April 2019

Why there are often several suitable recommendations

"As it is said, ‘there are more ways than one to skin a cat,’ so are there more ways than one of digging for money”
- Seba Smith, American humorist & writer, 1854

To the relief of cat-lovers (and YouTube) the ancient art of cat-skinning has been lost, along with its diverse methodologies. But the fear for financial advisers is that they, too, might be losing their 'art' — and their flexibility to explore alternative ways to 'dig for money'.

Increasingly, advisers are feeling boxed-in by regulations. Rules about how to go about giving financial advice are, generally, getting more prescriptive with limited practical insights.

The core question is: Should a client expect to get exactly the same financial advice, or plan,  from two or three different advisers?  Before you can answer this question you have to first deal with a range of tricky questions that sit beneath it.

The first set go to the very heart of the role of a financial adviser:

• Can there be two, or more, correct answers to a financial planning question?
• Does the adviser still have a professional judgement capacity to be exercised?
• If there are many correct answers, how would an adviser justify the choice of one alternative over another?

The second set of questions go to the basis of the business-model of giving financial advice:

• If financial advice becomes a 'tick-a-box' process, that always leads to the same outcome, then what value is the advice-giver delivering?
• If advisers deliver a 'cookie-cutter', commoditised approach, for how long can they charge a premium fee?

Thankfully, regulation has not yet become a total straight-jacket that ties advisers' hands. Advisers are still permitted, and required, to apply their professional judgement as they work through the alternatives that face every client.

Regulations are prescriptive around what information about clients and financial products must be gathered and 'taken into account'. But the regulations generally don't say much about what 'taking into account' means or looks like. For example, most regulation speaks of knowing the clients' risk tolerance and their goals — but how those two pieces of information are to be evaluated, weighted and used is not explained.

This 'taking into account' stage is where the door opens to advisers' professional judgement. Because, in most situations, there will be alternatives and choices that must be considered — and there is seldom just one 'correct' answer to a financial planning question.

It's well known that different people often reach different conclusions from the same set of facts, because they evaluate those facts differently. Each person may place different weights on the same fact, or interpret a particular fact in a different way.  And, of course, we rely on this diversity of opinion to produce the buyers and sellers needed to keep financial markets operating!

Similarly, it is entirely proper, and even to be expected, that a client could present their facts to different financial advisers and receive different recommendations from each of them. Each adviser will bring their own approach to gathering information, weighting its importance and using it in their own rules-based system to made decisions and recommendations — and each adviser can be fully complaint, despite these differences.  

The common theme in global regulation is that in order to give suitable financial advice or make a recommendation of a suitable financial product an adviser must:

• Know the client
• Know the product
• Have a reasoned basis for mapping the clients to the product.

However, the level of detail required for each stage varies enormously across jurisdictions.

The United States, for example has very 'thin' regulation on what information must be gathered as part of knowing your client (KYC). By contrast, the United Kingdom has the world's most detailed KYC rules — yet even the UK does not include some of the KYC factors currently under consideration for Canadian rules.

So even though everyone across different countries is doing the same thing — knowing the client — they are all doing it differently! It means an adviser in the UK must arrive at a somewhat different recommendation compared to a US adviser, because each is actually considering a different set of data.

But even within a single jurisdiction different people will take different approaches to KYC. Some will only meet the precise 'letter of the law' and go no further, while others will add extra steps to gather extra data that enables them to use professional judgement to make more informed recommendations.

In the United Kingdom financial advisers work under the world's most detailed and strict regulation and rules, where 'suitability' is a core concept. But even these rules still allow advisers to exercise their professional judgement. They are able, compliantly, to explore alternative solutions that might exist for their clients.

The concept of 'suitability' in financial advice is often misunderstood — it does not mean 'best', which would suggest there is only one correct answer. Rather, suitability means that there is a sound, factual and reasoned basis for making the recommendation or product sale.

An example helps us to better understand the concept.

It is cold out today and I don't want to catch a chill. So, I ask two friends' advice on what to wear. One suggests that I should just put a thick coat over my everyday clothes — the other advises me to put on thermal underwear. They are two very different answers to the same question, but both are quite suitable. If I follow either recommendation I will be warm. The selection of one or other option will be determined by other factors such as availability and cost.

Similarly, advisers will exercise professional judgement in constructing advice that will, inevitably, lead to a different pathway toward the goals than a plan constructed by another adviser. 

The critical test is that someone-one else must be able to review the advice and, even if they disagree with the conclusion, how it was reached.

The logic and process should provide clear evidence of how all of the dots around the advice connect to suitability for the client. This is good-practice for advice-givers who must keep comprehensive records. Not only is record keeping good business practice, it will also be crucial if the advice is ever subject to a consumer complaint or regulatory review.

Done well, professional judgement can help build the differentiation and competitive-advantage that advice businesses need to avoid the trap of becoming a commodity, where everyone's offer is the same and price is the only consideration.

We have seen how fund-manager margins are being crushed by index-fund managers, who work for just a few handfuls of basis points instead of the few hundred points their grandfathers knew and enjoyed!

Telecommunications is a great example of the price pressures and customer churn that attach to commodities. All telco connections are pretty much the same, whoever sells it to you, so people regularly change providers based solely on price. The key to avoiding the commodity price-trap is to be differentiated.

Telcos differentiate by making tweaks around the edges of their offer, like different rates and free add-ons, that make it almost impossible to make an 'apples-for-apples' comparison with a competitor.

For advice-businesses the differentiation comes from the way they work with, and extend, the regulation that governs them to produce client service and outcomes that are not 'cookie-cutter' or 'one-size-fits-all' — and which allow for premium fees to be charged.

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An Experiment Comparing Risk-Tolerance Questionnaires

John E. Grable, Ph.D., CFP® (1)
Amy Hubble, Ph.D., CFP®, CFA®
Michelle Kruger

University of Georgia
Athens, Georgia USA

Over the past several years, our research team has been testing different methods used by financial advisors to evaluate client risk attitudes. If you are currently in the practice of providing financial advice to consumers, you already know that assessing a client’s risk tolerance is a mandated activity in nearly all countries. You also know that the assessment marketplace has become intensively competitive over the past five years as more and more firms have entered the market with evaluation tools. Essentially, two approaches to assessing risk tolerance are being presented and debated by test developers: techniques based on economic modelling and assessments founded in psychometric theory. This brief report highlights findings from a study our team developed to determine which approach offers financial advisors the more valid measurement.

The purpose of the study was to compare and contrast the predictive validity of risk-tolerance questionnaires. Here is what we did. First, we asked approximately 160 people to complete an online survey. The survey asked each participant to answer a series of demographic and socioeconomic questions. Participant were asked to provide estimates of the amount they held in risky assets, like stocks, their likelihood of gambling, their investment experience, and their investing knowledge. We also asked participants to answer different risk-assessment questions.

The first set of risk-tolerance questions was based on the notion of economic risk aversion. These questions required participants to answer a series of income lottery questions. In the economics field, results from income gambles and lottery questionnaires are thought to provide insights into an investor’s revealed preference. If an advisor asks a client enough of these questions it may be possible to estimate a person’s expected utility function and derive a risk aversion coefficient. For those advisors who use a mean-variance optimization framework when making portfolio recommendations, the economic approach appears to be very efficient. Here is an example of the economic questions that were asked (2):

Question 1: Suppose that you are the only income earner in the family, and you have a good job guaranteed to give you your current (family) income every year for life. You are given the opportunity to take a new and equally good job, with a 50-50 chance it will double your (family) income and a 50-50 chance it will cut your (family) income by a third. Would you take the new job?

If the answer to this question was ‘yes,’ the participant was then asked:

Question 2: Suppose the chances were 50-50 that it would double your (family) income, and 50-50 that it would cut it in half. Would you still take the new job?

If the answer to the first question was ‘no,’ the participant was then asked:

Question 3: Suppose the chances were 50-50 that it would double your (family) income and 50-50 that it would cut it by 20 percent. Would you then take the new job?

Participants who answered ‘no’ to the first and third questions were classified as having high risk aversion (i.e., low risk tolerance). A participant who answered ‘no’ to the first question and ‘yes’ to the third question was classified as having above-average risk aversion. A participant who answered ‘yes’ to the first question and ‘no’ to the second question was classified as having below-average risk aversion. Those who answered ‘yes’ to the first and second questions were classified as having low risk aversion (i.e., high risk tolerance). Theoretically, one should expect those who score low in risk aversion to take more financial risks when faced with a choice in which the outcome of a decision is both unknown and potentially negative.

We also asked a series of traditional psychometrically-based risk-assessment items. The questionnaire used in the study was developed using classical test theory as a guide for question selection. The questionnaire has traditionally shown excellent validity and reliability. The types of questions asked were similar to ones that are included in most robust psychological measures of risk tolerance.

Several weeks later, we randomly invited 40 participants to visit our lab at the University of Georgia. Each person who agreed to visit the lab received $US10. Once in the lab, the participant was asked if she or he would be interested in an opportunity to win an addition $10 or $20 by playing a simple game of chance (i.e., a monetary risk-taking activity). The question was asked as the person stood next to a Las Vegas style craps table, as shown in Figure 1. Those who opted out of the game were compensated for their time. Those who opted in were asked a series of follow-up questions.


Figure 1. Gaming Table Used in Study.

The advantage to using a game of chance is that the odds of winning and losing a bet are predetermined. Also, games of chance add a sense of realism to risk-taking activities. The game was a simple one. Those who indicated a willingness to gamble were asked to choose between a wager that would return an additional $10 or one that would return $20. Here is the exact question:

Here is how the game works. You will be given a pair of dice to roll. You must wager your $10 gift card. In order to win $10, you must roll a 5, 6, 8, or 9.  If you roll any other number you will lose $10. In order to win $20, you must roll a 2, 3, 4, 11, or 12 to win; if you roll any other number you will lose $10. Which game would you like to play?

Each person’s choice was recorded. Participants were then allowed to take a practice roll of the dice. This was followed by the interviewer providing details about the true odds associated with the selected wager. Participants were allowed to change their bet, however, few moved off of their original choice.

At that point, participants played the game and either won or lost. It is important to note that the game was rigged, although participants did not know this at the time. Everyone left the game with US$30, even those who lost the wager and those who won only US$10. In other words, participants did not know prior to the game that they were guaranteed to leave with $US30, which gave the game a sense of reality. Participant behaviors related to the game were used as a way to validate the scores obtained from each participant on the economic and psychometric risk assessments.

Our team’s findings are somewhat controversial. So, it is important to say, at the outset, that this study was exploratory. If time and funding permits, we would like to use a larger sample and increase the incentives for participation. Nonetheless, financial advisors may want to consider the findings from the study in the context of the tools they are using to measure client risk tolerance.

As a reminder, those who scored highly in terms of risk tolerance—regardless of which assessment approach was used—should have exhibited a willingness to play the risky game. Risk tolerance scores should also have been positively correlated with other measures of risk taking, including the likelihood of gambling, investment experience, and investment knowledge. It turns out that only psychometric theory-based risk-tolerance scores were predictive of actual behavior. Equally interesting was the finding that only psychometric test scores were positively correlated with the other indicators of risk tolerance. Specifically, scores from the psychometric scale were correlated with knowledge of casino games, the likelihood of gambling, financial decision making experience, and investing knowledge, as well as participant holdings of cash and equities. Scores from the economic test were not predictive of behavior or correlated with the other measures of risk taking.

These findings should give pause to financial advisors who are considering adopting traditional relative risk aversion approaches as a means of assessing a client’s risk tolerance. A key reason to use a risk-tolerance tool is to anticipate who, among a group of clients, will be the most or least willing to take financial risks. The economic-revealed preference approach provided very little predictive power. The psychometric questionnaire was the only measure to predict who was more likely to participate in the risk-taking game where the outcomes of the game were potentially negative—a situation similar to what investors face in the markets.

Results from this exploratory study suggest that a questionnaire developed using psychometric theory is likely superior in terms of predicting financial risk taking behavior, at least when compared across the measurement techniques examined in the study. One takeaway from the study is that a financial advisor should ask for and receive information from a test developer about the validity and repeatability of the tool being presented and sold. If a test developer can prove these elements, then the selection of one assessment approach over the other should come down to advisor preference and theoretical training.