Files and links (1)
Ben_Lim_Thesis_deposit31.46 MB
Embargoed Access, Embargo ends: 01/31/2027
Dissertation
On evaluating medical underwriting in life settlements and mortality table development
University of Iowa
Doctor of Philosophy (PhD), University of Iowa
Spring 2022
DOI: 10.25820/etd.007726
Abstract
The life settlement industry is the secondary market for life insurance. The valuation of policies in the life settlement market hinges upon life expectancy assessments provided by medical underwriters. As accurate assessments are essential to the market's well-functioning, determining so is of interest to various stakeholders, including regulatory bodies. There has been some recent interest in better alternatives to the traditional metric for this quality, the A/E ratio: the ratio of actual to expected number of deaths. One such alternative is the Implied Difference in Life Expectancies (IDLE) metric. Its design largely retains the simplicity of the A/E ratio while being informative, unlike the A/E ratio, throughout the life of a policy block. Even though the IDLE is a significant improvement over the A/E ratio, it requires the mortality distributions of the insureds as an input, which may not be available in practice. Our proposed methodology utilizes informative covariates derived from the life expectancy assessments, in conjunction with an appropriate survival model, to estimate the mortality distribution of the insureds. We show that our proposed metric -- the average deviation of the life assessments from those derived using this model -- is a robust yet well-performing alternative to both the A/E ratio and the IDLE.
As a third party to settlement transactions, medical underwriters, and hence their auditors, have to rely on public sources in compiling mortality data on underwritten insureds. Such acquired data is known to contain a significant proportion of unreported deaths. Accurate accounting for their presence is crucial to a fair evaluation of an underwriter's methodology. However, existing methods for doing so either rely solely on actuarial opinion or are based on assumptions untenable in the life settlement context. Towards developing a practical data-driven methodology for consistently estimating mortality in the presence of unreported deaths, we propose the IBNR (incurred-but-not-reported) rate model. This adaptation of the cure rate model importantly accommodates the heterogeneity in the rates of both mortality and unreported deaths seen in practice. Our methodology thus facilitates an accurate and objective evaluation of an underwriter.
Developing mortality tables can be challenging especially for smaller life insurers, who lack credible experience data or the expertise to adjust raw mortality rates. The recently proposed entity embedding neural network (EENN) methodology aims to resolve this issue by extracting features from industry tables reflecting such information for use in fitting mortality rates for such firms. Notably, such fitted rates do not incorporate desired monotonicity constraints e.g. with respect to attained age. We extend the EENN methodology to do so, which has the added benefit of regularizing rates for actuarial use.
Details
- Title: Subtitle
- On evaluating medical underwriting in life settlements and mortality table development
- Creators
- Hong Beng Lim
- Contributors
- Nariankadu D Shyamalkumar (Advisor)Daniel Bauer (Committee Member)Thomas Berry-Stoelzle (Committee Member)Elias SW Shiu (Committee Member)Sanvesh Srivastava (Committee Member)
- Resource Type
- Dissertation
- Degree Awarded
- Doctor of Philosophy (PhD), University of Iowa
- Degree in
- Statistics
- Date degree season
- Spring 2022
- DOI
- 10.25820/etd.007726
- Publisher
- University of Iowa
- Number of pages
- xv, 190 pages
- Copyright
- Copyright 2022 Hong Beng Lim
- Language
- English
- Date submitted
- 04/25/2022
- Description illustrations
- illustrations (some color)
- Description bibliographic
- Includes bibliographical references (pages 158-170).
- Public Abstract (ETD)
During the outbreak of AIDS in the eighties, many Americans with dire health prognoses unsurprisingly also encountered mounting medical costs. With patients’ lifetimes often less than two years, their life policies became valuable assets with actuarial values close to their death benefits. However, lacking a contractual pathway to unlock this value and facing lapsation due to unaffordable premiums, the prospect loomed of being shortchanged to a much lower contractual surrender value. The life settlement market was born to address this urgent need by offering a more equitable buyout.
With AIDS becoming a chronic disease, the settlement market has morphed to cater to seniors with impaired health. The key for this market to thrive is fair buyout values, requiring accurate life expectancy assessments by medical underwriters. Evaluating the accuracy of their assessments is hence of much interest to regulators and to themselves towards improving their processes. This thesis’s main contribution is its improved methodologies for such an exercise, broadly contributing to ensuring the market’s continued high quality of service to society. Small life insurers tend to cater to a geographical, population, or product niche and thus help promote accessibility and lower costs. This, by their very nature, much distinguishes their insured base from that industry-wide, necessitating custom mortality tables. On the other hand, their size restricts the resources and expertise available for developing such tables. This thesis also provides a methodology to construct such tables in a semi-automated manner by leveraging upon the expertise built into industry tables.
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984774767302771
Metrics
12 Record Views