Towards a Shared Framework for Measuring Financial Inclusion and Well-being

This article explores the significance of financial inclusion in determining the financial well-being of Indian households. It discusses a measurement framework developed by Dvara Research and xKDR Forum, focusing on access to and usage of financial products, and financial well-being. Our results from collaborative research with financial service providers shed light on the framework’s applicability and its relationship with improved financial outcomes.

There is a widely shared agreement on the significance of financial inclusion, leading to concerted endeavors aimed at enhancing accessibility of financial services both through financial sector entities and government-led initiatives.  While the significance of financial inclusion is acknowledged, there is a lack of consensus on a set of universally accepted metrics to gauge its effectiveness. This gap underscores the importance of developing robust measurement frameworks for the same. One such attempt is made by Dvara Research and the xKDR Forum to assess the impact of financial inclusion initiatives. Dvara Research and xKDR Forum, over the past few years, have come up with a financial inclusion measurement framework that takes into account the level of access to financial products, usage of the products owned by households, and the reported levels of financial well-being. The measurement framework establishes an inputs, outputs, and outcomes framework to ascertain if financial inclusion (product ownership and usage) is associated with better levels of financial well-being. This framework has been applied to customers of microcredit institutions, self-help groups, and digital lending and, although these surveys have been conducted over different time periods, we delve into the results of the study on how these models compare. To validate the measurement framework, we administered the survey tool among different segments of low-income households. This allowed us to assess its applicability and effectiveness across diverse lending models. Once the framework was deployed, we aimed to test the relationship between financial inclusion and financial well-being.  

So far, we have run three iterations of this survey to validate the tool and see if the hypothesised relationship between access, usage, and financial well-being, namely that increased access and usage are associated with higher reported financial well-being, is robust. These surveys have been conducted in partnership with financial service providers (FSPs), given their role in serving the financial needs of their customer segment. In the following paragraphs, we will discuss the key results of the surveys.

The first round of the pilot study was administered to 310 households from Tamil Nadu and Chhattisgarh. These households were part of a Joint Liability Group (JLG) company and belonged to the low-income household category with an average annual income of about 1.92 lakhs INR. Most households drew their primary income from a regular salary-earning occupation or were self-employed in the non-agricultural sector. We found that the average input score for the households was 0.22, meaning that they owned between 1-2 financial instruments. Their output score was slightly lower (0.19), which translated to active usage of one of the financial instruments. Their reported financial well-being levels were, however, much higher with their average outcome score being 0.52. 

For another iteration of the study, we administered a revised version of the questionnaire among 1022 households in Chhattisgarh, Rajasthan, and Tamil Nadu. Our sample was primarily rural and while 33.86% of the sample was regular wage-earning or salaried, a major part of the sample comprised self-employed in non-agriculture (22.31%), casual labour in non-agriculture (17.91%) and self-employed in agriculture (17.81%). Their reported average salary was 2 lakhs INR per annum. Since the households accessed loans from three organizations out of which two were Microfinance Institutions (MFIs) and one was a Self-Help Group (SHG), the survey allowed us to tease out the reported levels of access, usage, and financial well-being for customers who were associated with different business models of lending for low-income households. Moreover, customers associated with the SHG model also had access to a group-based saving channel. We hypothesized that because of accessing finance through different financial channels, the households would potentially report differing levels of inputs, outputs, and outcomes. These scores can be found in Table 1. 

Finally, we ran an iteration of the survey on 1343 digital lending customers and found that their reported levels of financial well-being were significantly higher, as can be seen in Table 1. We administered only the access and financial well-being questions to this cohort. 79.30% of the digital lending customers belonged to the regular wage-earning category. Additionally, a majority of digital lending customers reported falling in the 5 to 10 lakhs per annum income category. As these customers reported better financial well-being, it suggests that income positively correlates with the reported levels of financial well-being among households. 

Table 1: Average inputs, outputs, and outcomes score

Note: Round 1 for MFI 1 was conducted in July 2021. The retail digital lending customers were surveyed in February 2023. Finally, round 2 for MFI 1 and the surveys for MFI 2 and SHG were conducted in April 2023.

In comparing the SHG and JLG models within the microfinance landscape, it is crucial to recognize the different design principles that underpin their operations. The key differences between JLGs and SHGs lie in their operational dynamics: SHGs engage in collective saving and are driven by collective decision-making and shared financial responsibility, inherently fostering a communal approach. This communal ethos may lead to better levels of access, usage, and financial stability among members. SHGs also interface more with the banking system, potentially enhancing familiarity with various banking products. Consequently, disparities in reported financial inclusion metrics may emerge. We find that households associated with an SHG report relatively higher levels of inputs and output compared to other models. However, the highest outcome scores are reported by digital lending customers. 

The regression results in each iteration showed a positive association between the financial well-being score and the socioeconomic factors of the households, meaning households with better income levels and physical asset ownership would also have higher financial well-being. We also found a positive association between the input scores and the outcome scores. This means that better levels of financial access are associated with higher reported levels of well-being.   

Although finance did seem to matter, it is only one of the many factors that influence the financial well-being of households. Social ties and informal strategies play a significant role, with formal channels representing only a fraction of the overall influence. In the first iteration of the survey, we included a question on whether households reported feeling confident in their financial future and found strong perceptions of well-being, even in cases where financial inclusion was not evident.

Our results illustrate that households often adopt a blend of formal and informal methods. This indicates a diversified approach to managing financial well-being, extending beyond conventional metrics such as ownership of financial products and their usage levels. In the distinctive context of India, social capital could greatly influence financial well-being. Notably, the value of R2, which indicates the explanatory power of the studied independent variables in a regression model, suggests that 15% of the variation in financial well-being is attributed to access to finance and its usage. This underscores the necessity for exploring a more nuanced understanding of the dynamics of financial well-being in poor, rural communities.

In conclusion, while the multiple iterations of the survey conducted in partnership with different FSPs helps shed light on the complex relationship between financial inclusion and well-being in the context of India, it also unveils some areas for further exploration. Firstly, there is a gap in our understanding of the financial well-being of the urban poor owing to the scarcity of readily available data on this demographic. Urban poverty presents unique challenges and opportunities that demand specific attention within the financial inclusion discourse. Secondly, there is a need to conduct surveys that capture well-being on a continuous basis, which will enable us to capture the evolving dynamics of financial well-being and inclusion, providing a more comprehensive understanding of long-term trends and the effectiveness of interventions. Thirdly, to create a global benchmark against which the well-being of households in different countries can be compared a set of common metrics are needed. While these common metrics could apply to any household, they need to be complimented with some context-specific questions such that the reported results of the households can be contextualized with their local reality. Some of these contextualizing questions could be aimed at understanding how the cultural traditions of a certain group might encourage or discourage certain financial practices and behaviors, what the prevailing attitude of a group might be towards formal finance, etc. These suggested research areas will enhance our understanding of financial inclusion and allow for a broad spectrum of strategies to address diverse issues that affect the financial well-being of low-income households in India.