Retirement planning, riddled with uncertainty and consumer biases as it is, may be best handled with a mix of digital and face-to-face advice. People polled by telephone are slightly less likely than those interviewed online to say their personal finances are in “poor shape” (14% versus 20%, respectively), a Pew Research Center survey experiment has found.
The experiment, conducted in February and March, is part of a line of research at the Center looking into “mode effects” – in this case, whether findings from self-administered web surveys differ from those of interviewer-administered phone surveys.
In particular, survey researchers have long known that Americans may be more likely to give a “socially desirable” response (and less likely to give a stigmatized or undesirable answer) in an interviewer-administered survey than in one that is self-administered. Mode effects can also result from other differences in survey design, such as seeing the answer choices visually on the web versus hearing them over the phone.
Historically, so long as your company and government stayed solvent, you knew with a fair amount of certainty what your retirement benefits would be and how long they’d last – basically for life. The rise of defined contribution plans turned that on its head and created a large market for personal financial advice, as individuals suddenly had to figure out how to plan for their own retirement. However, as we outlined in the first part of this series, traditional face-to-face financial advice isn’t cost-effective for providers and average investors.
So, how to provide advice to the average long-term investor in a cost-efficient and profitable way? In this piece, we are going to delve a little deeper into a solution.
Financial planning isn’t just about finance. Long-term saving is a classic case study in behavioral biases. These must be managed and mitigated – whether it is through digital or face-to-face advice.
Inertia is one such bias. While people will generally put off taking action, research has shown that if they are intimately involved in preparing a plan, they are more likely to stick to it. The most committed planners also tend to be the most financially literate.
The Center’s experiment randomly assigned respondents to a survey method (online or telephone). Although it found that political questions, such as whether respondents approve of President Donald Trump, don’t elicit significant mode effects, some other, more personal items clearly do. When asked whether or not they had received financial assistance from a family member in the past year, for instance, just 15% of phone respondents say yes. That share is significantly higher (26%) among web respondents.
Americans at both high and low income levels are more likely to report financial stress when interviewed online than via telephone. Adults with annual household incomes of less than $30,000 are 10 percentage points more likely to say their financial situation is in “poor shape” when interviewed online versus on the phone (37% vs 27%). The effect of survey mode on the other answer choices (“only fair,” “good” or “excellent”) was less pronounced for low-income adults.
Among Americans with household incomes between $30,000 and $74,999, the share who report being in “poor” or “only fair” financial shape was higher on the web (65%) than on the phone (57%). And respondents in this group were less likely to report being in “good” financial shape on the web than when speaking on the phone to an interviewer (32% vs. 40%, respectively). Few from this income group in either mode report being in “excellent” financial shape.
On a broader level, individuals need to understand the trade-offs they make, now and in the future. They need to be educated about the consequences of their decisions and consciously choose their priorities. What lifestyle do they want now? How about in retirement? Are they contemplating any bequest?
Imparting a good understanding of behavioural biases should be an integral part of the retirement planning process and needs to be built into any successful digital-style advice model. Either that, or the model should protect individuals from the worst of their own biases, as much as possible.
Any model is based on assumptions that must be evaluated. While robo-advisors are getting lots of press at the moment, they are mostly just a delivery mechanism. A nice user interface should not be a substitute for solid advice that ultimately addresses a key financial and behavioural problem. Digital poor advice is still poor advice.
Tool creators – particularly when there is limited opportunity to ask them questions – need to be upfront about the assumptions they used for calculations. By far the most consequential assumptions that go into long-term planning concern the expected rates of return. If the tool assumes that equity markets will continue to return 6 percent (in real terms) as they have for the past century, monthly savings need to be a lot less than if a 3 percent return rate is assumed. But which rate better reflects the future? Over which time frame? How is the person’s age taken into account? Does time to retirement matter?
Thinking in real terms is convenient, but what happens if inflation turns out to be 5 percent per annum instead of 2 percent? Inflation plays a key role as it is the link between salary (and hence saving capacity), asset market returns and valuations, the value of other assets (like property) and perhaps most importantly, spending in retirement. In short, it is so integral to the problem of retirement that it needs to be carefully modelled – and very clearly explained. Failing to adequately address it may render the advice misleading at best, leaving the user to reach retirement woefully underfunded.
What a useful digital tool should look like. To be a valuable tool, a digital platform needs to be both robust and user-friendly. A smartly designed product that manages biases to bring about the outcome chosen by the consumer will be a remarkably cost-effective way of providing customised financial advice to most people, most of the time.
The tool should explain its assumptions in a simple way, but without sacrificing real-world complexity. Other points to note:
Users should be asked, in non-misleading terms, whether they want a basic, average or luxury retirement lifestyle.
The language should be free of jargon and go to the heart of the users’ problem. For instance, users generally aren’t interested in the content of their portfolio, but care whether they can retire according to a certain lifestyle they are comfortable with.
The tool should allow users to be actively involved in making the trade-offs based on their unique needs, wants and circumstances. For instance, would they prefer to retire a year later or save $200 more per month? This will ensure they work towards the retirement they want, rather than being lectured by a computer or given an inappropriate cookie-cutter response.
Computationally, a Monte Carlo approach – a computer-simulated analysis of potential decision outcomes – is the optimal way to allow for the range of possibilities that the unknowable future may hold in store. Simulations need to be run with different rates of return and inflation and maybe even varying levels of tax rates and government entitlements.
The best blend of digital and face-to-face advice. Ultimately, the biggest weakness of digital advice tools is the unpredictable behaviour of users. For instance, what will they do – and who will they turn to for counselling – when markets fall 20 percent in a month?
Moreover, government benefits are extremely difficult to project even five years out, let alone 20 years. These benefits vary by country but often include tax advantages for long-term savings, an old-age pension, health care subsidies and specific one-off cash grants. Given their inherent uncertainty, the value of these future benefits can be extremely difficult to model.
For all these reasons, we envision the current generation of digital advisors providing about 50 percent of the advice needed for 80 percent of the people. As retirement age approaches, it is wise for customers to sit down with a specialist and plan how to maximise their government benefits and tax structuring (especially estate planning in some countries).
In other words, it will be quite a while before the human planner goes extinct. Instead, financial advisors will deliver issue-specific advice using digital devices. Gone will be the days of trudging to their offices clutching a pile of paperwork at an appointed time. Financial advice will only be a few clicks away after you’ve reviewed your plans on your phone.
Even among relatively well-off adults, the survey mode influences reports about personal finances. Americans with annual incomes greater than $75,000 are 14 points more likely to report having an only fair or poor financial situation on the web survey than on the phone (36% web vs. 22% phone). This result expands on the Center’s prior research into mode effects on financial questions by demonstrating that survey mode can sometimes affect responses from relatively wealthy respondents, not just responses from those at lower income levels.
While the findings from this experiment suggest that self-administered surveys may be more accurate than interviewer-administered approaches as a way to measure financial stress (all else being equal), this does not mean that past telephone-based research arrived at erroneous conclusions regarding financial stress – for example, what predicts it or how the likelihood varies across subgroups. That said, researchers studying financial stress should consider that phone surveys have, at least to some degree, been understating the share of Americans experiencing economic hardship.