Data Analytics Firm Develops Variable Annuity GLWB Value Ratio
The highest GLWB benefit value number analysts calculated was 38% higher than the lowest.
Hedgeness Inc. has come up with a new tool for comparing variable annuity contracts: a standardized expense-to-benefit ratio for variable annuity guaranteed lifetime withdrawal (GLWB) benefits riders.
Analysts from the Chicago-based data analytics services firm showed off their GLWB value indicator earlier this month, in a report comparing the value of the GLWB riders available with seven different VA contracts.
The analysts found that:
- The expense number for the GLWB rider with the highest expense number was 25% higher the number for the rider with cheapest expense number.
- The highest benefit value number was 38% higher than the lowest benefit value number.
- The highest expense-to-benefit ratio was 28% higher than the lowest expense-to-benefit ratio.
The GLWB rider expense ratios varied less than the benefit value number because riders with a higher benefit value numbers tended to have somewhat higher expense ratios than the riders with lower benefit value numbers.
(Related: Advisors Said These 4 Things Might Increase Annuity Sales)
A copy of the full report is available here.
Analysts at Hedgeness started by defining a hypothetical rider purchaser.
They assumed, for example, that the hypothetical purchaser is a retiree couple, with the older spouse or partner being 65 years old. They also made several assumptions about how the couple would make withdrawals, and how the couple would allocate the underlying GLWB assets.
The analysts developed a rider expense figure that includes the effects of mortality and expense fees, administrative fees, sub-account investment management fees, and GLWB rider fees.
The analysts came up with a more elaborate process for calculating a GLWB rider benefits value number.
The come up with the benefit value number, the analysts started with factors such as the GLWB guaranteed withdrawal rate and the time horizon of the guarantee.
The analysts then created a hypothetical VA portfolio, with derivatives used to support the guarantees. They ran the portfolio through a scenario generator.
To account for the risk that an issuer might default, the analysts adjusted the final benefit value number to reflect the issuer’s credit rating.
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