Stat and GAAP: raising the bar for data analysis and policyholder behavior modeling

Whether VM-21 for variable annuities, GAAP LDTI, or the prospect of VM-23 for fixed indexed annuities, regulatory changes are raising the bar for data analysis, use of relevant industry data, and policyholder behavior model development.  Let's discuss how our industry studies, benchmarking, and customized model development services can help you.


Timothy Paris


How much is 1% A/E improvement worth to you?

For deferred annuities, minimizing hedge breakage is a key risk management objective.  Here is a simple example showing how a seemingly modest 1% improvement in actual-to-expected ratios can dramatically reduce hedge breakage, even for small- to medium-sized blocks.  How to do it?  By expanding on your own company's experience data to use relevant industry data and credibility theory to improve policyholder behavior models.

This is what we do.  Our work is not an expense, it is an investment in risk management with quantifiable benefits.  Let's discuss exactly how this can work for you.


Timothy Paris


Case study - modeling FIA GLIB income commencement

Download the case study here:  Ruark - case study - FIA income commencement using credibility theory and PA

Quantifying the benefits of using your company data, industry data, and credibility theory in a predictive analytics context.  This case study is focused on FIA GLIB income commencement but the approach works similarly well for other products, riders, and policyholder behaviors.  Our experience is that the financial benefits can be 1000x greater than the costs.  Let’s discuss exactly how this can work for you.


Timothy Paris


New VA and FIA mortality tables, splits for benefit type and durational anti-selection

I am very pleased to announce that we have released new industry mortality tables for variable annuity (VA) and fixed indexed annuity (FIA) products. Building on the industry studies and tables that we have produced since 2007, the new tables are derived from our 2018 studies of VA and FIA mortality and are an expansion of this work for specific VA rider types and for FIA. They include a table for VA contracts with lifetime withdrawal benefits (“RVAM-LB”); a table for VA contracts without living benefits (“RVAM-DB”); and a table for FIA (“RFIAM”) in aggregate. All are single-life mortality tables.

• The RVAM-LB table incorporates 34 million exposure years and 320,000 deaths on VA contracts with guaranteed lifetime withdrawal benefits (GLWB) or hybrid GMIB. The table is calibrated to experience in contract durations 3 and later, with select factors for the earlier durations. This reflects key findings from our 2018 study - GLWB and hybrid GMIB mortality is lower than average at issue and rises to an ultimate level over time.

• The RVAM-DB table incorporates 29 million exposure years and 523,000 deaths on VA contracts without living benefits. The table is a select-and-ultimate table with a 5-year select period. This reflects key findings from our 2018 study - VA contracts without living benefits, primarily with death benefit (DB) only, have higher mortality than average at issue and the magnitude of anti-selection varies by issue age.

• The RFIAM table incorporates 16 million exposure years and 265,000 deaths on FIA contracts, both with and without lifetime income riders. Similar to RVAM-LB, the RFIAM table is calibrated to experience in contract durations 3 and later, with select factors for the earlier durations reflecting lower mortality consistent with findings from our 2018 study.

These new tables are purpose-built for deferred annuities, and are demonstrably better than standard industry tables for VA and FIA valuation -- they reflect not only the effects of age and gender, but also differences by product type and contract duration which are important components of mortality anti-selection.

We are making the new tables immediately available, free of charge, to clients who have already purchased our respective 2018 VA and FIA mortality studies. New purchasers of the these studies will also receive the tables.

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

Please contact us if you would like to learn more.

EBIG Conference: using predictive analytics to model annuity policyholder behavior

Here is our presentation from session 2B of the EBIG Conference in November 2019.

It includes an exploration of drivers, cohorts, and dynamics for policyholder behavior for VA and FIA based on industry experience data, including changes in recent years and the emergence of long-term data in key areas.

Moreover, we discuss critical elements to developing a sustainable and coherent framework to translate this complex experience data into assumption models.