Estimating life expectancy 8 oct 12_v3_monarch

Estimating Life Expectancy
• Consistency

• Accuracy

• Professionalism

© Fasano Associates 10/2012 1 Estimating Life Expectancy

Estimating Life Expectancy
• Overview/History of Market

• Actual to Expected/LE Comparisons

• Fasano Approach:
– Physician Based Analytics
– Modified Debit Methodology
– Mortality Table Adjustments
– Research Based Clinical Judgment


The History of the Life Settlement Market
• Evolved from the Viatical Market
• Was therefore marketed as an uncorrelated, short-
term duration investment
• Misalignment of interest plus underwriting mistakes
led to too short LEs
• The investor paid the price

• Investors are more informed today, but the market
still has not completely matured


Actual to Expected / LE Comparisons

• Fasano Results

• Methodology Issues

• Fasano changes to debits and tables

• Spreads among LE Underwriters


Fasano Actual to Expected Analysis
Actuarial Net Lives (After Elimination Total
Firm Period Covered of Duplicate Reviews)* Deaths A to E Ratio

Milliman 2001-2003 5,000 252 94 to 99%

IFA 2001-2005 21,000 1,100 96%

Lake 2004-2008 59,000 3,417 96%

Lake/KPMG 2005-2010 64,680 5,877 99%

• Fasano results are based on ACTUAL LE estimates given to clients
• We have not adjusted or restated our LE estimates

* Duplicate reviews on the same life in the same calendar year have been eliminated – so that only the
most current review is included


A/E Methodology
• Take actual LE estimates given to client
• Build mortality distributions around each
LE estimate
• Aggregate all estimated mortality
distributions
• Compare actual deaths to estimated
deaths, as per aggregated mortality
distributions

Actual versus Restated A/E
• A/E should be based on the actual LE estimates
given clients
• Restated A/E analyses are more subjective and
require simplifying assumptions
• Terminology like “historical versus current basis”
is misleading
• If we don’t use the actual LE estimates given
clients, then label the analysis clearly as a
restated analysis based on adjusted LEs

Fasano Changes Since IFA A/E Study

• Cardiovascular debits reduced in June 2007

• Older age (≥ 75) debits reduced in May 2008

• New Mortality Tables implemented in May 2008

• New Tables reflect impact of overall Mortality
Rating

• Underwriting adjustments need to account for
changes in relative risk (debits) as well as
mortality tables

Impact of Fasano Changes
•
Changes have been minor
• Changes vary by category:
• Older ages, relatively longer LEs
• Some younger ages, shorter LEs
• Low mortality ratings, longer LEs
• High mortality ratings, shorter LES
• Across-the-Board mortality table changes lead
to pricing errors


Why Did We Reduce Cardiovascular
Debits in 2007?
1. Compelling research findings
documenting a halving of cardiovascular
mortality

2. Bad A/E results


U.S. Mortality Improvements:
Coronary Heart Disease, 1980-2000
Males Females
Deaths per 100, 000 Population

Source: E. Ford et al, NEJM 356;23 June 7, 2007

Cardiovascular Improvements =>
Maximum Impact > Age 65
Reductions in Deaths by Age and Sex

Source: E. Ford et al, NEJM 256;23 June 7, 2007

Impact of Cardiovascular Changes
Changes in Fasano A to E for CAD/Cardiovascular

Total A/E Total A/E
100%
Cardio A/E 99%
90% 96%
90%
80%
Cardio A/E
70%
Percent A to E

60% 67%

50%
40%
30%
20%
10%
0%
2001 - 2005 2005 - 2010
Reduced debits => Longer LE => Better A/E

CAD and Cardiovascular Overall


Why Did We Reduce Debits in 2008
> Age 75?
1. Adjust for steep slope of mortality curve

2. Bad A/E Results


Slope of Mortality Curve Increases at
Older Ages
(2008 VBT, Select Mortality, ALB)

20
19
18
17
16
15
Standard Mortality

14
13
12
11
10
9
8
7
6
5
4
3
2
1
0

25 35 45 55 65 75 85

Issue Age


Impact of Increasing Mortality Slope:
Same Disease, Same Extra Mortality =>
Lower MR at Older Ages
Mortality Ratio: Standard
Mortality plus 10 extra
Age deaths/1,000/year* Debits
45 235% + 135
65 146% + 46
85 110% + 10

Solution: Formulaic Debit/MR reductions at older ages
*Based on 2008 VBT Primary Mortality Table, Male Non-Smoker, ALB

Impact of Older Age Changes
Changes in Fasano A to E by Age Bracket
100%
Total A/E
98%
Total A/E 99%
96%
A/E >Age 75
96%
94%
95%
Percent

92%
90%
A/E >Age 75
88%
88%
86%
84%
82%
2001 - 2005 2005 - 2010
Series1
> Age 75 Series2
Overall

Reduced debits => Longer LE => Better A/E


Impact of Fasano 2008 Mortality Tables*
Mortality
Rating: 100% 250% 350%

Fasano 08 Prior Fasano 08 Prior Fasano 08 Prior

65 M/NS 232 241 167 169 146 149

75 M/NS 168 162 112 107 87 91

85 M/NS 101 91 54 52 36 41

• Changes differ by age and mortality rating. Across the board
changes lead to pricing errors.
*Please Note: All values are in months, Age Last Birthday


Fasano vs VBT 08*
Spread
Fasano 08 VBT 08 Months %

65 MNS 232 mo 259 mo -27 mo -10.4%

75 MNS 168 mo 169 mo -1 mo -0.6%

85 MNS 101 mo 89 mo +12 mo +13.5%

* Based on 100% MR, ALB

NOTE: FASANO is significantly shorter at the younger ages and
significantly longer at the older ages


Fasano vs AVS/21st at Different Ages
70%

Fasano 60% longer than
21st at age 90

60%

21st at age 85

50%

FAS/21st % Difference Fasano 25%-30% longer
than 21st at age 80
FAS/AVS % Difference
40%

30%

%

21st at age 75
D
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F
c
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f
i

20%

AVS at age 90
10%

Fasano 10% longer than Fasano 30% longer than
AVS at age 80 AVS at age 85
0%

Fasano same as AVS
at age 75
-10%
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Age


Restated Fasano A/E – Based on Client Sample: *
Our Changes Have Resulted in Better Age Specific A/E
Expected Cum.
Age Lives Deaths Actual Deaths A/E Ratio

65 635 23 23 100%

70 1,745 74 76 103%

75 2,707 138 131 95%

80 3,405 221 239 108%

85 2,225 225 208 92%

90 602 103 90 87%

95 75 22 19 88%

Total 11,394 805 786 98%
*MRs were arranged by decile, and MRs from 2005-2008 were adjusted based on the
2009/2010 decile rankings; then applied to Fasano 2008 to get Adjusted LEs. Client used VBT
08 to generate mortality distributions


Conclusion
• Market based pricing, such as VBT08, can
lead to valuation errors

• Older age LEs are too short

• Cardiovascular LEs are likely too short

• Across the board LE adjustments lead to
pricing errors


History of LE Spreads
• Fasano historically has been the longest, 21st the
shortest, and AVS has been in the middle
• AVS extended significantly in 2003 and then again in fall
2008 (by 16%), and more recently in November 2011
• 21st extended approximately 30% in 2005 and then 25%
in fall 2008, attributing both changes to mortality tables
• Spreads tighter today, but Fasano remains longest, as
21st remains the shortest, with AVS in the middle
• Spreads for traded policies are greater than the averages
• Spreads are getting wider again


*Source: Cantor Insurance Group. The sample used to compile the above chart is not large enough to be considered statistically valid. Therefore, the information is for illustrative purposes only.
These materials have been provided to you by Cantor Insurance Group, L.P. (“Cantor”) for informational purposes and not in connection with any proposed transaction(s) and may not be relied
upon for any purpose. The information contained herein is subject to change and has been prepared solely for informational purposes, and is not an offer to buy or sell or a solicitation of an offer
to buy or sell any security, loan or asset or to participate in any trading or investment strategy. Cantor assumes no obligation to update or otherwise revise these materials. Nothing contained
herein should be construed as legal, business, tax or accounting advice. You should consult your own attorney, business advisor, tax advisor and accounting advisor as to legal, business, tax,
accounting and related matters concerning the business described herein and its suitability for you. The materials should not be relied upon for the maintenance of your books and records for any
tax, accounting, legal or other procedures.
None of Cantor or any of its affiliates make any representation or warranty, express or implied, as to the accuracy or completeness of the information contained herein, and nothing contained
herein shall be relied upon as a promise or representation or the basis of a transaction.

2010 Comparative LE Analysis
of >1200 Lives

Underwriter Average LE Spread to Shortest
Months % Spread

Fasano 148.5 months 14.3 +11.1%

AVS 143.0 months 8.8 +6.6%

21st 134.2 months 0 0%


LE Spreads Remain Large
Life Expectancy Spreads:
Average Life Expectancy (mo.) Longest vs Shortest LE
Year Fasano AVS 21st Months % to Longest Sample Size

2007 130 117 97 33 mo. 26% 149

2008 141 120 108 34 mo. 24% 1876

2009 132 115 106 27 mo. 20% 621

2010 124 102 86 38 mo. 31% 240

2011 120 103 91 30 mo. 25% 226

2012 115 102 82 33 mo. 28% 124


LE Spreads:
Percentage of Shortest to Longest LE
32%

30%

Avg. = 28.3%
28%

26%

24%

22% Avg. = 23%

20%
2007 2008 2009 2010 2011 2012


What Happened in 2010?
Mortality Rating Differentials
700%

600%

500%
Mortality Rating

MR for Shortest LEs
400%

300%

200%

100%
MR for Longest LEs
0%
2007 2008 2009 2010 2011 2012

Fasano AVS 21st


Fasano vs AVS/21st at Different Ages
70%

21st at age 90

60%

21st at age 85

50%

FAS/21st % Difference Fasano 25%-30% longer
than 21st at age 80
FAS/AVS % Difference
40%

30%

%

21st at age 75
D
o
n
e
a
F
c
s
r
f
i

20%

AVS at age 90
10%

Fasano 10% longer than Fasano 30% longer than
AVS at age 80 AVS at age 85
0%

Fasano same as AVS
at age 75
-10%
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Age


Underwriting Challenges
• Personnel

• Actuarial


Personnel: One Curve Says It All
(2008 VBT, Select Mortality, ALB)

Life Insurance Life Settlements
20
19
18
17
16
15
Standard Mortality

14
13
12
11
10
9
8
7
6
5
4
3 Life Underwriting is easy
2
1
Life Settlements are not
0
25 35 45 55 65 75 85

Issue Age


Personnel: Clinical Perspective
• Pulmonary Function Tests – Setting for testing

• Congestive Heart Failure – Functional Status
and Underlying Cause

• Family History – Is it relevant?

• Establishing Relative Mortality when everyone is
sick


Actuarial Issues
• Assuming that large populations – by
definition – are always good

• Not profiling to make sure populations are
comparable

• Averaging and extrapolating inappropriately


Challenges of Population Databases, like Medicare
• Based on heterogeneous population, rather than the homogeneous
population that characterizes the life settlement market
• Medicare database does not even discriminate smokers from non-
smokers
• It does not discriminate risk profile within impairment: High risk
profiles are lumped with low risk profiles
• 70% of Medicare population have incomes below $44,000 (based on
2 person household); 62% of Medicare spending is for hospital
services, managed care, home health and nursing care (used by the
sickest), while only 26% is used for physician and other fee for
services
• Because the Medicare population is a poorer and sicker
population than what characterizes the Life Settlement market, this
leads to incorrect conclusions about the slope of the survival (and
mortality) curve for most cases
• More concavity often is assumed than is appropriate

Results of Assuming Too Much Concavity
• Will lead to very high initial mortality ratings in early
durations (for low risk profiles), to be followed by a “run
off” of mortality, i.e., a lowering of mortality ratings, in the
later durations
• This pattern of mortality is appropriate for high risk
profiles, such as stage IV prostate cancer, but not for
most other diseases
• This will lead to underestimating of LE for most
diseases, with a PV adjusted LE that is even more
distorted to a short average life because of the front
weighting of cash flows
• At the same time this lumping together of cash flow
patterns will lead to an overestimation of LE for the really
extreme impairments


Prostate Cancer Survival Curves
Low Risk Means Convex Survival

High Risk is concave

Group 1: Gleason Score (GS) = 2 – 6, T1 – 2 NX
Group 4: GS = 8 – 10, T3 NX or GS = 8 -10, N +
Source: Int. J. Radiation Oncology Bio. Phys. Vol. 47, No. 3, pp 609-615


Follicular Lymphoma Survival Curves
Low Risk

Intermediate Risk

High Risk

Only High Risk Profile has Concave Survival
Source: AJCC Cancer Staging Handbook 6th Edition 2002

Cardiomyopathy: Survival Curves Based on Underlying Cause

Low Risk

Intermediate
Risk

High Risk

Only High Risk Profile has Concave Survival
Source: NEJM, vol. 342, Number 15

Low Risk Profile Impairments Have
Convex Survival
Cumulative Survival*

1200.00
100%
1000.00 As mortality
rating increases,
800.00
survival becomes
600.00 more concave
400.00
200.00
350%
0.00
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49
Years
MR 100% MR 350%

* Male, Non-Smoker, Age 70, Fasano 2008 Mortality Tables

Impact of Assuming Too Much Concavity
in Survival
180
• 86 year old male non-smoker
160
Concave Survival => extremely high • Mild, recently diagnosed type II
mortality rates diabetes. HbA1c < 7
140
• Sleep apnea treated with
120
CPAP
Deaths Per Year

100
• Symptoms of TIA. MRI showed
80
only small vessel ischemic
60 disease
40 • Mildly overweight
20
Convex Survival => more • Underwriter 1 => gross MR
0 normal mortality 155%/net MR 124% => 84
0 1 2 3 4 5 6 7 8 9 10 months LE
Years
• Underwriter 2 shows initial MR
Underwriter 1 of 596% with 46 months LE
Underwriter 2


Fasano Approach
• Physician Based Analytics

• Modified Debit Methodology

• Mortality Table Adjustments

• Research Based Clinical Judgment


Proper Personnel

1. Must be able to put reported impairments in proper clinical
perspective
2. Must have experience in underwriting extreme cases. Life
underwriters, even impaired risk underwriters, generally don’t.
3. Must be able to apply clinical judgment when the debit
methodology generates incorrect results, as it can when:
a. The insured is very, very old
b. The debits are very high
c. There are multiple impairments


The Fasano Approach
Physician Focus

1. Complexity of > 65 underwriting requires physician review
2. We prefer physicians with clinical experience & insurance
medicine experience & substandard annuity experience
3. Our physicians include former Chief and Senior Medical Directors
of major U.S. life insurance companies, such as New York Life
and First Colony Life (G.E. Finance/Genworth), John Hancock,
and Munich Re.
4. New physicians start with a small quota of easy files. All files are
reviewed by another physician or senior underwriter for quality
control. As they learn the Fasano approach and prove
themselves, they are allocated more cases and more complicated
cases.


The Fasano Approach (cont.)
The Process
1. Files are screened by senior underwriter and then assigned to
physician for review:
• Cancer cases go to our oncologist
• Most complicated cases go to our most experienced doctors
• Only easy cases go to new physicians

2. Physician reviews entire file and submits his or her analysis.
3. All physician reports are peer reviewed by another physician
4. The most complex cases will be peer reviewed by 2 or more
physicians
5. The President, VP-Underwriting or a senior physician
adjudicates any differences among the physician analyst and the
peer reviewer(s)
• All files are reviewed by at least 2 physicians
• Multiple physician review => Clinical perspective +
consistency + accuracy
• This is not subjective

Modified Debit Methodology

1.  Modified from methodology developed by insurance
and reinsurance companies for life insurance business
2.  Entails assignment of risk factors (debits) for medical
impairments and then converting the total risk factor for
an individual into an estimate of life expectancy through
the use of actuarial mortality tables.
3.  If done right, actual deaths to expected deaths will
approach 100% for a portfolio of similar risk profiles.


Modified Debit Methodology: Adjusting
Debits
1. Certain impairments move more slowly in older
people
2. The rate of progression for some impairments
will not create a problem in a senior’s remaining
lifetime
3. Risk Factors are different
4. Simple math – a fixed number of excess deaths
per thousand translates into a different
percentage for older people (who have more
deaths from other causes) than for younger
people.

Modified Debit Methodology –
Adjusting Mortality Tables
• Insurance tables overstate mortality in early
durations
• Income effect: Average income in life settlement
population is significantly greater than in life
insurance
• Lapsation effect: Healthy lives lapse out of
insurance pools; but not so for life settlements
• Insurance Tables don’t adjust slope for impact of
Mortality Rating

Higher Face Amount Means Lower Mortality
2001 VBT Actual to Expected Experience Variations by Policy Size

Non-Smokers: Policy Face Amount (000’s)

Slope of Mortality Curve
Issues:

• Life Insurance underwriting is easy,
because mortality curve is relatively flat.

• Need for formulaic debit adjustments at
older ages.

• Implication for Select Mortality Period.

• Changes in slope of mortality curve

Impact of Increasing Mortality Rating

• Shape of Mortality Curve changes as Mortality
Rating Increases.

• Most significant impact at higher Mortality Rates.


VBT 2008 Mortality Curves
Impact of Increased Mortality Rates

80 350%

250%
70

60

50
100%
Deaths

40

30

20

10

0
70 72 74 76 78 80 82 84 86 88 90 92 94 96 98 100 102 104 106
Age
100% Mortality 250% Mortality 350% Mortality


250%

350%

100%


Research Based Clinical Judgment
• Impairments where the mortality pattern bears little
resemblance to a standard mortality distribution – e.g.,
many of the cancers

• Severe impairments for which debiting is simply
inappropriate – e.g., ALS

• Be leery of “demographic” analyses based on population
data, such as Medicare. Populations must be
comparable for results to be correct.

Research Based Clinical Judgment (con’t.)

The science/art is to work from the research based
lifespan and:

a. Profile risk to put person on the proper
mortality curve

b. Measure progression along mortality curve to
estimate remaining life expectancy


Research Based Clinical Judgment:
Prostate Cancer

• T3, N0, Gleason 9 diagnosed and treated 3
years ago, with radiotherapy, in a 70 year-
old male
• How long will he live?



ICD 9 Codes do not risk
differentiate

Group 1: Gleason Score (GS) = 2 – 6, T1 – 2 NX
Group 2: GS = 2 – 6, T3 NX or GS = 2 – 6, N + or GS = 7, T1 – 2 NX
Group 3: GS = 7, T3 NX or GS = 7, N + or GS = 8 – 10, T1 – 2 NX
Group 4: GS = 8 – 10, T3 NX or GS = 8 -10, N +
Source: Int. J. Radiation Oncology Bio. Phys. Vol. 47, No. 3, pp 609-615


• 3-year survival corresponds with an 82% survival rate
• Half of 82% is 41%, which corresponds with 8.25 years
• 8.25 less 3.0 years => remaining life expectancy of 5.25 years

Research Based Clinical Judgment –
Cardiomyopathy
• Functional status and etiology
determine longevity

• Debit Manual less useful


The Heart - Simplified

LUNGS
To Body

Right A Left
From Body O
Atrium Atrium
R
T
Right A Left
To Lungs Ventricle Ventricle


Cardiomyopathy
• Cardiomyopathy is a disease of the heart muscle
resulting in a weakening of the heart muscle or a change
in heart muscle structure that may lead to heart failure

• Heart Failure can either be:
– Systolic (the impaired ability of the left ventricle to pump blood to
the body) or
– Diastolic (the impaired ability of the heart to fill with blood)


Clinical Stages of Chronic Heart

NYHA Failure
Functional Estimated
Class Characteristics 1-Year Mortality
I Asymptomatic 5%-10%

II Symptomatic; slight limitation of physical activity 15%-30%

III Symptomatic; marked limitation of physical activity 15%-30%

IV Inability to perform any physical activity without symptoms 50%-60%

Source: Heart Disease: A Textbook of Cardiovascular Medicine, 7 th Edition

Cardiomyopathy: Survival Curves Based on Underlying Cause

Source: NEJM, vol. 342, Number 15


Cardiomyopathy: Case Study
Insured: 85 year-old, male, non-smoker

Primary Impairment:

4-vessel CAD ischemic cardiomyopathy with congestive heart failure.

Reduced Ejection Fraction of 30% in 8/08.

Arteries stented in 8/08.

Most recent visit in 12/08 notable for no shortness of breath or other
symptoms.

Secondary Impairments: Diabetes, Build.

Life Expectancy as of 1/09 without any ratable impairments: 114 months.

HOW LONG WILL HE LIVE?

Case Study (cont.)

• LE is 70 months, or approximately 6 years

• NYHA Functional Class I Chronic Heart Failure
(Asymptomatic) 1-year mortality of 5% to 10%
=> LE of 5 to 10 years – say 7.5 years by
functional status

• Ischemic Cardiomyopathy median LE of
approximately 7.5 years by etiology

• Adjust down for age and for comorbid conditions
LE of < 6 years versus 9.5 years, if no
impairments.

The Future
• Will attempt to further incorporate ADLs in the
LE process

• Do not expect as significant future mortality
improvements for cardiovascular impairments
• Promising research for ALS and Alzheimer’s
• Monoclonal antibodies may produce significant
longevity extensions for many of the cancers


Impact of Rituximab (Rituxan) on
Non Hodgkins Lymphoma Mortality

© Fasano Associates 10/2012
Source: Annual Rev. Med 2008; 59: 237 250 68 Estimating Life Expectancy

Fasano Deliverables
• LE Reports with Mortality Distributions

• Special Database Analyses

• Mortality Tables

• Database

• Portfolio Analyses


Valuation Approach for Seasoned Portfolio
1. Solve for MR that fits actual portfolio mortality
2. Reunderwrite lives OR refresh old LEs to current
tables and methodology
3. Reconcile approaches 1 and 2 and project cash flows:
- The longer the portfolio history, the greater weight
to give approach 1.
- The shorter the portfolio history, the greater weight
to give approach 2.
- In an ideal world, both approaches would generate
similar results.


Illustrative Valuation Approach
• Portfolio of lives originated in the 2004/2005 time
frame with an expected portfolio duration of 7
years
• Fund manager obtained 2 LEs on each life
• Fasano LEs were used on 4% of the portfolio
• As of year-end 2011, roughly 50% of people
should have died
• Actual deaths were only 25%. What to do?


Solve for MR that fits Portfolio
Mortality
• A portfolio mortality rating of 125%, based
on the Fasano 2008 Mortality Tables =>
25.33% expected deaths as of the end of
2011
• Actual deaths were 25.34%, for an A to E
of 100% and an extremely good fit


Refresh LEs
• Although the fund had used only 4% of the Fasano LEs, Fasano had
underwritten 97% of the lives in the portfolio

• Of the lives underwritten by Fasano, LE was estimated using a Mortality
Rating approach for all but 5 lives and Research Based Clinical
Judgment was used for 5 lives

• LEs and MRs were updated to current tables and methodology for the
lives for which a Mortality Rating methodology was used

• For the 4 of the 5 Clinical Judgment lives who had died, MR was
backsolved based on date of death and Fasano 2008 Mortality Table.
For the 1 Clinical Judgment who was still alive, MR was backsolved
based on the original Fasano LE and the Fasano 2008 Mortality Table

• For the 3% of the lives not underwritten by Fasano, an MR of 125% was
assumed, based on the portfolio A/E analysis that had generated a
100% result based on 125% MR

Results
• Taking the MRs generated from refreshing the prior
Fasano underwritings and the MRs for Clinical Judgments
and files not seen as described in the prior slide =>
portfolio MR of 124.36%, a near perfect fit to the portfolio
experience based MR of 125%
• Expected death benefits were then projected by applying
the MRs from the Refreshed LE analysis applied to the
Fasano 2008 Mortality Tables and the respective policy
face amounts
• Premiums were then allocated based on the expected
mortality pattern of each life, with actuarial adjustments
made for joint/survivor policies.
• The new portfolio half life (by death benefit) was
approximately 6 years

PLEASE JOIN US!

Fasano Associates 9th Annual Life Settlement Conference

October 29, 2012

Washington, DC

Michael Fasano
Fasano Associates
1201 15th Street, NW – Suite 250
Washington, DC 20005
202-457-8188
202-457-8198 (fax)
mfasano@fasanoassociates.com
www.fasanoassociates.com


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