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Brief

Financial Health Solutions: Driving Change Through Measurement

By adopting these four measurement best practices, financial institutions can better understand and improve the impact of their financial solutions.

By Trey Waters, Heidi Johnson

Wednesday, June 25, 2025
Financial Health Solutions: Driving Change Through Measurement
Executive Summary

Effective FinHealth Measurement Strategies for Financial Institutions

Measuring the impact of financial health solutions is essential for developing effective products and services that truly improve consumers’ financial lives. The Financial Health Network’s Financial Health Impact Lab partnered with financial service providers, including banks, credit unions, fintechs, and nonprofits, to support the development and testing of innovative financial health solutions. This program has not only contributed to the body of evidence on what works to advance financial health, but also has shown how financial institutions can successfully embed measurement processes into their solution development lifecycle. The Impact Lab identified four measurement best practices that financial institutions can adopt to understand and improve the financial health impacts of their solutions.

Key Insights

  1. Use control groups to capture customer outcomes. By employing randomization and control groups, financial institutions can isolate and quantify the effects of specific interventions, providing clear evidence of a solution’s impact on customer financial health.
  2. Leverage administrative data for financial health analysis. Administrative data, such as account inflows and outflows, savings balances, and credit utilization rates, offer a rich view of customer behaviors and outcomes without imposing additional data collection burdens.
  3. Disaggregate data using metrics related to financial health. Disaggregate data to gain insights into how solutions impact different customer segments and identify unintended outcomes.
  4. Evaluate customer impacts repeatedly and over time. Repeated analysis captures both short-term and long-term effects, revealing how the impact of financial health solutions may change or evolve over time.

Introduction: Overview of the Financial Health Impact Lab

When financial institutions can measure the impact of financial health solutions accurately, they’re able to make data-driven decisions about their products and services. The Financial Health Network launched the Impact Lab (formerly known as the Financial Health Leaders Lab) to spearhead the development and testing of financial health innovations. The program partnered with companies that were creating innovative solutions, supporting the development of these solutions, and creating plans to measure their financial health impacts. The findings were shared publicly to build the body of evidence on what works to advance financial health.

Over the course of the program, the Impact Lab worked with 17 financial service providers, including banks, credit unions, fintechs, and nonprofits. The program employed a high level of rigor with these studies and sought to implement the studies at a scale that ensure statistically significant results.

Beyond merely assessing the impact of innovative solutions, the Impact Lab clearly demonstrated that financial institutions can embed rigorous measurement processes into their solution development lifecycle and identified best practices for doing so. By embracing measurement techniques such as control group comparisons, leveraging administrative financial health data, and disaggregating data by metrics related to financial health, financial institutions can make data-driven decisions and create more effective financial health solutions that make a meaningful difference for the people they serve.

Measuring Financial Health

Financial health is a composite measurement of a person’s financial life. It assesses whether people are spending, saving, borrowing, and planning in a way that will enable them to be resilient and pursue opportunities over time. The Impact Lab used administrative data, such as savings balances, to understand how solutions impacted consumers’ financial health.

4 Financial Health Measurement Best Practices

1. Use control groups to capture customer outcomes.

Financial institutions should use control groups and randomization to capture a solution’s impact on financial health. Companies can leverage existing infrastructure to develop simple processes for randomizing users and creating control groups when evaluating new solutions.

The Impact Lab and its partners collaborated to employ rigorous research methodologies to measure the impact of solutions on customer outcomes. This included advanced measurement design techniques, such as establishing control groups through randomization. 

Randomization is a research technique that randomly assigns users to different groups, such as randomly selecting which customers to pilot a new solution. Using randomization allows companies to compare the outcomes of customers who participated in the program. We worked with our partners to isolate and quantify the effects of specific interventions. This approach allows for a more accurate assessment of how a new solution is impacting customers, from changes in financial behaviors to improvements in financial health.

Financial institutions can also use other methods to measure the impact of their financial health solutions, such as observational study methodologies like pre-post analyses. While these alternatives may be easier to implement in some cases, they generally provide less robust evidence of causality compared with approaches such as randomization.1

The Impact Lab worked with its partners to leverage their existing internal processes and infrastructure to implement powerful research tools. Many of our partners already used similar methods to A/B test marketing content or user experience improvements in their digital platforms. By extending these capabilities to test financial health solutions, banks and other financial service providers were able to gather data on how new solutions were impacting their customers’ financial health.

Case Study: SaverLife Uses Randomization and Control Groups To Capture Impact

The Impact Lab partnered with SaverLife to examine the company’s new savings competition, The Race to $500, to capture the specific impacts of a prize-linked savings challenge. SaverLife randomly invited a group of users to the challenge to measure the effect of a prize-linked savings initiative before rolling it out more broadly.

2. Leverage administrative data for financial health analysis.

Administrative data are valuable and accessible sources of information for capturing information that users can not easily self-report.

Administrative data offer a unique set of information for conducting in-depth analyses of financial health solutions. These data could include account inflows and outflows, savings balances, debt-to-income ratio, and credit utilization rate, depending on the data source. Financial institutions routinely collect these metrics during their operations, and they provide a rich, detailed, and often longitudinal view of customer behaviors and outcomes. 

The Impact Lab and its partners strategically leveraged administrative data to uncover nuanced insights. By utilizing data already being collected during normal business operations, we worked with our partners to conduct robust analyses without imposing additional data collection burdens. While other data collection methods, like customer surveys and external data sources, can also offer valuable insights into customers’ financial health, these approaches may come with additional costs and often lack the granularity and depth of administrative data.

Financial institutions need to identify a breadth of data when capturing a solution’s impact. It is important to not only focus on primary outputs, such as increases in savings deposits for a savings solution, but also on secondary changes, such as how the solution impacted savings balances. The Impact Lab worked closely with financial institutions to think holistically about a solution to ensure we captured its full impact on financial health.

Case Study: Even Gains Insights on Active Choice Messaging With Administrative Data

The Impact Lab partnered with Even (now known as ONE@Work), an employer-based financial management platform, to examine the effects of presenting an active choice about enrolling in an automatic savings solution to new users at onboarding. To understand the impact of the new onboarding process on users, we used administrative data to capture automatic savings enrollment rates and savings balances.

3. Disaggregate data using metrics related to financial health.

When testing new solutions, companies should disaggregate the data using metrics that reflect the financial health behaviors connected to the intended outcome. This is an important step because a solution can impact people’s financial lives differently.

The Impact Lab worked with its partners to capture the impact of solutions by disaggregating data using metrics related to financial health, like savings balances and credit scores. This analysis complements other approaches to disaggregating data, such as demographics. While disaggregating by demographics provides valuable insight into how outcomes might differ for people by age, income, race and ethnicity, and gender, it is also valuable to examine how outcomes differ for people with different financial health characteristics or behaviors.

To effectively disaggregate data using financial health-related metrics, financial institutions should first define key financial health metrics. Product managers can then use these key metrics to disaggregate data when evaluating new solutions. This approach provides a deeper understanding of how a solution impacts different customers’ financial health and potentially identifies unintended outcomes or changes not directly related to the primary goal. This information can help a company target its solutions to relevant customer groups.

Financial institutions can capture and disaggregate metrics about their customers’ financial health in numerous ways. One approach is to survey customers using tools like Attune to capture a financial health score. Additionally, financial institutions can use administrative data, such as the ratio of inflows to outflows and the frequency of late payment fees, to create internal financial health segments.

Case Study: BECU Tests Savings Solution by Disaggregating Data

The Financial Health Network partnered with BECU, a large credit union, to test a new digital savings feature to help members with low to moderate incomes build emergency savings. The Quick Save feature enabled credit union members to make small, spontaneous deposits to their savings accounts with the swipe of a button on the app’s home screen. To understand Quick Save’s impact, we disaggregated members by their initial savings balances, which allowed us to capture how Quick Save impacted members differently.

4. Evaluate customer impacts repeatedly and over time.

Financial institutions should analyze data to capture both short-term and long-term effects when assessing a solution’s impact on financial health.

To structure the timeline for its research studies, the Impact Lab worked with its partners to assess multiple factors, such as the organization’s timelines and the structure of the solution, to ensure there was enough time to collect a suitable sample size. We developed timelines intentionally to look beyond immediate impacts, recognizing that financial behaviors and outcomes often require time for meaningful change.

By ensuring our research captured both immediate and long-term impacts, we helped our partners identify when a financial solution’s impacts were not linear. For example, a solution may sometimes have a short-term positive or negative financial health impact that either dissipates or reverses over time. Recognizing these potential shifts is essential for making well-informed product decisions. 

Furthermore, companies should implement short-term and long-term evaluations of their solutions. By consistently measuring, they can gain deeper insight into the various dimensions of a consumer’s financial health that the solution may influence at different points in time. This ongoing assessment enables companies to refine their offerings, ensuring sustained positive outcomes for consumers.

Case Study: Commonwealth Bank of Australia Explores How Impacts Can Change Over Time

In collaboration with the Commonwealth Bank of Australia (CommBank), the Impact Lab evaluated the impact of solutions like simplified digital payment tools, pre-commitment messaging, and refund reminders on customer debt repayment behaviors during tax refund season. The study assessed engagement rates, debt payment behaviors, and subsequent financial health impacts over multiple months. We captured how financial health behaviors changed over time by continuing the research over an extended period.

Endnotes
  1. When implementing randomized controlled trials (RCTs), it is important to remember that the effects for a financial institution’s customers on average may be different from the effects for important subgroups, including underrepresented and underserved consumers. Disaggregating data by subgroup when feasible is important from an equity lens. See practice 3 for more detail about the value of disaggregating data.

The Impact Lab Series

This study is part of a series highlighting Impact Lab member innovations. You can learn more about these solutions at the Impact Lab website or by visiting specific evaluation reports.

Impact Lab Reports

Acknowledgments

We thank the following Financial Health Network staff members for their help reviewing this brief: Hannah Gdalman, Necati Celik, Marisa Walster, and Angela Fontes.

The Financial Health Impact Lab is generously funded by MetLife Foundation. Learn about the financial health solutions identified through the program here.

Additional Resources

Financial Health Network has researched, published case studies, and created tools to help measure financial health. These resources provide a comprehensive overview of financial health measurement best practices and are valuable guides for anyone seeking to identify financial health measurement best practices.

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Written by

Trey Waters

Trey Waters

Senior Manager, Financial Services Solutions
Financial Health Network
Heidi Johnson

Heidi Johnson

Senior Director, Behavioral Economics