Adapting Risk Profiling for Decumulation: Measuring what matters

The concept of Risk Profiling has become commonplace within the advisor's toolkit.

Despite, or probably because of this popularity, risk profiling tools have become the subject of increasing industry scrutiny, with concerns regarding the validity of the methodology and assumptions that support them:

  • One industry report highlights apparent inconsistencies in asset allocations generated by different risk profiling systems1
  • Recently, other commentators question whether existing "centralised investment propositions" are suitable for use with "decumulation" customers2,3

Debate over the use and abuse of risk profiling tools is not news. However, upheaval in the retirement savings industry accompanied by long-term low yields, and the consequent growth in customers looking to use drawdown to fund retirement income, means it is ever more important to address the questions:

  • Is our chosen Risk Profiling system valid for all customers, particularly for those in "decumulation"?
  • Does the existing Risk Questionnaire work for customers in decumulation?
  • Are the existing Fund Risk Ratings valid?
  • Do existing risk measures used to define risk profiles and "risk rate" funds make sense for decumulation?

In many cases, the answers to some of these questions may be "no".

A "Risk Framework" for Risk Profiling, Fund Risk Rating and Investment Suitability

To address these questions, we need to understand the "Risk Framework" – the methodology, assumptions and risk models – which underpins the key elements of the Risk Profiling process:

1. Customer Risk Profiles

Customers are assigned to a risk profile (e.g. "Low Risk", "Cautious"), based on a range of fact find information, typically including a risk questionnaire. Risk questionnaires are designed to measure a customer's attitude to risk, relative to a reference population. In terms of their risk aversion, where does the customer "rank" in the population. Risk profiles may be given textual descriptions which can be discussed with the customer to validate the result. This is a qualitative process, based on psychometric research and behavioral finance.

2. Fund Risk Rating

Each risk profile is characterised in terms of a quantitative risk target, based on defined risk measure(s). Typical risk measures used are volatility or value at risk, which define a probable range of portfolio returns over a given term.

A risk model, which uses mathematical equations and capital market assumptions to describe the behaviour of the risk factors, is used to quantify risk for each investment fund or portfolio, based on these same risk measure(s). This allows the fund to be "risk rated" against the defined risk profiles.

3. Asset Allocation

The same risk model can be used to identify asset allocations which maximise return for each defined risk profile. These "optimal" asset allocations will depend on an investment firm's proprietary views or forecasts for different asset classes.

4. Risk Illustration & Cashflow Analysis

It is important that the customer is given a clear explanation of "risk" taking account of their own savings objectives. Cashflow analysis is a technique used for this purpose, and is particularly well suited to decumulation.

Importantly, the Risk Framework opposite is based around a single set of customer risk profiles. The implication of this is that the definition of the risk profiles and the associated fund risk ratings do not depend on the customer's savings objectives. For example, if Fund ABC is rated "Low Risk" for a 30-year old accumulation customer, then Fund ABC will have the same risk rating for a 65 year-old customer seeking to generate sustainable retirement income.

This reflects the fact that these tools were developed to support customers accumulating wealth, but creates problems when attempting to apply existing tools in to decumulation customers.

The good news is the problem is not hard to fix.

Quantifying Risk: Why is decumulation different?

To understand what will happen if we apply our existing "accumulation" Risk Framework to decumulation, we should consider why "risk" is different for accumulation and decumulation customers.

Exhibit 1: Risk vs. Return for an Accumulation Customer (No Income)

 Risk vs. Return for an Accumulation 
Customer (No Income)

In Exhibit 1, we show a standard risk-return chart for an accumulation customer. Return is plotted on the vertical axis, risk on the horizontal axis. In this case, risk equals "value at risk" – the size of the biggest 1 year loss over a 20 year period. The different points on the line denote ten risk-graded funds, with equity allocations from 0% to 100%. The funds are equally spaced along the risk axis, from low risk (0% Equity) to high risk (100% Equity).

Exhibit 2: Accumulation Risk vs. Decumulation Risk

 Accumulation Risk vs. Decumulation Risk

In Exhibit 2, we extend this to decumulation, by making two adjustments to the chart:

  • We include income: the different lines on the chart represent increasing levels of income (as a % of the initial fund), shown in the legend on the right
  • On the vertical axis, rather than return, we plot decumulation risk – the risk of running out of money. This is a more relevant measure of risk for a customer relying on their fund to support income through retirement

If decumulation risk is the same as accumulation, we should see lines running from the bottom left to the top right of this chart.

Key take-aways:

  • Risk measures used for accumulation are not reliable measures of risk for decumulation. For example, funds enclosed in the red box (Exhibit 2) are rated "low risk" for accumulation, but are "high risk" for decumulation
  • For decumulation, risk is dependent on the income level (cashflow) as well as the asset allocation

How can the Risk Framework be adapted for decumulation?

Many Risk Profiling and Fund Risk Rating systems rely on a Risk Framework which has been designed for accumulation. As we have seen, this may not reflect the risks facing decumulation customers. The result will be risk profiles and fund risk ratings that make little sense.

The following table highlights the differences between the savings objectives, risk factors and describes the relevant risk measures we should use as a basis for the Risk Framework for decumulation vs. accumulation:

Accumulation Decumulation
Savings Objective Accumulate wealth over savings term, based on regular contributions from salary. Drawdown from accumulated retirement savings to generate a stable stream of income over the course of retirement
Success Measures
What does a "good" outcome look like?
Maximize value of wealth over savings horizon, relative to inflation Maximize sustainable income over lifetime
Relevant Risk Measures
Which risk measures should be used for "risk rating" funds?
Value at Risk: Size of fund losses in periods of "bad" investment performance Probable range for real value of wealth at end of savings term. Risk of running out of money Potential reduction in sustainable income due to a "bad" sequence of returns.

Moody's Analytics works closely with clients and partners like Capita to understand the distinct savings objectives of different customer groups. In this way, our clients can adapt their risk profiling and fund risk rating solutions accordingly.

  1. Rory Percival Training and Consultancy Ltd: An ex-regulator’s guide to Risk Profiling Tools, 2017
  2. CWC Research/Lang Cat: “Never Mind the Quality, Feel the Width 3”, October 2017
  3. Danby Bloch: Time to sort out your decumulation strategies, Money Marketing, September 2017