The Methodology Behind the Risk Activity

The Risk Activity is the application of decades of breakthrough behavioral economics and decision science research by our academic co-founders.

By having clients make a series of tradeoffs at varying levels of investment risk and opportunity, we are able to calculate their Attitude to Risk and Sensitivity to Loss scores, which tell us how clients respond to different portfolio outcomes when investing their wealth. This is why the size of the green triangle changes across the six different scenarios, to stress-test the client’s risk preferences across market conditions.

Using the client’s Attitude to Risk and Sensitivity to Loss scores, we calculate where the client would be located on an efficient frontier of investment options, given your firm's capital market assumptions and model portfolios, and provide a Risk Comfort Score for each model portfolio on the frontier. This Comfort Match Score is a measure of how much utility a client attains from a model portfolio, relative to the other investment options.

In the below chart, you can visualise how the client's risk profile translates to a Comfort Match Score for each of the model portfolios on an efficient frontier of expected volatility and expected return. 

Our scientific methodology differs from traditional Stated Preference methods of understanding a client's risk profile, such as a risk tolerance questionnaire like the one shown below.

Stated Preference methods like the above are imprecise, relying on ambiguous language with no underlying mathematical theory supporting their scoring methods or definition of risk, making them:

• Unreliable – Results will vary, depending on the questions asked or even how standard questions are interpreted by investors, resulting in varying advice for that same client.
• Difficult to validate – Without precise language and mathematical theory as a core underpinning, defending the suitability of the advice provided is problematic.
• Difficult to interpret – Questions like “On a scale from 1 to 5, how comfortable are you with uncertainty when investing?” are very difficult for investors to accurately answer.

What makes our methodology unique is that, in contrast to having clients answer a questionnaire and state their preferences, clients complete the Risk Activity where they can demonstrate and reveal to their advisor how they make investment tradeoffs at varying levels of risk and reward. This is called Revealed Preferences.

The core philosophy of Revealed Preferences is simple:

• Show, don’t tell – Use gamification to let clients naturally reveal their preferences regarding risk vs. return, today vs. tomorrow, and certain vs. ambiguous, rather than relying on stated preferences alone.
• Adopt technologies from the frontier of economic research – Use the most scientifically advanced decision games that can be administered efficiently to clients in order to scale an advisory practice, make digital financial services successful, and address looming compliance and regulatory concerns.
• Lever economic science and mathematics – Use quantitative and verifiable assessments of a client’s goals, constraints and preferences that have clear economic interpretations and direct implications for portfolio construction and financial planning.

Going Forward: The value is in the client data. The successful advisor and firm of the future will create value by fully understanding their clients. Rich data will help them balance their goals, preferences, and constraints with products and services that reflect who they truly are. The advisors and firms who apply science and rigor to both portfolio optimization and client profiling will achieve personalization and growth at a scale previously impossible with traditional client-profiling methods.

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