1. Longevity 12
Chicago 2016
Importance of High Quality Data for Underwriting Pension Risk Transfer (PRT) and Longevity Reinsurance Transactions
Thomas Jones
Prudential Financial, Inc.
Primary Competency:

2. Disclaimer
Views expressed as part of this presentation are my own and do NOT represent those of Prudential Financial, Inc.
The numbers in this presentation are for illustration purposes only. Reading into them may only yield academic knowledge.

3. Agenda Why Data is important for PRT and Longevity Reinsurance
Background: What goes into setting Mortality and Marital assumptions
Case Study I – Number of Deaths
Case Study II – Number of Exposures
Mortality Improvement Assumption

4. Why Data is Important for PRT and Longevity Reinsurance
The quality of Mortality and marital data is critical to accurately assess the value of liabilities. For a PRT transaction, where there is a single premium paid upfront, the assumption set applies for the next years and hence it becomes paramount to get accurate data.
Life expectancy off by 3 months for a 70 year old is worth more the 1% in liability amount.
Insurance companies lose capital
Expected profits are not realized and stock price could fall
Mutual insurance companies could see their solvency ratios drop
All firms with pension plans see their funding ratios drop

5. Background I: What goes into setting Mortality assumption
Base Mortality Table:
Varies from one population to another
Differences attributable to different working conditions, geographical locations, level of benefits, industries, etc.
Qx’s generated by age and gender in any given mortality study are impacted by:
Number of deaths recorded in the experience period, and
Total amount of “exposures” for the given population
Mortality Improvement Assumption:
Data available from sources such as Human mortality database (HMD), Social Security Administration (SSA), Medicare (CMS), Center for Disease Control (CDC)
Does Mortality Improvement vary by population within a country and even across countries in the long run?

6. Background II: What goes into setting Marital assumption
Critical Assumption for Longevity Reinsurance transactions
Spousal benefit is for the spouse as of the primary participant’s date of death rather than the retirement date
Presents tail risk in liability
Most of the data sources on marital assumption do not capture “young spousal risk”
“Direct survey” data preferable to general data sources where appropriate judgment needs to be employed

7. Case Study 1: Company ABC – “Number of Deaths”
ABC Pension plan had ~20,000 participants – an average age of 75
Anomalies in the early years where the “rate of mortality” was low
Further data review led to a better pattern of deaths

8. Case Study 2: Company XYZ – “Exposures”
Exposures for a given population are determined by when a participant “enters” the mortality study and “exits” the mortality study
There are several issues that are common with the exposures aspect:
Lag in dependent/new retirees deaths
Under-reporting of dependent deaths within same year deaths
Unknown entry dates

9. Mortality Improvement Assumption – Data Sources
Publicly available data sources
Centre for Disease Control (CDC)
Social Security Administration (SSA)
Industry tables (MP2014 and 2015) used SSA
Human Mortality Database
Privately available data source
Medicare (CMS)

10. Mortality Improvement Assumption—Data Sources and Results
Below is a comparison of average improvements between 2000 and 2010 for various ages and data sources:
While there is not as much differentiation between the data sources in ages 65-75, we see differentiation emerge for ages 80 and beyond

11. Important Disclosures
This document has been prepared for discussion purposes only. Prudential Financial, Inc. (PFI) does not provide legal, regulatory, or accounting advice. An institution and its advisors should seek legal, regulatory, investment and/or accounting advice regarding the legal, regulatory, investment and/or accounting implications of any of the strategies described herein. This information is provided with the understanding that the recipient will discuss the subject matter with its own legal counsel, auditor and other advisors. This document does not constitute an offer or an agreement, or a solicitation of an offer or an agreement, to enter into any transaction (including for the provision of any services).
Insurance and reinsurance products are issued by either Prudential Retirement Insurance and Annuity Company (PRIAC), of Hartford, Connecticut, or The Prudential Insurance Company of America (PICA), of Newark, New Jersey. Both are wholly owned subsidiaries of PFI, and each company is solely responsible for its financial condition and contractual obligations. PFI of the Unites States is not affiliated with Prudential plc, which is headquartered in the United Kingdom.
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