Setting Standards: RIIA’s Methodologies Committee
Francois Gadenne has graciously agreed to cover for me until my return on May 16. He will be contributing a variety of essays addressing contemporary and future retirement income opportunities and challenges.
Financial Advisors (FAs) need training but they also need reliable tools. During the February 2006 MRI Conference, a member suggested that RIIA set standards for software illustration methodologies such as Monte Carlo analysis. Indeed, Moshe Milvesky and others have noticed in the past that similar input in different Monte Carlo engines returned materially different outputs.
First let’s review a short history of income projection models as told by Ben Williams, co-founder of Rational Investors, Inc. and Retirement Engineering, Inc.
Advice and planning has come a long way but still has far to go:
When we entered the retirement investment advice business in 1996, it was common to find on that new Internet any number of retirement savings advisor web sites, allowing individuals direct access to a calculator to help them plan. Asset gatherers had distributed similar PC software for years. Enter a few numbers and get advice on how much to be saving, and maybe, how to invest to achieve your income goal. These were straightforward enough:
- What is your age now?
- When do you want to retire?
- How much do you earn?
- How much have you saved to date?
- How much are you saving?
Fair enough questions. But a number of these calculators would then ask:
- What returns will you get on your investments?
- When will you die?
- What will inflation be over the years until you die?
Anyone who needed help in planning for retirement knew they did not have good answers for these ‘imponderable’ questions. Further, some products we reviewed would suggest values that were wrong or, at least, imprudent. (An example: life expectancy from birth, instead of from retirement age)
The user who went along with this data request was rewarded with a retirement income projection that confused precision with accuracy: Using compound interest calculations, these projection was made to the very dollar of annual income.
The second generation of planners that we participated in (as Rational Investors, Inc.) applied Modern Portfolio Theory (MPT) and probabilities to the problem. We designed our software to eliminate the imponderable questions, and restrict the data collection to facts and data requests that the user could plausibly estimate. Depending on the approach, the results were expressed in terms of probability, either as percent chance of meeting a goal, or the income provided by a savings program expressed as an income at a given level of confidence.
It was complicated then, it seems to be getting even more complicated now. As Boomers are now entering the final stretch before retirement, the trend is to get very specific, and incorporate as much detail as possible into a retirement income plan. But this specificity means it is even more important for the user (and his advisor) to understand the assumptions implicit in any planning model.
Here is a short list of problems that we still see with conventional methodologies in the marketplace today:
- Industry models give widely different answers to the same scenarios, so how can consumers have confidence in them?
- Comparison of outputs from different models is difficult given inconsistent use of terminology and inadequate disclosure of assumptions and limitations.
- The way that market assumptions and plan results are illustrated often leads to false conclusions about risk, such as the fallacy of time diversification.
- Even though the stochastic methods of today are a vast improvement over the deterministic methods of old, many models still use stochastic techniques for investment returns only, not for other important factors such as inflation.
- While the probability of success is commonly provided as a means of conveying the level of risk in a plan, the potential magnitude of failure (e.g., how soon you could run out of money) is often ignored.
Given its “View Across the Silos” RIIA has a role to play in setting industry standards for the emerging retirement income industry. In particular, the Methodologies Committee has a view of what’s needed to remedy these problems:
- A) A set of principles (best practices) governing income projections, yet that also allows great flexibility in methodology and presentation
- B) Full disclosure of assumptions and limitations
- C) A set of industry-recognized “calibration points” to serve as a type of benchmark upon which different models can be compared. Calibration points do not in any way dictate a particular methodology, set of assumptions, or even results. They do provide a frame of reference for comparison purposes among the many different models out there. It is absolutely OK for a model to differ from these calibration points. They are for use as a means for explaining WHY differences exist.
If you have an interest in setting standards for such Methodologies, please connect directly with Richard Fullmer (Russell Investment Group), the Chair of RIIA’s Methodologies Committee. You can find his contact information at www.riia-usa.org.