Friction costs are real. Each additional click, field, step, choice, form, or call is a toll on the decision-maker and can deter even the best of intentions. For example, research suggests that reducing a form from 9 fields to just 5 fields can increase conversion rates by 3.4 percentage points. Simply removing or reducing the number of steps required of people can increase how many of those people end up following through.

We are currently testing both light-touch and heavier re-design strategies for friction reduction in several 2018 projects. Beyond simply cutting steps out of the process, there are several strategies that we are using to reduce friction.

Strategy 1: Make the right behavior automatic

Evidence suggests that changing intentions is unlikely to lead to big changes in behavior. Even with strong intentions, people have lapses in self-control or they might procrastinate. In reality, there are many barriers and biases that make it difficult for even the best among us to follow through on our intentions. When designing products and services, it is often better to recognize this and make the right behaviors automatic.

For long-term savings, automatic enrollment and default contributions have been the biggest factor in increasing savings rates, increasing participation from 34% to 90%. Setting up automatic transfers is often heralded as a best practice for building short-term savings as well. However, current automatic savings programs require the saver to pick a day each month, like the 25th, and a fixed amount to transfer, like $100. These are not designed well for most low-wage workers, who are more likely to be paid bi-weekly and income that varies paycheck to paycheck. We are building better automatic systems for LMI households. This means programs that align with when and how much people are paid and programs that de-risk signing up for an automatic savings transfer.

making saving automatic can help overcome the many barriers and biases that make it difficult, but many automated savings options are not well designed for low-wage workers.

With Narmi, a tech platform for Credit Unions, we are testing ways in which we can connect automating savings directly with when someone gets paid. Specifically, we are exploring whether a fixed percent-based transfer amount (i.e. 6% of every deposit) is more or less attractive than an escalating percent-based transfer amount (i.e. 2% to start, increasing by 1% until 6%). With Earn, a non-profit, financial technology company that incentivizes savings, we are testing whether offering overdraft protection helps make automatic savings feel less risky and more attractive to potential savers.

We are also exploring how automation at the employer level can help employees’ financial wellness. For example, in our work with Homebase, a scheduling platform for small- to mid-sized employers, we are encouraging managers to publish work schedules earlier. This gives employees more notice to better plan for their work schedules or pick up additional work outside of their primary job. To do this, we are creating default schedules that allow employers to easily and quickly copy schedules from prior weeks. We believe that automatically generating schedules will make it easier for employers to publish their schedules sooner, giving employers significantly more time to plan ahead.

The tests with Earn and Homebase are currently in the field. The test with Narmi is poised to launch in summer 2019. We look forward to sharing our results.

Strategy 2: Make the right choice the default

In addition to automation, it’s important to set the right default. Defaults are incredibly powerful, and yet, many financial institutions and companies set defaults that are not ideal for the consumer. For example, the most common default contribution rate for auto-enrollment retirement plans is 3%, and 40-70% of employees stick to the default rate. Yet, experts recommend that people save closer to 15% of their income to be adequately prepared for retirement. Defaults are powerful because they make that choice the easy choice, they imply that is the “right choice”, and they create an anchor around the default number.

Another area where carefully choosing the right defaults is important is debt: taking on debt and paying it back. For example, the default for taking out a car loan or a student loan is often the maximum available. In partnership with Duke’s Office of Personal Finance, the department that manages student loans for the University, we re-designed how graduate students were offered and accepted loans. Instead of providing the total amount available to borrow, we split the total loan package into two bundles – one covering known, fixed costs like tuition and the other covering unknown, variable expenses like the cost of living. By breaking up the loan into two separate numbers, we decreased the percent of students borrowing the maximum loan amount from 29% to 13%, a more than 50% reduction.

figuring out what is affordable to pay for a car is complicated and most people anchor on the monthly payment, neglecting uncertain or future expenses

With Beneficial State Bank, a community development bank based in California, we changed the default payment due date of car loans from 30 days from the day they buy the car to the day they get paid. By defaulting the due date to their payday, we are reducing the mismatch between income and expenses, which may improve rates of repayment. This project is currently in the field and results will be shared in our 2019 Annual Report.

Strategy 3: Simplify complexity

Complexity creates its own kind of friction. A study from 2015 found that complexity around the Earned Income Tax Credit explains why not everyone takes advantage of the tax benefit. As a decision becomes more complex, we should take more time and effort figuring out the right decision for ourselves – but instead, we rely on mental shortcuts that may be error-prone and imprecise

One complex decision is figuring out how much car you can buy. With 7 million Americans more than 90 days behind in their car payments, it appears that many people are mis-calculating how much they can afford. Most car buyers only consider the monthly payment of their auto loan, neglecting to consider uncertain or future expenses that are difficult to determine. These expenses include repairs, maintenance, insurance, or how much they will spend on gas. As a result, many people end up paying more than they can comfortably afford. We designed an auto loan calculator that breaks down these complex costs and conveniently adds them to the monthly payment, therefore adjusting the total amount one should borrow. In a lab experiment, we found that going through the auto loan calculator significantly reduced the size of an auto loan participants felt they could afford, moving from $15,000 to $12,500 on average, a 20% reduction in the size of a potential loan. We plan on testing the calculator in the field to see if it actually decreases the amount people borrow.

making saving automatic can help overcome the many barriers and biases that make it difficult, but many automated savings options are not well designed for low-wage workers.

With the St. Louis Housing Authority, the government entity that manages St. Louis’ section-8 housing voucher program, we are testing a text-message program that breaks down the complex steps of moving to better neighborhoods with a voucher. Voucher recipients receive weekly text messages that provide clear action steps for that week to get them closer to moving. We think that simplifying the complexity of moving with a voucher will encourage more voucher recipients to move to higher opportunity areas, which has been shown to improve life outcomes. This project is currently in the field; we will share results in our 2019 Annual Report.

Making a process completely frictionless is often impossible due to technological, regulatory, financial or logistical constraints. This means that we also have to find ways to reward and motivate people to overcome the remaining barriers. Once friction has been reduced as much as possible, we look to boost motivation either by making the existing benefits more appealing or by adding benefits, often closer in time.