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Of all the variables we routinely measure in our behavioral assessments, our research shows that one most accurately predicts risk-taking – overconfidence. It’s time that advisors systematically identify their overconfident clients and develop skills to overcome the bias it breeds.
Risk is one of the most important considerations for portfolio construction and management. Financial advisors need an accurate view of a client’s risk appetite to draw appropriate financial plans. Risk is generally thought of in relation to risk tolerance, which refers to the degree of risk that an investor is willing to endure in the pursuit of a financial objective. It is often influenced by the individual’s experience and perception of the market. To assess risk tolerance, an advisor typically asks clients to rate themselves on a scale or complete a more comprehensive risk assessment. This score is then considered alongside other factors, such as the client’s capacity to take risk.
The role of financial advisors is changing to reflect a decreased emphasis on pure investment advice, due to automation and the democratization of finance. As a result, advisor-initiated risk profiling can provide value beyond portfolio construction if it is also used to inform marketing, communication and client-relationship management. This requires deeper insights into client mindsets, which more “behavioralized” risk-tolerance instruments can provide.
Behavioralizing risk tolerance requires advisors to:
- take into account important behavioral aspects of risk tolerance, such as loss aversion, as well as other psychological factors, such as overconfidence and how individuals deal with uncertainty and regret;
- use behaviorally meaningful methodologies that best predict investment decisions, such as questions asking people to make trade-offs, scenarios to gauge their behavioral reaction, or real-life trading behavior; and
- take a more holistic approach by ensuring a mutual understanding of risk based on the client’s experience and behaviors, as well as hopes and fears.
One psychological factor that is easily overlooked even in behavioral-risk assessments is overconfidence. People with this bias are overly optimistic, particularly with respect to their own skills and competencies. This may lead them to overestimate the likelihood of positive financial outcomes. Investors with excessive confidence may under-diversify and overtrade.
Data we have collected on a representative sample of working-age Americans shows the important role played by overconfidence in relation to risk tolerance. When we analyzed the data, we found the usual relationships between risk tolerance and demographic characteristics: Being male, younger, more educated and high-earning are all associated with greater willingness to take risks. We also looked at investment knowledge and time preferences. Results suggest that greater financial literacy makes people more cautious, reflected in somewhat lower risk-taking. The same is true for people with greater patience: Those who prefer payoffs in the future over smaller but immediate rewards tend to be more risk averse.
When we added our measure of overconfidence to the mix, the effect of most other variables weakened, while the effect of financial literacy and income was no longer statistically significant.
Overconfidence stood out as the strongest predictor of risk-taking.
The link between overconfidence and risk tolerance is not a new discovery (see this example in the Journal of Investment Consulting). But our data demonstrates the vital psychological role of overconfidence relative to other factors in the way people perceive risk. Controlling for the effect of all other variables we measured, we found that a person’s risk-taking score, expressed as a percentile, is about 10 points higher for a person with high (top tertile) overconfidence than one with moderate (middle tertile) overconfidence.
This creates two challenges for financial advisors with overconfident clients. Advisors may need to readjust their assessment of clients’ risk tolerance in light of this excessive confidence. They must also figure out how to work with overconfident clients who may resist their recommendations.
The first challenge is an ambitious, but important one. Its aim is to answer one key question: How realistic are this client’s risk preferences? While risk capacity sheds light on the same question from an objective point of view, overconfident risk tolerance implies a subjective bias.
The second challenge is trickier. How do you make overconfident clients realize that they are overconfident without deflating their egos?
When it comes to confidence, it’s not just about one side of the spectrum; dealing with clients who lack confidence could be difficult as well. Underconfident and risk-averse clients are highly likely to have a status quo bias. Hence, a key challenge is to get them to act by helping them view risk from a broader perspective than just via a negative frame of loss. How can you get underconfident clients to get more confident without sounding condescending?
All this boils down to the manner in which advice is given. An advisor should approach the problem as part of a more elaborate behavioral analysis, where the intention is not to point fingers, but to develop a thorough understanding to serve better. This could be a great way to not only build deeper client relationships, but also help them work on their biases to become better financial decision makers. The idea is to enable client education by increasing their self-awareness and getting them to become more reflective without taking a direct, confrontational approach.
You can build rapport if you share stories and anecdotes to convey and connect with your clients. Once your clients understand that you are using behavioral analysis to have an in-depth, forward-thinking discussion into their life experiences, motivations and anxieties, it stops being a difficult conversation.
Knowing your clients’ risk tolerance and confidence levels is a good starting point to know your clients and for your clients to better understand themselves.
Alain Samson, PhD is the chief science officer and Prasad Ramani, CFA, FRM, CAIA, is the chief executive officer of Syntoniq, a California-based provider of behavioral software for financial advisors.
Read more articles by Alain Samson, Prasad Ramani
