Can we design decision tools to offset or even leverage the hurdles that our brains put in front the most important decisions that we face? Take planning and saving for a comfortable retirement. How much and in what one invests are two of the most important decisions any adult needs to make and take responsibility for.
“Do your eyes glaze over when you start hearing about financial planning, asset allocation or stock picking?”*
With fewer people being able to rely on defined benefit pensions, social security’s long-term solvency uncertain and questions about conflicts of interest in the investment advice industry, people need to be more self-reliant. And yet, one half of American households will not have enough saved to maintain their standard of living in retirement. On average, people aged 55 to 64 years old have just $104,000 in retirement savings. Clearly some bad decisions are being made.
The Social Security Administration has helpfully compiled a summary of behavioral economics research that helps explain why people tend to fall short. It includes a list of depressingly familiar behavioral impediments:
| Category | Examples |
| Informational issues | Ambiguity aversion Anecdotal evidence |
| Heuristics and biases | Rules of thumb Status quo bias Default effects |
| Intertemporal choice | Self-control Procrastination Hyperbolic discounting Emotions |
| Decision context | Reference dependence Choice bracketing Framing effects Choice architecture |
Marketwatch.com recently published three articles examining the role “Robo-Advisors” can play in helping people meet their savings requirements. This unfortunate term refers to automated investment services, web sites that provide advice and execution with respect to asset allocation, rebalancing, dividend reinvestment even tax loss harvesting, at about one-half the cost of a human. The user answers questions about the amount they have to invest, risk tolerance, goals and time frame for investing. The service returns an investment plan including asset allocation with specific investments and provides ongoing management.
These services could be helpful from a behavioral standpoint. Just by requiring the user to slow down and answer a series of questions, the user has to engage their higher brain functions (“system 2“), rather than rely only on intuition or simple rules-of-thumb. They should reduce the effects of inattention and limited self-control over time by serving as a commitment device: people have implicitly promised (at least themselves), to follow through on savings and investment plans. Ambiguity aversion, discomfort with unknown risks and unfamiliar fields that plagues many would-be investors, can be limited if risks are explained simply and the questions posed are not too difficult. For example, don’t ask the user to forecast inflation or investment returns! These services also use choice architecture to draw people to low cost index funds and ETFs by default; high expenses are the bane of long-term investing.
The Marketwatch articles note that robo-advisors have some obvious limitations. Some people may really need the reassurance of a human to confirm that the results and the plan make sense and to help instill discipline to stick with the plan through market downturns. Humans are also required for unusual situations and other financial planning requirements like college, estate planning, insurance, etc.
If I were designing one of these, I’d include a Save More Tomorrow option, a really clever way to nudge ourselves to do what is best for us in the long run, reducing procrastination and present bias. Also, I would incorporate social media to leverage peoples’ desire for inclusion and try hard to make the process fun. In sum, automated investment services could be effective decision tools to help many people decide how to save for their future but also to execute that decision.
*http://www.marketwatch.com/story/how-a-robot-can-offer-sound-financial-advice-2015-04-21?page=1