Life Settlement Characteristics and Mortality Experience for Two Providers

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1 Prepared by: Milliman, Inc. David Cook FSA, MAAA Glenn Ezell MS, MBA Life Settlement Characteristics and Mortality Experience for Two Providers

2 , whose corporate offices are in Seattle, serves the full spectrum of business, financial, government, and union organizations. Founded in 1947 as Milliman & Robertson, the company has 48 offices in principal cities in the United States and worldwide. Milliman employs more than 2,100 people, including a professional staff of more than 1,000 qualified consultants and actuaries. The firm has consulting practices in employee benefits, healthcare, life insurance/ financial services, and property and casualty insurance. Milliman s employee benefits practice is a member of Abelica Global, an international organization of independent consulting firms serving clients around the globe. For further information visit

3 Milliman s analysis of two life settlement providers mortality experience data from Texas Department of Insurance filings produced significant results that may be of interest to industry participants, including insurers, life expectancy estimators, providers, and investors. The data analyzed are from Life Partners Inc. and Coventry First LLC for the calendar years 2004, 2005, and Our results extend previous analysis of a portion of this data and are augmented by an actual-to-expected mortality study. We focused on senior life settlements, which we defined, for purposes of this study, to mean ages at settlement of 60 or older and not diagnosed as HIV-positive. Results summary Key results of our analysis appear below. Additional detail and other results appear in later sections. Approximately 50% of senior life settlements in the data analyzed had face amounts between $500,000 and $2.5 million. The average face was approximately $1.8 million. The average age for senior life settlement was 76 years, with well over 50% of the insureds between 70 and 79 at settlement. The average age at settlement fell over the three years, with the portion of settlements in the age range 60 to 69 increasing while the portion at ages 70 and older decreased. The average life expectancy (LE) recorded for senior settlements during the three years was 113 months, though the data suggests the average by calendar year may be increasing. The averages for 2004, 2005, and 2006 were, respectively, 101 months, 107 months, and 127 months. Approximately 20% of senior settlements in the data were transacted in the third policy year. Incidence of settlement by policy year fell steadily thereafter, producing an average policy year of settlement of nine years. The portfolios are young relative to the life expectancies of the settlements they contain. The analysis of settlement month of death less original life expectancy was inconclusive. As would be expected, deaths that have occurred so far tend to be earlier than corresponding life expectancies. Although results for the small number of senior life deaths recorded are not statistically credible, they are quite consistent from year to year. Actual deaths recorded were approximately 60% of the number expected based on life expectancies in the settlement records and the computational methodology used. Actual investor returns are likely to be lower than anticipated returns calculated using life expectancies in the data.

4 Background The primary determinant of life settlement values and portfolio performance is mortality. For investors in life settlement policies, the excess of future death benefits over required premiums and expenses is the basis for expected value. For investors in settlement portfolios, mortality not significantly lower than expected is necessary to realize anticipated returns on investment. However, actual mortality experience for settled policies is limited and, in general, not made public. Both proprietary considerations and lawsuits among participants in the life settlement industry have reduced interest in sharing and publishing experience data. The purpose of this report is to provide the industry with a limited set of life settlement mortality and statistical data now in the public domain. This report is expected to be expanded as more complete data is acquired and processed. The Texas Department of Insurance requires life settlement providers registered to conduct business in the state to report certain information concerning settled policies and deaths for their viatical or life settlements in all states. That information is a potentially useful basis for evaluating the mortality experience of a significant number of life settlement providers. The actual value of the Texas data is reduced by certain actions of the providers submitting the data and of the department itself. These actions make the information more difficult to acquire and, once acquired, more difficult to use. The results in this report are based on the Texas data for calendar years 2004, 2005 and 2006 for two providers, Life Partners Inc. and Coventry First LLC. A number of statistical measures derived from the data are presented, with commentary about significant results. In addition, an actual-to-expected mortality study was performed for settlements during the three years that resulted in deaths during the same three years. While brief, it provides useful information about the mortality experience during important early settlement years. Joseph Belth previously reported in The Insurance Forum statistical results derived from the same data source and for the same providers. His results were limited to 2006 settlements and 2006 deaths. In many cases, we selected age, amount, and other ranges for reporting results that allow comparison to Belth s results. Most differences were small. We focused on data for senior life settlements, eliminating from our analyses policies with ages at settlement less than 60 or diagnosed as HIV-positive at settlement. Our reasons for and the effects of eliminating this data are covered below. About Life Partners and Coventry First Life Partners Inc. was founded in 1991 and is headquartered in Waco, Texas. Life Partners Holding Inc. is a publicly traded company (NASDAQ symbol LPHI). Coventry First LLC is a privately held company founded in 2000 and located in Fort Washington, Pa. Both Life Partners and Coventry First operate in a number of states besides Texas. Settlement characteristics Our analysis focused on senior life settlements. Accordingly, we removed all records with ages at settlement less than 60. For Life Partners, that meant removal of 613 records and for Coventry First, 16 records. From the remaining records, we removed eight Life Partners records and zero Coventry First records for which the diagnosis in the record was HIV, so as to eliminate records that might have historically been considered viatical settlements. This elimination of records was intended to produce data that would be regarded as pertaining exclusively to senior settlements. 2

5 We made no attempt to aggregate multiple settlements on policies for the same life or lives. All settlement and death counts are, therefore, based on policies, not lives. Settlement counts are shown in Table 1. All of our analyses were performed on combined data for Life Partners and Coventry First. Table 1: Settlement counts complete Data Excluded Reason Analyzed Data Under Age not senior 0 Age 60 or Older 1,884 8 hiv 1,876 Total 2, ,876 Settlements were unevenly distributed across the three years examined. The combined distribution by count and policy face amount is shown in Table 2. Table 2: settlement distribution by calendar year total Count ,876 Face amount $909,012,247 $1,208,127,815 $1,345,570,796 $3,462,710,858 Senior life settlements are typically large policies. For the three years combined, slightly less than 50% by count had face amounts greater than $1 million. The median size was slightly less than $1 million and average face amount was approximately $1.85 million, with no clear trend. The distribution of face amounts is shown in Table 3. Table 3: distribution of settlements by policy face amount range Percentage by count of settlements in each range Face amount range total $0 to $99, $100,000 to $249, $250,000 to $499, $500,000 to $999, $1,000,000 to $2,499, $2,500,000 to $4,999, $5,000,000 to $9,999, $10,000,000 and larger average face amount $1,942,334 $1,797,809 $1,828,221 $1,845,795 Life settlements are generally perceived to be more viable as age advances. Overall life expectancies become shorter, tending to increase the discounted value of death proceeds and limit the expected premium period. In addition, the risk that an insured will live significantly longer than the life expectancy is reduced, shortening the investment horizon. As shown in Tables 4A and 4B, for the combined data, the distribution of the seniors ages at settlement peaks in the 70 to 79 range, with an average age of 76. Results by count and by volume are consistent, though results by volume show more heaping in the age 70 to 79 range. The data show some trend toward younger settlement ages. The average age at settlement fell each year from 2004 to 2005 to In particular, the percentage of settlements in the age range 60 to 69 increased at the expense of settlements at ages 70 and older. 3

6 Table 4a: Distribution of age at Settlement by count Percentage by count of settlements in each range age at settlement total 60 to to to and Older average age Table 4b: Distribution of age at Settlement by volume Percentage of volume of settlements in each range age at settlement total 60 to to to and Older average age The data indicates that life expectancies at settlement increased dramatically from 2004 to 2006, as suggested in the graph below and detailed in Table 5. The calculated average increased from 101 to 127 months, an increase of more than two years. While the percentage of settlements decreased in every range of less than 11 years and increased at all longer periods, there was a particularly noticeable decline in the percentage of LEs of five to 10 years and an increase in LEs of 15 years and longer. Longer LEs are consistent with the trend toward younger ages at settlement shown in Table 4. However, that is unlikely to be the only driver. The trend toward longer LEs could result from: Targeting of particular LE periods by the providers Changes in the settlements available in the market Recalibration of LE estimation processes Other effects PERCENTAGE OF SETTLEMENTS Less than 5 Years Between 5 and 10 Years Between 10 and 15 Years 15 Years and Greater LIFE EXPECTANCY IN YEARS

7 Table 5: Distribution of life expectancy at Settlement by count Percentage by count of settlements in each range le in months total less than to to to to to to to to to to to to to to and greater average le There seems to have been little change in the distribution of settlements by policy year. For these providers, as across the industry, few senior settlements are transacted during the two-year insurance policy contestable period. However, about one in five settlements in the data occurred in policy year three. The percentage of settlements decreases almost monotonically thereafter. In broad terms, about one-third of settlements occurred in the first five policy years, another third in the next five policy years, and the remaining third thereafter. The distribution is shown in Table 6 below. Table 6: Distribution of policy year of Settlement by count Percentage by count of settlements in each range policy year total 1 or to to to average year

8 Reported deaths The data includes, for each death, a provider-reported difference between the month of death measured from the settlement date and the LE at settlement. The results shown in Table 7 below include all deaths during 2004, 2005, and 2006, not just those resulting from settlements transacted during the three years observed. As with new settlements, we excluded deaths from settlements at ages younger than 60 and with HIV as a diagnosis. Some care is required in interpreting Table 7. First, a negative difference results from death before an insured s life expectancy, while a positive difference results from a death later than the life expectancy. This sign convention, based on a calculation of month of death minus life expectancy, is defined in the Texas Code. We discovered during the course of our analysis that a significant portion of the data was reported with opposite (incorrect) signs. Results shown in Table 7 are corrected. Second, for a closed portfolio of settlements, the negative differences tend to emerge first. Put another way, at any observation point prior to the deaths of all insureds in a cohort, cumulative deaths earlier than expected are more likely to have been observed than deaths later than expected. In a growing portfolio, this effect is magnified. Therefore, the distribution shown in Table 7 is an early result that will tend to produce more positive differences as the portfolios mature. Finally, the number of deaths increases by calendar year, due in part to the increasing number of settlements in the providers portfolios and the aging of settlements in those portfolios. An increasing number of deaths is the expected trend, though there may be contributing causes other than these. Given the relative youth of the senior life settlement portfolios observed and the average nine-year life expectancy of the settlements they contain, this pattern of the results would be expected. It shows that, of the deaths that have been recorded so far, most have occurred before their life expectancies. This analysis does not suggest that more than the expected number of early deaths has occurred. In fact, the actual-to-expected analysis in the next section suggests that is not the case. Table 7: Distribution of month of death minus life expectancy count of deaths in each range policy year total Percent -120 to to to to to to to to to to to to Total * Results biased toward negative (before LE) values because the portfolios are not mature. See the text for commentary. 6

9 Actual-to-expected mortality results Death data for 2004, 2005, and 2006 was combined with settlement data to produce ratios of actual-toexpected deaths. Several assumptions were required: Expected base mortality is the 2001 Valuation Basic Table (VBT), select and ultimate, age near birthday. Because this base mortality is scaled in a later step, the pattern of mortality in the table is important, though the actual rates are not. All insureds were assumed to be male nonsmokers for the purpose of calculating expected deaths. Neither gender nor smoking habit was included in settlement records. However, as noted above, it is the pattern of mortality that is important to the analysis. Male and female 2001 VBT nonsmoker mortality displays approximately the same pattern in the age range of senior settlements, and essentially the same pattern as composite mortality, as smoking rates are low at these ages. Actual-toexpected ratios are, therefore, minimally affected due to the uniform male nonsmoker assumption. Using VBT rates by age at settlement and the life expectancy at settlement for each settlement, we calculated the mortality multiplier necessary to reproduce the life expectancy. In life insurance terms, we determined how substandard the insured must be to have the indicated life expectancy. The calculated multiplier was then applied to VBT rates to produce expected mortality rates for each settlement. Mortality rates were applied to settlement counts and the results aggregated and adjusted for partial year exposures to calculate expected deaths. Joint policies are not identified in the settlement records. Our general experience is that fewer than 5% of senior life settlements are joint second-to-die policies with both insureds alive. In an attempt to bound the effects of joint policies and recognizing that joint status mortality is lower than single life mortality, alternate results are shown below with 5% of expected mortality removed. Actual deaths were tabulated from 2004, 2005, and 2006 settlements. Actual-to-expected ratios by count appear in Table 8 below. Although results for the small number of senior life deaths recorded (66) were not statistically credible, results are reasonably consistent over the three years analyzed. Actual deaths were approximately 60% of the number expected based on the life expectancies in the settlement records and the computational methodology used. Table 8: actual-to-expected mortality percentages by count calendar year of death Calendar Year of Settlement Unadjusted Results Total Results Adjusted to Remove 5% Potentially Joint Records Total

10 If the life expectancies were perfectly predictive, the slope of VBT mortality table rates appropriate, and the computational method an exact translator of life expectancies into expected mortality rates, actualto-expected ratios would be approximately 100%. The table above shows significantly different results. There are several potential explanations of the lower percentage: The life expectancies in the data may have a low bias due to misestimation of life expectancies during settlement transactions. A simple mortality multiplier may not be appropriate for calculating mortality rates. In particular, while some rating parameters are thought to produce such multiplicative increases in mortality, others are thought to produce more level increases. However, for this brief analysis immediately following settlement, the difference should not be expected to be significant. Some practitioners believe that insureds select against providers when deciding to accept or decline settlement offers. Specifically, for a group of insureds assigned the same life expectancy, those that believe themselves to be in the best health will be more apt to accept settlement offers. The result would be lower actual mortality, at least initially. At the other extreme, individuals that judged themselves likely to die soon would very seldom accept settlement offers. There may be a lag in reporting deaths. While a lag is probably unavoidable, we believe a significant lag is unlikely. Because these portfolios are managed, it is unlikely that deaths would go unreported for long. Many providers obtain life expectancy estimates from more than one source when valuing an insurance policy and take differences into account in some way. It is unclear what value was provided to Texas, but we would expect that the life expectancy used to evaluate the policy was provided. Investment returns to life settlement investors are reduced from expectations regardless of the reason for lower-than-expected early deaths. Not enough information is available (particularly purchase prices and premiums) to quantify the variance. It is not clear whether low early deaths indicate generally reduced mortality (and actual life expectancies exceeding expected) or whether deaths might catch up and compensate (perhaps preserving expected life expectancies). While some might occur, a full catch-up seems unlikely given the magnitude of the difference. Conclusions Several conclusions can be drawn from the Texas Department of Insurance life settlement data for calendar years 2004, 2005, and 2006 for Life Partners Inc. and Coventry First LLC. These conclusions are based only on those two companies data and may not be representative of the entire set of filings with Texas, for any other grouping of the data in those filings, or for the senior life settlement industry in general. The Texas Department of Insurance life settlement data is a potentially significant source of life settlement mortality experience. Efforts on the part of the entities required to file information to keep the data confidential, as well as the form of data provided to us, impair its usefulness. The portfolios are young relative to the life expectancies of the settlements they contain. The analysis of settlement month of death less original life expectancy was inconclusive. Although results for the small number of senior life deaths recorded was not statistically credible, actual deaths recorded were approximately 60% of the number expected based on life expectancies in the settlement records and the computational methodology used. Investor returns based on settlement values using life expectancies in the data would likely be less than anticipated at pricing. 8

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