Encouraging savings from debt consolidations and loan modifications

Background

Many LMI households want to save but have difficulty finding slack in their budgets to dedicate to savings. Data from the US Bureau of Labor Statistics indicate that households with incomes in the lowest 20% spend an average of 72% of their income on housing, food and transportation versus 57% of income for households with the highest 20% of incomes. It would be so much easier to save if free money just appeared – money that isn’t already spoken for within an established budget.

In fact, debt consolidations and loan modifications may create enough of a financial windfall for some households to be able to start saving. In an experiment that we ran with Digital Federal Credit Union (DCU), we found that 16% of people who were refinancing a loan wanted to save a portion of their payment difference. We partnered with Washington State Employees Credit Union (WSECU) to see if we could validate our DCU learning. WSECU call center staffers regularly modify loans or consolidate debts for members; the reductions in payments that members get from modifications or consolidations could be a potential source of short-term savings, as it may be that funds are not yet earmarked for other expenses. In an experiment with WSECU, call center staffers asked if members wanted to save a portion of their payment reductions when consolidating debt or modifying a loan.

Key Insights

In our work for the DCU refinance to savings project, we identified a number of barriers:

• Loss Aversion: One of the real challenges to saving is the loss aversion that people feel when spending money is directed toward savings. If they don’t yet have the opportunity reclassify payment reductions to another mental account, we can more easily help them allocate toward emergency savings.

• Lack of attention to emergency savings: The call center employees can create a norm for members to save for emergencies when they suggest that the member use some of the payment reduction for savings; the norm alone could increase the number of members who save.

• Friction: While employees highlight the importance of savings by giving the member more information, we know that information is unlikely to motivate action. In fact, in our work with DCU we found that the friction of setting up an automatic savings transfer, even after a member has expressed a desire to set up that transfer, can deter the best of intentions. It’s therefore important to minimize the actions that members need to take to save.

Experiment

WSECU call center employees were assigned to deliver one of two scripts: 1) a suggestion with information prompt and 2) a suggestion and offer to set up automatic transfer. When WSECU members initiated a loan modification or debt consolidation with the call center, they would hear one of the two scripts depending upon the condition to which their call center employee was assigned. The call center employee recorded how much reduction in payments was expected, if the member agreed to save for emergencies and whether they allowed the call center employee to set up automatic savings transfers.

Results

After rolling out the experiment, we saw that the sample size was lower than the 700 members we had anticipated over a 3 -month period, with just 107 members in 4 months. Upon further investigation to understand the reduced sample size, we found that the employees were inconsistent in recommending the savings, and some expressed difficulty in fluidly incorporating the script into their process flow.

Of the 107 loans where one of the scripts was used and the data were tracked, we found that 31% of members were willing to set up savings with two thirds of those members allowing the call center employee to set up automatic savings, and the median amount saved was $100. A greater proportion of members who received the prompt without the offer to set up automatic transfer said that they would save than members in the group with the offer (38% versus 25%). This result was not statistically significant and was likely driven by call center employee differences, since we see significant variation between employees. Therefore, we caution against making conclusions about effectiveness of this intervention without further testing. Ultimately, we stopped the experiment until we’re able to uncover an easier way to incorporate it into the workflow of call center employees. Any future experiments should also randomize borrowers to different conditions with each call center employee changing the script they use based on the randomization to avoid employee-induced effects.