Last November, the Consumer Financial Protection Bureau’s Office of Financial Empowerment hosted a conference on “Empowering Low-Income and Economically Vulnerable Consumers: Making the Case through Access, Data and Scale.” A key highlight of the conference was a breakout session about the incentives and obstacles to collecting data in the field. Leading the session were representatives from LISC, NeighborWorks, CGAP and the University of North Carolina’s Center for Community Capital. Everyone agreed that we need more rigorous data. What was less clear was exactly how to get there. Two key questions emerged throughout the day:What outcomes are we measuring? And, how do we collect data?
1. What outcomes are we measuring?
Standardized measures sound great in theory, but before we can devise standards, we need to decide which outcomes actually matter. Is the ultimate goal to help an individual achieve financial stability, financial self-sufficiency, or something else altogether? On the product side, should we focus on access to and usage of a product? Or should we emphasize service quality and safety? And once we decide which outcomes matter, which proxies should we use to measure these outcomes?
Kevin Jordan, Vice-President of National Programs at LISC, proposed 4 core principles that should guide our efforts to devise these standard measures. He insisted that any definition of a household's or an individual’s financial success must focus on net income rather than wages. Simply put, households will achieve financial stability only if the amount of money they take in is greater than the amount of money they spend. Any definition of financial success must therefore focus on making monthly cash flows positive. Secondly, we must help individuals improve their credit scores. An individual’s credit score can affect everything from the down payment he puts on a home, to the monthly interest rate he pays on a credit card. Thirdly, we should focus on helping households improve their net worth. Growth in a household’s net worth from year to year is indicative of long-term sustainable progress in the right direction. And finally, we must work to improve employment retention because a stable source of income is an integral part of financial stability.
Others argued that we look beyond traditional measures and employ an integrated approach that takes into account additional indicators of financial stability such as whether an individual has insurance, receives government benefits, or has a reserve of savings to fall back on in case of an emergency.
However, measuring some of these indicators might not be as simple as they sound. For instance, how do we measure an individual’s net income? Do we focus on monthly net income or annual net income? And how do we measure expenditures? What is an acceptable ratio of expenditures to income?
2. How do we collect data?
Another key question revolves around what we can reasonably expect practitioners to collect in the field. Kevin Jordan said that practitioners feel as if they spend too much time “counting” clients and that every additional database researchers ask them to use takes away from valuable time they could be spending with clients. Kim Manturuk from UNC’s Center for Community Capital expressed the concern that practitioners are hesitant to ask clients sensitive questions about their finances for fear of alienating them. Jessica Anders from NeighborWorks explained that practitioners are inclined to use extra funding to improve their program activities rather than spend these additional dollars on data collection.
However, each of the panelists also offered potential solutions that would lessen the burden placed on practitioners. NeighborWorks’ grant recipients have successfully integrated data collection directly into the services they provide. They have also realized that baseline information doesn't necessarily need to be collected all in the first meeting. Since a person’s financial situation doesn’t change overnight, baseline information can be effectively collected over the first few weeks of meeting with a client, rather than all in the initial meeting. Front-line staff can therefore make the most of a first-time meeting and save the more sensitive questions until a level of trust has been established between staff and client.
All the panelists agreed that technology must play a crucial role in streamlining the data collection process. Kate McKee from CGAP discussed how international researchers have begun to look at consumers’ entire digital footprint and not just their credit scores. With the mobile payment revolution in Kenya, for example, there is a wealth of data that can be leveraged to shed light on consumers’ behaviors. She also invoked the promise of geo-mapping where supply-side data can be matched with non-financial data to measure trends and get a more holistic view of the environment in which financial services operate.
And yet, collecting data in the field remains a very real challenge. Instead of expecting practitioners to collect data themselves, should we rely on the information presented in large national surveys such as the Survey of Consumer Finances or the FDIC Unbanked and Underbanked Households Study? Or should we instead focus on encouraging foundations to allocate funding to individual organizations to collect program-specific data? Or, perhaps we consider a third approach, such as the one used in the U.S. Financial Diaries where academic research institutions partner with non-profit organizations to conduct an in-depth look at household finances. These are important questions that should guide our work as we move towards standardizing and streamlining data collection in the field.