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.

Contact:

Timothy Paris

timothyparis@ruark.co

860.866.7786


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.

Contact:

Timothy Paris

timothyparis@ruark.co

860.866.7786


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.

Contact:

Timothy Paris

timothyparis@ruark.co

860.866.7786