In this post:
- The Difference Between “Nudging” and Deeper Behavioral Understanding
- The Behavioral Power of Preferences
- Behavioral Science Unlocks Precision Financial Wellbeing
Regulators Want More Behavioral Science in Financial Services – Let’s Go Beyond Nudging
Paul Adams recently wrote a thoughtful article crystallizing the key ways behavioral science features in the Financial Conduct Authority’s (FCA’s) Consumer Duty policy statement of July 2022. I’d like to build on Paul’s thoughts here.
I believe there’s a risk the industry stops well short of the full behavioral science opportunity. How? By focusing mainly on “nudging” strategies (based on behavioral insights) without fully appreciating that behavioral science lets them understand and act on behavioral drivers at the individual consumer level.
It’s the difference between listing calorie counts on a restaurant menu (knowing that it will lead some customers to get the small fries or switch to salads on occasion) vs. having the medical and dietary understanding of each consumer to know how they are likely to make decisions about nutritional wellbeing, and then crafting a personalized menu that will frame the optimal set of choices for each consumer.
That’s a large and powerful difference.
The Difference Between “Nudging” and Deeper Behavioral Understanding
In their guidance, regulators mostly focus on using behavioral insights to help frame decisions so that (some) consumers will choose in a way that increases their financial wellbeing. For example, framing the options for a savings rate not as a percentage of salary, but as the cost of a more relatable everyday object (e.g., a cup of coffee) can help consumers choose to save more.
Broadly speaking, these sorts of interventions are of the “nudge” variety popularized by Richard Thaler and Cass Sunstein’s work (and book of the same name). There’s low hanging fruit to be had here, and it’s a good thing for regulators to lay down expectations of the industry on this front.
But there’s a larger behavioral science opportunity in view. It involves the relatively recent development of a new-in-kind class of profiling tools that infuse behavioral and decision science in their very design. These tools feature “revealed preference” methods, in which customers use their mobile device to make tradeoffs in a series of decision scenarios rooted in behavioral science. From their choices, we can deeply understand (and mathematically model) the unique set of fundamental preferences that drive each consumer’s behavior.
See Foundations: Life’s Three Key Tradeoffs for more on preferences.
The Behavioral Power of Preferences
These preferences explain why, among two consumers identical in demographics and financial situation, one will choose to go with a fixed rate mortgage while the other chooses a floating rate. It’s a function of risk preferences (how the consumer trades off risk and return).
Or that drive one consumer to sell out of an equity position in the face of market turbulence, while another hangs on for the long term. It’s a function of loss aversion (how painfully the consumer feels losses).
Or that lead one consumer to put 5% of salary in retirement savings, while another saves just 1%. It’s a function of time preferences (how the consumer trades off consumption today vs. consumption in the future).
Behavioral Science Unlocks Precision Financial Wellbeing
Why is it essential that we use tools infused with behavioral science to understand preferences this deeply and for each consumer? Three reasons:
1) Reveal new-in-kind insights – Using behavioral tools to measure preferences enables us discover insights about customers that conventional tools (e.g., risk tolerance questionnaires) simply aren’t capable of. For example, they can detect advice clients who lack coherent risk preferences and who, academic research has shown, are likely to make poor decisions that negatively affect their long-term wealth accumulation and financial wellbeing. See – Foundations: Decision Consistency and Economic Rationality.
2) Minimize “noise” in understanding customer’s preferences – Quite simply, shifting to behavioral tools removes much of the bias and noise that plague questionnaire and dialogue-based methods for understanding preferences. (See Kahneman, Sibony and Sunstein’s “Noise: A Flaw in Human Judgment”)
It’s like letting a blood test measure cholesterol (LDL and HDL), instead of relying on the physician to ask the patient about diet and make a best guess. There are better tools for doing the measurement, creating more time and mental space for human experts to do what they do best (e.g., synthesize disparate information; frame choices; engage patients empathetically; etc.).
3) Scale personalized financial wellbeing programs – Ultimately, a deep and integrated understanding of each consumer’s preferences lets firms deliver much more precision and personalization to the table when serving customers and helping them achieve financial wellbeing.
Nudging programs, and the decision design that goes with them, tend to be applied at a “segment” level—in other words, the same decision design is applied to a swath of customers to help them, for example, save more. Some customers will respond to the nudge, others won’t. But if financial firms understand preferences at the individual level, they can design more targeted and personalized programs that are likely to be much more effective.
There’s an opportunity for forward-thinking financial firms to use behavioral tools like revealed preferences to uncover the full range of preferences that underpin any given customer’s financial decisions. The resulting insights form the basis for an integrated framework of client understanding, which can and should inform all parts of the customer experience (acquisition, onboarding/discovery, regular re-engagement with clients to detect movement in preferences, etc.).
That’s the golden opportunity with behavioral science that regulators – and the firms they oversee – should put front and center.