Policyholder Behavior is the focus at this SOA seminar

We will be presenting at the Bridging the Gap seminar on Nov 10, which leads into the Equity-Based Insurance Guarantees Conference Nov 11-12. Hope to see you there!


Unlocking -- feel like you've done this before?

My fellow actuaries, I think there is a better way.  Let's discuss "How to Get Real Results in Policyholder Behavior Modeling" at session 134 of the SOA Annual Meeting.


Join me at this ACTEX webinar - Data Analysis and Modeling for Long-Term Products

https://actexmadriver.com/orderselection.aspx?id=453145085

In this webinar, we will explore the difficulties of analyzing experience data for long-term products that are early in their lifecycle and translating this data to assumption models. These issues are endemic to any new product line and are evident across many large and important segments of the life and annuity landscape, including post-level term mortality and variable and fixed indexed annuity lifetime income guarantees. As a case study, we will utilize actual industry-level policyholder experience data from the US annuity market to explore the key drivers, interrelationships, and market segments. Following this, we will put ourselves in the position of an actuary working for a company in this market and analyze a company's experience data. Then we will develop and calibrate assumption models to this data, mindful of credibility limitations and risks of over-fitting data. Finally, we will show how relevant external data can be incorporated to refine the model, and how to quantify the cost-benefit of accessing this data and improving a company’s risk management.


Obstacles to annuity reinsurance deals?

I'll be speaking about how to deal with one of the biggies -- policyholder behavior assumptions -- at the 2019 SOA Reinsurance Seminar on Sep 24-25.  Hope to see you there.


The Use of Predictive Analytics to Set Valuation Assumptions

I will be one of the speakers at session 39 of the SOA Valuation Actuary Symposium, which will cover this hot topic for annuities and other product lines.  Hope to see you there.


Super Models - SOA webcast

August 2, 2019

12:00 - 1:30pm Eastern

Register

I will be the presenter at this SOA webcast.  If you like me, Super Models, or continuing education credit, this is the webcast for you!

What is a "super model"? In this context, super models are developed based on rigorous data analytics techniques, and they provide a range of potential outcomes and financial metrics that can be used to evaluate when material changes are necessary. “Assumptions” can be extracted from super models for various applications, but the super model itself is more robust than that. It is a framework for analysis and risk management, not a point-in-time set of numbers.

This session will emphasize data visualization and communication of highly technical concepts to colleagues and non-actuarial stakeholders. There will be examples based on industry-level policyholder behavior data from the U.S. annuity market, but the concepts transcend product lines.


Ruark Releases 2019 Variable Annuity Study Results

Increasing data exposure in key areas

Ruark Consulting, LLC today released the results of its 2019 industry studies of variable annuity (VA) policyholder behavior, which include surrenders, income utilization and partial withdrawals, and annuitizations.

“Data exposures in key areas have increased considerably since last year’s studies, allowing for more detailed analysis and higher credibility of results,” said Timothy Paris, Ruark’s CEO.

Among the notable increases in exposure:

  • Nearly double the exposure in years 11 and later, including income commencement behavior after common 10-year deferral incentives for guaranteed lifetime withdrawal benefits (GLWB).
  • 12% increase in exposure for in-the-money GLWBs, following equity market declines during the fourth quarter of 2018.
  • 29% increase in exposure for guaranteed minimum income benefits (GMIB) past their waiting period.

Total data comprises 85 million years of exposure and 14 million policyholders from 24 participating companies spanning the 11-year period from 2008-2018, with $795 billion in account value as of the end of the study period.

Highlights include:

  • GLWB deferral incentives appear to be effective. Income commencement rates are low overall; about 12% in the first year and falling to about half of that in years 2-10. However, commencement rates more than double in year 11 with the expiration of common 10-year bonuses for deferring income, before falling to an ultimate rate.  The pattern for GMIB is similar, although somewhat muted. After commencement, continuation rates are over 80%.

  • Annual withdrawal frequency rates for GLWB and GMIB have continued to increase and have become more efficient with approximately 60% of recent experience at the full guaranteed income amount.

  • The effects of "moneyness" (account value relative to the guarantee base) on partial withdrawal behavior differ depending on circumstances. Income commencement rates increase when GLWBs are more in-the-money. This effect is quite pronounced after the expiration of common 10-year deferral incentives, with commencement rates ranging from low single digits to nearly 40% depending on moneyness. At all durations, when guarantees move out-of-the-money, withdrawals in excess of the maximum amount are more common, which is suggestive of policyholders taking investment gains out of the contract.
  • On contracts without GLWB or GMIB, free partial withdrawal amounts increase after the end of the surrender charge period, similar to the familiar “shock” in surrender rates.

  • Surrender rates have not returned to 2008 levels, even as strong equity market performance has boosted account values in recent years. Newer sales include more GLWBs which have strong incentives for persistency. Also, VA writers de-risked their product offerings in the wake of the 2008 financial crisis and the low interest rate environment has reduced the attractiveness of non-VA investment alternatives.

  • Three surrender regimes are evident during the study period: surrenders at the shock duration were nearly 30% at the onset of the 2008 economic crisis, and in a range of 12-16% subsequently except for 2016 when they reached their nadir below 10%. The 2016 dip is believed to be the result of uncertainty surrounding the DOL’s proposed Fiduciary Rule and other political factors.
  • Contracts with GLWB and GMIB have much lower surrender rates, and this effect is even more pronounced for those limiting their partial withdrawals to the guaranteed income amount.

  • Policyholders that take systematic withdrawals on GLWB and GMIB exhibit a select-and-ultimate effect, with very low surrenders in the first systematic withdrawal year and increasing thereafter. In the fourth systematic withdrawal year and beyond, surrender rates are comparable to those of contracts that have not taken any withdrawals.
  • When calculating relative value for GLWBs, use of a nominal moneyness basis (account value relative to the GLWB benefit base) can be deceiving, since it fails to reflect important aspects of the product’s economics. Therefore, it may be preferable in many cases to use an actuarial basis that incorporates interest and mortality rates. Surrenders exhibit a dynamic relationship to moneyness, whether measured on a nominal or actuarial basis. On a nominal basis 81% of GLWB exposure is in-the-money, whereas on an actuarial basis only 11% is in-the-money.

  • Annuitization rates for GMIBs are in the low single digits and continue to decline. “Hybrid” versions that allow partial dollar-for-dollar withdrawals have much lower rates than traditional versions which reduce the guarantee in a pro-rata fashion, especially in the first year of eligibility. Factors influencing annuitization rates include age, duration, last year of eligibility, death benefit type, contract size, and moneyness.

Detailed study results, including company-level analytics and customized behavioral assumption models calibrated to the study data, are available for purchase by participating companies.


2019 VA industry studies are coming

This year's VA industry studies of policyholder behavior (surrenders, partial withdrawals and income utilization, and GMIB annuitization) should be complete and delivered to purchasers in mid-June.

If you have not yet decided, we continue to see significant increases in exposures and credibility in key areas that are critical for assumption models:

Total exposure years: 85 million (+5.1% since last year)
GMIB (10yr) exposure years: +28.7%
GLWB in-the-money by 25% or more: +12.3%
GLWB income commencement exposure in years 11 or later: +94.5%

With all of this data in our studies, we can identify key factors of influence and interactions that are typically not evident at the individual company level, even for large blocks. Moreover, we can use this data to develop and calibrate customized behavioral models that are readily implementable with sensible factors of influence, strong goodness-of-fit, and dramatically improved predictive power in terms of A/E ratios. This is not a budget question, it is an investment in risk management with quantifiable benefits. You can check this out as part of our Premium service option.

Also, data gathering is in progress for new industry studies for payout annuities (incl. GMIB/GLWB post-annuitization, SPIA, and structured settlements, respectively), fixed deferred annuities, and the growing market of structured/indexed variable annuities.

Details and pricing are available upon request, including all of the above along with our 2019 FIA studies and triennial (2018) VA and FIA mortality studies. Please contact me with your purchase decisions or if a discussion would be helpful. We will be back in touch in a few weeks when the VA study results are available.

On behalf of our team, thanks for your ongoing support! Talk to you soon.

Tim

timothyparis@ruark.co

860.866.7786


Pictures of Super Models

Delighted to contribute this cover article to The Modeling Platform newsletter of the Society of Actuaries Modeling section.

And thanks to those of you who attended my presentation at session 08 of the Life & Annuity Symposium this week, which was in a similar vein.

Please contact me at timothyparis@ruark.co if you would like to learn more about how we use industry-level data and techniques like these to develop a cost-benefit equation for data, and quantifiably improve actuarial models and risk management.