The historically low interest rate environment that kicked into high gear after the Great Financial Crisis began fourteen years ago compelled an array of annuity products today that are dizzying in scope. And that has created a paradox of choice for consumers and those who advise them.
The existential threat that low rates created for annuity manufacturers compelled a wave of innovation like never before, and we are now drowning in a sea of product choices that often blur the lines of value proposition. To wit, we now have not just indexed annuities with simple indexes; we have custom volatility controlled indexes of every stripe, the common thread being some combination of equities, fixed income, cash, and perhaps commodities, with allocation wizardry quarterbacked by rules based black box recipes that span the gamut. One can also "buy up" more upside potential via a fee, and can opt for interest crediting annually, or for longer durations, such as every two years or even every five years.
We also now have a growing crop of structured annuities with both floors and buffers, participation rates north of 100% in many cases on an array of indexes, some with caps, some without, and the list goes on and on. This product proliferation has spawned an explosion of choice and an increasing risk that a suboptimal choice is selected.
Our industry has access to the data required to make better choices, but are we using that data to best effect - developing decision analysis tools with that data - to answer the right questions in the pursuit of improved annuity choices?
Sheena Iyengar, S.T. Lee Professor of Business at Columbia Business School, is a recognized expert in the art of decision making. She helped coauthor the 2003 study: "How much choice is too much? Contributions to 401 (k) retirement plans", which was published in a Pension Research Council working paper and coauthored by Gur Huberman and Wei Jiang.
In a recent article, she was quoted as follows:
"We are constantly collecting data and data and data. We see data as the answer provider. Data unto itself does not help us; it could actually overwhelm and distract us. You have to ask yourself first what the question is that you want to ask, and then see if you have the data that could help answer it."
I thought about this in the context of our industry. For example, a quick glance on AnnuitySpecs this morning of three established issuing companies showed each having between 40 and 50 actively sold products, and most of these were fixed, fixed indexed, and registered index linked varieties. While some of the product variations were channel specific, the fact remains that wholesalers whether in a channelized or dechannelized model are now tasked with expert discernment and articulation of the value proposition of all of these product categories and choices within. The advisers they serve expect and want this level of discernment and counsel, as do the clients in turn served by the advisers.
But do annuity manufacturers and their sales forces have the data and tools to accomplish that level of discernment? For example, Is a RILA with a floor and a cap on a given index over a a given interest crediting period a more appropriate choice for the broad mandate of "risk managed accumulation" than a FIA with a custom index and a par rate over the same period? Can we use more dynamic data in the development of analysis tools, such as current equity market valuations relative to long term averages, or the current rates environment within the context of a tightening or easing cycle?
Our industry has an amazing array of powerful solutions. The question is, have we developed the data that insurance companies have access to in spades to develop the analysis and decision-making tools to help customers, advisers, and wholesalers make the most informed and thus optimal product and allocation choices to meet their goals?