Speech notes on the Impact of the Financial Advisor on Investor Performance at the Advocis Symposium 2017

It was a joy to present with Paul Bourque, president and CEO, IFIC; Claire Tsai, Associate Professor of Marketing, University of Toronto; and Al Jones, Vice Chair, Advocis Board of Directors and a financial advisor at the Advocis Symposium 2017.

Key points from my talk included:

1. On Gamma:

a. Measuring Gamma is the right direction for the evaluation of the performance of financial advice

b. Measuring gamma is difficult, but it is vital to operationalize key behaviors

2. On the impact of financial advice:

a. Research demonstrates the positive impact of financial advisors on investors, however more scientific studies are necessary

3. On behavioural economics strategies for financial advisors to use to help their clients:

a. Financial advisors should look to how the unbanked manage their financial affairs out of the banking system for ideas i.e. the ROSCAs

b. Financial advisors should look to scientific research on how to nudge investors i.e. the aging simulation software that increases empathy with our future selves in order to motivate action today

c. Debiasing can help investors make better decisions

d. Technology is not necessarily beneficial if investors are looking at the performance on a daily basis and at risk of reacting to short-term trends. Technology can be helpful if it leverages in-the-moment impulses such as “Impulse savings”.

4. On Regulation and Policy:

a. It is imperative that policy makers engage in scientific research to test the impact of policies on market behaviour as there can be unintended consequences i.e. as we found in BEworks research on investor risk appetite and other research on disclosures

Taken from my notes:

1. On Gamma

· Measuring gamma is the right direction for financial advisors in terms of measuring the “value of financial advice,” a measure which goes beyond the goals of higher returns in the market, i.e., the “alpha” (Blanchett and Kaplan, 2003). Without capturing Gamma, investors may UNDERESTIMATE THE VALUE OF THE ADVISOR.

· Blanchett and Kaplan say that an advisor is adding value/”Gamma” if they are getting people to do certain things:

1. Putting money in the most tax-efficient account type and making withdrawals in a tax-efficient way (e.g. first from taxable accounts then from more tax-efficient accounts)

2. Paying attention to risk capacity (ability to take on risk) not just risk preference (aversion to risk). Investors acting without advice are likely to rely on risk preference, not capacity.

3. Appropriate annuity allocation, to avoid outliving resources — most retirees fear outliving resources (61%) more than death (Bhojwani 2011)

4. Appropriate withdrawal strategy that is updated based on market performance and the investor’s expected longevity

5. Incorporating liability into portfolio optimization. This approach is less efficient from an alpha perspective but is actually better for ensuring that people have enough money to support them in retirement

· Blanchett & Kaplan did a series of calculations with and without each of the 5 optimized strategies listed above. They found that a retiree can expect to generate 22.6 percent more in certainty-equivalent income in retirement through implementing five fundamental financial planning decisions or techniques.

· The above are behaviours, so that’s a good start for defining Gamma, but as Behavioural Scientists, we need to ask if these are the CRITICAL BEHAVIOURS, and whether these behaviours are SUFFICIENTLY OPERATIONALIZED?

Measuring Gamma means evaluating behaviours on the ADVISOR and INVESTOR SIDE

-How much coaching/effort was put in by the advisor?

-Is the coaching/effort of the advisor appropriately targeted and necessary?

-Gamma might be low if the advisor spends lots of time trying to prompt sophisticated investment behaviours in a consumer who hasn’t even got basic financial housekeeping down

-Gamma might also be low if the advisor puts in effort to change or elicit a behaviour that could be more effectively/efficiently elicited by implementing lower-effort behavioural interventions (e.g., a text message instead of an in-person meeting)

-is there a Cause-Effect relationship between the Advisor and Investors’ behaviours?

-As in, is advised investors’ success due to recommendations of their advisor?

-You could have an educated investor who tells their advisor what to do, and they tell their advisor to do all of the right things — in this case, Gamma would actually be low, despite the fact that all of the behaviours that are characteristic of Gamma, are demonstrated.

2. On measuring Impact:

-The above activities will help us to hone in on what specific behaviours advisors need to drive in the investor. Without this level of specificity, it is impossible to know what works, beyond some evidence that shows that there is something beneficial about having a financial advisor. Cases in point:

§ A recent study by Hermansson and Song (2016), shows that the use of a financial advisor has a significantly positive effect on investors’ savings behaviour. Studying the impact on savings generated by a group of Swedish investors that received advice compared to a control group that invested without the aid of a financial advisor during the study period, the study finds that the group receiving advice generated 22 per cent higher savings. SELF-SELECTION BIAS is a challenge to this study.

§ A study by Marsden et al. (2011) on retirement planning in the United States shows value of having a financial advisor. The authors examine the differences in retirement planning for individuals who use the help of a financial advisor compared to individuals who do not use an advisor. The study shows that using a financial advisor improves an individual’s savings behaviour due to the positive impact on their overall financial planning, such as awareness of retirement needs and diversification of retirement savings. In addition, the results indicate that individuals who received financial advice demonstrated some positive behavioural changes in response to the financial crisis that had hit the United States in 2008. Individuals who used a financial advisor reported that they spent more time learning about financial topics, saved more or postponed retirement.”

§ Montmarquette and Viennot-Briot (2012, 2016) also found that research participants using a financial advisor accumulated substantially more assets (173% more over 15 years) than comparable non-advised participants. They conclude that the difference is explained by higher savings rates and a greater allocation of non-cash investments which are attributed to disciplined behaviours acquired through the efforts of a financial advisor (POLLARA, 2016). While this research leveraged powerful empirical techniques, further investigation would be valuable as we continue to pursue a robust understanding of the impact of financial advice. One point worth exploring further is to understand more about the investor, in this case a deeper understanding of the research participants could be beneficial. 85% of the participants in this study declared that they had chosen a financial advisor (as opposed to having merely responded to the acquisition efforts of one). While this helps to resolve concerns about selection effects based on wealth, what it doesn’t address is the role motivation may play in explaining the adherence to sound financial planning (and therefore the strong outcomes). Motivation, then, might offer somewhat of an alternative explanation. These participants may have generated strong returns without an advisor as they may have sought alternative channels for good advice and maintained strong adherence to those guidelines. It might be the case though, that a motivated investor paired with a financial advisor is a combination that leads to strong performance outcomes. Further research ought to explore the role of motivation in the behaviour of these strongly performing investors.

3 Before we can design interventions to drive these target behaviours, we need to understand the barriers to these behaviours.

David R. Lewis, PhD, CFA conducted a survey (n=400) on a representative sample of consumers to identify factors that affect decisions about financial advice and how decision-making differs between segments.

He found that intent to seek advice explains only 54% of the variance in advice-seeking behaviour, reflecting a big say-do gap that is explained by factors such as procrastination, fear, inertia, lack of trust. Ambivalence (i.e. feeling torn between alternatives) is the biggest predictor of procrastination. Targeting this ambivalence and helping huge cohorts of unadvised customers to overcome procrastination and invest more capital may add more gamma than establishing long term client relationships.

He found that the biggest predictors of intent to seek advice are TRUST and UNDERSTANDING OF FUNCTIONAL BENEFITS OF INVESTING. Behavioural interventions can target these factors to drive advice-seeking behaviour.

David Lewis also found that predictors of intent to seek advice vary by segment.

· Men vs Women: Compared to men, women place a much lower value on the personal relationship and a higher value on functional benefits such as establishing a financial plan. Males report less financial distress than females, and report higher self-efficacy (belief that they can influence their own financial wellness). Men perceive that advisors are more opportunistic than females, so transparency may resonate more with men. Women respond more to functional benefits of advice than men.

· Over vs. under 50 years old: Trust is less important for 50+ but personal relationship with advisor is more important (This fits with the work of Stanford psychologist Laura Carstensen, showing that as we age we begin to value close personal relationships and emotional stability over novelty and material gains)

· Married vs. not married: Married people have higher intent to seek advice compared to not married people, but self efficacy is lower in married people.

3. On impacting and influencing investor behaviour:

1- De-biasing can help customers make better financial decisions.

In a study done by researchers at University of Windsor & McMaster University, decision-aids were found to be effective in reducing common biases and improving financial decision making in a laboratory setting (Bhandari, Hassanein & Deaves, 2008).

In one scenario, they measured inconsistency in asset allocation by comparing a person’s subjective risk tolerance (as measured by a questionnaire) with their objective risk tolerance (as measured by their asset allocation in a computer game. They gave participants $100,000 to allocate how they pleased, either with 2 choices (a stock and a bond) or 9 choices (corresponding to nine cells in the capital vs growth potential matrix). If there was inconsistency in the subjective vs. objective risk tolerance measures, participants received feedback like this:

People showed a huge equity gap in the 9-cell condition (because of diversification bias), but the de-biasing support message reduced their equity gap by approx. $10000.

In another example, participants were given $100000 to allocate between two stocks. The past performance of the stocks is shown, either in a biased way (stock A > stock B for 6 months) or in a less biased way (stock A > stock B for 6 months and stock B > stock A for 6 months). In the first condition, allocation was expected to be more biased by representativeness heuristic. The decision aid was a 3-year performance chart that showed roughly equal performance of stock A and stock B (below) and all participants received the aid. The optimal allocation was 50/50, and any deviation from there was considered irrational. People who saw the biased performance chart showed a bigger irrationality gap ($29020 vs. $14574) and the value of the irrationality gap decreased to ~$5500 after the de-biasing feedback.

ROSCA:

Rotating Savings and Credit Association or ROSCA is a group of

individuals who agree to meet for a defined period in order to save and borrow together, a form of combined peer-to-peer banking and peer-to-peer lending. In a typical ROSCA, the first participant to receive the draw obtains an interest-free loan; she/he receives the total draw plus imputed savings which represent interest payments normally incurred on such a loan. This amount represents an imputed income. The last recipient has saved over the entire period without receiving any interest income, obtaining the same amount saved during the period of the ROSCA. She/he receives the total draw less the imputed value of interest income which would have been received on the savings made over the period.

-People love it; they want to be nudged.

-They want that commitment, people take their paadna out of their checks first before they begin to pay bills or conduct any transactions with their pay. It compels one to save.

-They want the peer pressure because not wanting to let anyone down can have a really powerful effect on our behavior, Knowing that the banker will come round on the first of the month to collect your hand really helps you stick to the plan”.

-They want that convenience; there’s no walking into a cold bank, explaining all your business to somebody asking questions that only suit the bank; there’s no forms, there’s just an understanding and that trust makes people feel good and like they’re a part of something that is a part of their community.

-And, for a lot of reasons, it’s really hard for banks to be these things.