwriters either present one set of
results without IBNR or explicitly disclose their
IBNR assumptions in a way that allows investors
to substitute their preferred assumptions on
IBNR, then the goal of transparency will be met.
© 2010 – Fasano Associates, Inc. All Rights Reserved
Fasano Associates commissioned an extensive
research study on the components of IBNR that
we make available to investors who request
copies of our Actual to Expected analyses. There
are 3 major components of IBNR:
1. Master Death File Errors — The Social
Security Administration (SSA) has estimated that,
at the older ages that typify the life settlement
market, approximately 5% of U.S. deaths are
excluded from the MDF due to incorrect or
missing social security numbers. (See Social
Security Bulletin, Vol. 64, No. 1.)
2. Client and Underwriter Database Errors —
Despite our best efforts to validate social security
numbers (SSNs), we still find significant database
errors. The commercial data services such as
Experian and Veris do not adequately cleanse
their databases and therefore it is not unusual
to find multiple names associated with the same
SSN or multiple SSNs associated with the same
name.
3. Lag in reporting deaths to SSA — We have
found that this is the smallest component of IBNR
and tends to wear down quickly.
Expected Deaths
The issue of what constitutes Expected Deaths
has become somewhat controversial. Do we
mean Expected Deaths as per the actual life
expectancy estimates we gave our clients,
or as per adjusted or restated estimates —
perhaps based on current mortality tables and
methodologies being used, or both?
continued …
Although I see value in pro-forma analyses that
are clearly labeled as such, my view is that an
Actual to Expected analysis should measure
an underwriter’s actual, not hypothetical,
performance. Nevertheless, there are
advantages to the use of restated estimates
of Expected Deaths:
But if we improve our underwriting by adjusting
both our debiting and our Mortality Tables,
doing a restated or adjusted Actual to Expected
analysis would require us to reunderwrite all our
prior cases, which is not feasible, OR to make
simplifying assumptions, which leads to mushier,
less credible results.
1. There is an intuitive appeal to putting together
an analysis that is based on current mortality
tables and methodologies.
3. May not be relevant — There is a question
as to whether back testing, or applying current
methodologies to the past, really gives us any
insight as to the future. To illustrate this, let’s
consider a couple of hypothetical examples —
that of a fixed-income investment manager and
that of a life settlement underwriter:
2. Restated calculation of Expected Deaths
can be a measure of how accurate your current
underwriting approach is.
3. What value is there in dwelling on past
underwriting mistakes? What does that have to
do with the future?
On the other hand, there are also disadvantages
in using adjusted estimates of Expected Deaths:
1. Adjusted Estimates are difficult to audit —
There is no question as to what an underwriter’s
actual life expectancy estimates were. It is an
easy exercise to audit the values in a database
with those in the reports given to clients. But
when we use adjusted life expectancy estimates,
how does an investor know that the methodology
and Mortality Tables we say we are using today
are the same as we will be using tomorrow, or the
day after tomorrow?
2. Difficult to do right — LE estimates are
derived by applying a Mortality Rating to a
Mortality Table. Although it is easy to change
Mortality Tables to solve for a better Actual
to Expected ratio, good underwriting requires
that we not be so simplistic and that we look at
both debiting (Mortality Rating) and Mortality
Tables. The fact is our accuracy in estimating
life expectancy varies by impairment. Medical
developments – such as coronary artery bypass
surgery and development of statins to treat
elevated cholesterol affect specific impairments
— in these examples, cardiovascular disease.
The best way to adjust for these impairment
specific developments is to change our debiting,
or risk assessment, for the affected impairments,
not to lump them in with overall extensions to our
Mortality Tables.
© 2010 – Fasano Associates, Inc. All Rights Reserved
a. Evaluating a Fixed Income Investment
Manager — Interest rates have been low and/or
declining over the last 10 years, with a positive
yield curve in which long-term bonds have
had a higher yield than short-term bonds. If a
fixed-income manager were to come out with a
new investment policy of investing only in zero
coupon bonds of 10 years or longer maturity and
if he back tested this against the last 10 years,
his “track record” would be spectacular. But
what would happen if in the future interest rates
increased? His actual performance would fall far
short of his hypothetical track record.
Rather than see a back tested analysis of the
investment manager’s current investment policy,
I would like to see how he actually performed in
periods of both increasing and decreasing interest
rates, with his actual portfolio at the time.
b. Evaluating a Life Settlement Underwriter
— Life settlement history can be broken into four
somewhat distinct periods:
• Pre-2001 — which was very viatical and very
short-term;
• 2001 to 2003 — a slow market in which LEs got
longer as we transitioned from viaticals to
life settlements;
• 2003 to 2008 — substantial growth with
significant impact of premium finance/STOLI
business, which was largely standard and
preferred business; and
• Post 2008 — very little new business with more
mildly and moderately impaired and virtually
no premium finance/STOLI business.
continued …
What if our Life Settlement underwriter changed
their tables/methodology such that they were
very long on standard and preferred cases but
very short on mildly and moderately impaired
cases? A back tested A to E analysis over the
post 2001 period, heavily influenced by standard
and preferred premium financed policies, would
show them favorably. But if the future had less
premium financed policies and more mildly and
moderately impaired policies (for which their LEs
are short), their actual performance going forward
would fall far short of their hypothetical track
record.
Wouldn’t it be nice if we could see how LE
underwriters actually performed in the viatical
era, in the 2001 to 2003 transition era, in the
boom era of 2003 to 2008 and post 2008?
The reality is that we really won’t know how our
current methodologies and Mortality Tables play
out for another 3 to 5 years. I plan to be here.
I hope that my clients and competitors will
be as well.
Mortality Tables
For every Life Expectancy estimate there is a
distribution of mortality around that estimate —
a certain percentage of people are expected to
die in the first year, a usually larger percentage in
the second year, and so forth. When doing A to E
analyses, we need to disclose the Mortality Table
used to build the mortality distribution around
the point estimate of life expectancy. It is very
important that any mortality distribution pass
a reasonableness test as illustrated in the
following graph:
Each of the above mortality distributions reflects an 11 year life expectancy estimate. However, the
spiked, blue distribution is not reasonable and would make the underwriter using that distribution look
unrealistically more conservative than an underwriter using the more reasonable red distribution.
© 2010 – Fasano Associates, Inc. All Rights Reserved
continued …
I have argued that LE underwriters should do
at least one A to E analysis based on the same,
“common”, Mortality Table that is also in the
public domain and not proprietary — (1) to assure
that the mortality distribution is reasonable; (2)
to make sure that we don’t generate different A
to E ratios simply due to the fact that we have
used different Mortality Tables; and (3) to allow
investors to reverse engineer our results, should
they want to estimate our performance relative to
a different Mortality Table. Mine is the minority
view, as it would appear that the other major LE
underwriters would prefer to use the Mortality
Tables used at the time they made their LE
estimates or the tables they are currently using.
Theirs is most certainly a reasonable position,
but may not be practical or transparent. The
fact is most LE underwriters have changed their
Mortality Tables multiple times and most of their
Mortality Tables are proprietary and therefore
not available for the investor to analyze. It is for
these reasons that I still would like to see at
least one A to E analysis done by all the LE
underwriters based on a publically available,
transparent, common table.
One of the reasons I have argued so strongly
(but unsuccessfully) for a Common Table is
so that investors can better reconcile our A
to E results with the LE spreads that exist in
the market. A.M. Best has done an analysis of
3 major LE underwriters based on the same
portfolio and underwritten after the 21st and AVS
LE extensions of 2008. The spread between the
shortest and the longest in the A.M. Best analysis
was 10 months. I have seen a more recent
analysis that showed a spread of 14 months. In
percentage terms, I have seen analyses showing
spreads between the shortest and longest of
the LE underwriters of 10% to 15%, with even
greater spreads on traded policies. Yet all of the
LE underwriters appear to be reporting Actual to
Expected ratios of close to 100%. This simply
doesn’t reconcile with reality and with common
sense. We can’t all be close to perfect when our
LE estimates are so far apart.
To the extent that we use different methodologies
and different Mortality Tables in doing our Actual
to Expected analyses and reject the notion of
using a common Mortality Table, we will continue
to present results that don’t seem to reconcile
with the reality of significant LE spreads and that I
believe will keep investors on the sidelines.
© 2010 – Fasano Associates, Inc. All Rights Reserved
Fasano Associates • 1201 15th Street, N.W., Suite 250 • Washington, DC 20005 • 202.457.8188
© 2010 – Fasano Associates, Inc. All Rights Reserved