Financial health – or financial well-being – is a multidimensional concept that encompasses an individual’s ability to manage finances, cope with shocks, pursue goals, and feel confident about their financial future. Measuring financial health could help government authorities, in particular financial sector authorities, develop policies, regulations, and supervisory tools that enhance financial capability, promote financial inclusion, protect consumers, and enhance financial stability.
To date, financial authorities that measure financial health have mostly relied on demand-side data collected through national surveys. It is important that they also consider using supply side data (such as administrative and transactional data collected from financial service providers by financial regulators), as well as data collected from non-financial public and private organizations (such as utility companies and mobile network operators). To explore the potential use of such data to measure financial health, CGAP conducted desk research and interviews with key informants. Given that few financial authorities currently collect supply side data to analyze financial health, we hope this blog encourages further exploration and testing.
The value of supply-side data for financial health measurement
While demand-side surveys provide valuable insights into consumer perceptions and experiences, they have limitations such as high costs, infrequent data collection, subjectivity, and inadequate representation. Supply-side data, especially “administrative and transactional” data collected by financial authorities from financial service providers, offers several pros and cons. In terms of pros, we see the following:
- Cost effectiveness: Supply-side data often comes with lower collection costs, especially financial sector administrative data regularly collected through existing regulatory reports or transactional records.
- Timeliness: This data is collected by supervisors regularly and with high frequencies, sometimes even daily or real time, which is crucial for financial authorities to respond promptly to emerging trends and risks.
- Objectivity: Data collected by financial institutions and other organizations is generally more objective than self-reported information, providing a more reliable basis for policy decisions.
At the same time, supply side data comes with its own shortfalls. For example, supply side data collected by financial sector authorities from financial service providers only covers the formal financial sector, and some of the data and indicators may suffer from low quality, especially the data not used for routine prudential supervisory purposes.
Potential sources of supply-side data for financial health measurement from the financial sector and beyond
Although few financial sector authorities currently collect supply side data to measure financial health, they could theoretically access a wide range of such data sources. These can be categorized into data from financial service providers (administrative and transactional data) and consumer data collected by organizations outside of the financial sector.
For financial sector supply-side data, two sources are more accessible for financial sector authorities.
Data from regulated financial institutions
Banks, e-money issuers, payment service providers, and insurance companies process transactional and complaints-related data that can be used to measure financial health components. This includes information on account balances, transaction volumes, loan repayments and conditions, and customer complaints, providing a comprehensive view of consumers’ financial behaviors and challenges. For example, CGAP worked with the Bank of Tanzania to analyze transactional data on more than 20 million digital loans over nearly two years, revealing high rates of late repayments, defaults, and potential over-indebtedness among repeat borrowers.
Examples of supply side indicators that financial authorities could consider (non-exhaustive):
It is noteworthy that supply side indicators collected by financial authorities from financial service providers often focus on measuring volume and value data in absolute terms, oftentimes aggregated at the sector or macro level. By contrast, the indicators suggested above measure relative values or changes over time rather than absolute values, which is more appropriate for comparing financial health across different market segments, and to measure progress.
Data from non-regulated financial service providers
Non-regulated microfinance organizations, fintechs, digital lenders, payroll lenders, and community-based organizations hold valuable insights into the financial health of underserved populations who are not covered by traditional financial institutions. However, obtaining compatible data across all these different providers can be challenging.
Identifying financial authorities who use supply side data not collected from financial service providers to measure financial health is nearly impossible. However, in theory, these financial sector authorities could consider using supply-side consumer data collected by organizations that do not belong to the financial sector. This would require them to collaborate with other authorities and organizations, and comply with consumer data protection regulations. Such data could include:
Tax-related data
Tax authorities collect income and expenses information, which can assess financial resilience. For example, the United States’ Congressional Budget Office (CBO) uses individual income tax return data to measure household income and assess taxpayers’ financial health.
Housing eviction data
Court records on housing evictions can indicate financial distress and the inability to meet housing costs, serving as an early warning of deteriorating financial health for specific demographics.
Social protection program data
Digitalized welfare programs can provide insights into benefit utilization and financial stress, helping authorities understand the financial challenges faced by vulnerable populations and the effectiveness of social safety nets.
Property rental and utility company data
Payment patterns can predict financial health developments. Consistent rent and utilities payments indicate resilience and capacity to plan ahead, while arrears may signal financial difficulties.
Health data
Healthcare institutions have data on healthcare costs and access, offering insights into financial health. High healthcare costs can significantly burden financial health. Of course, the utilization of such data requires careful consideration due to its sensitivity.
Mobile network operator data
Mobile network operators possess real-time data on phone and internet usage, offering insights into consumer economic activities. Changes in usage patterns can reflect shifts in financial behavior and economic conditions.
Social media and e-commerce platform data
While often considered demand-side data, social media posts and comments can provide valuable insights into public sentiment and financial health trends, particularly confidence. In India, CGAP, in collaboration with the RBI Innovation Hub and Decodis, analyzed social media posts using AI to understand the nature and level of urgency of consumers’ complaints regarding digital credit.
Considerations for integrating supply-side data into an actionable financial health measurement system
Financial authorities should adopt a phased approach to developing a financial health measurement system that includes supply-side data. Starting small and gradually expanding the scope is crucial.
- Define policy objectives. The first step is to identify the most salient policy objectives for monitoring different components of financial health. This may require analyzing the needs of different offices within the financial sector authority, such as consumer protection, financial education, financial stability, and financial inclusion.
- Assess data sources. Evaluate existing financial health demand- and supply-side data sources to determine gaps based on policy objectives, and engage in dialogue with other authorities and data holders to explore supply-side data sharing opportunities. Additionally, address legal considerations, data privacy concerns, and data fragmentation to ensure ethical and secure data use.
- Select indicators. Select existing indicators using financial service providers’ data that can be used for financial health monitoring (see table above).
- Leverage open finance initiatives, where available, to facilitate supply-side data aggregation and analysis across the financial sector, keeping consumers’ data privacy as a priority.
- Utilize AI to automate supply-side data analysis and identify patterns and trends. For instance, the Central Bank of the Philippines has implemented an AI-driven chatbot named BOB to handle consumer complaints and identify emerging issues.
- Include “off-grid” populations. Ensure representation of underrepresented groups by exploring supply-side data from informal financial systems and government-to-person programs. An ITU recent report shows that 32% of the global population is still offline.
- Monitor and analyze regularly. Authorities should monitor and analyze financial health indicators regularly to identify trends and potential risks for consumers. This could enable authorities to respond proactively, promoting more responsible finance ecosystems.
By testing new ways to measure financial health with supply side data, financial authorities can better understand consumers’ financial lives. This positions them to design regulation and interventions that benefit people’s financial health and ultimately contribute to broader development outcomes.
