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Financial Literacy and Financial Inclusion

Unbundling the Nexus

Saibal Ghosh (emailsaibal@ is with the Qatar Central Bank, Doha, Qatar.

Using district-level data, the effect of financial literacy centres on financial inclusion in India is investigated. There is evidence of an improvement in the use of bank accounts over time. Robustness tests suggest that banks with a strong capital position and asset quality are more inclusive through their financial literacy centres, and the traditional bank agents continue playing an important role in this process despite non-traditional channels like mobile telephony. Yet, the findings show that the overall impact of financial literacy on bank account ownership is still limited. The analysis raises useful policy pointers to address those impediments that plague the process.

The author would like to thank the anonymous referee for the useful technical comments on an earlier draft. The views expressed and the approach pursued in the paper reflects the personal opinion of the author.

Finance has been widely regarded as a powerful intervention to foster economic growth (King and Levine 1993; Rajan and Zingales 1998; Demirgüç-Kunt and Klapper 2013; World Bank 2014; Demirgüç-Kunt et al 2015). And yet, as of 2017, roughly a third of the adults globally remain unbanked, down from nearly 50% in 2011 (Demirgüç-Kunt et al 2018). What this suggests is a discernible gap between the availability of finance and relatedly, its use.

The evidence at the global level is also echoed in the Indian context. To illustrate, although 690 million adults were added into the fold of account holders between 2011 and 2017, the extent of financial inclusion—defined as an adult (aged 15 years and above) having an account at a formal financial institution or through a mobile money provider—stood at 80% in 2017, up from 35% in 2011. What is less impressive is the use of finance. On average, 14% of Indian individuals saved at any financial institution in 2014, up just 2 percentage points since 2011. By 2017, although this increased to 20%, it was much lower than the global average of 27%. The picture is even starker when it comes to the use of formal credit with only 7% of individuals in India borrowing from a financial institution in 2017, lower than the global average of 11% and the lowest among the other Brazil, Russia, India and China (BRIC) countries (Ghosh 2019b).

Realising the not-so-impressive progress of finance, policymakers have been continuously devising innovative ways to improve financial inclusion. Most policy measures thus far have focused on the supply-side, taking the demand-side as a status quo. However, after the global financial crisis, it is being increasingly recognised that any concerted attempt to promote financial inclusion would need to take a holistic view of the process, encompassing the demand-side as well.

One area on the demand-side of the financial inclusion process that has gained currency is financial literacy. By now, there is persuasive evidence which suggests that adequate knowledge of basic economic concepts, such as interest rate compounding, inflation or financial risk diversification equips individuals to incur lower transaction fees, deleverage their outstanding debts and ensure lower interest outgo on loans (Lusardi and Tufano 2015). Central banks stand out as institutions that are leading programmes on financial literacy. Consistent with this global trend, the Indian central bank has also undertaken significant steps to promote financial literacy of its population. A key initiative in this regard has been the establishment of Financial Literacy Centres (FLCs).1 Accordingly, beginning 2007, commercial banks were advised to set up FLCs on a pilot basis in the state/union territory under their jurisdiction. How far have such FLCs been effective in improving financial inclusion remains a moot empirical issue.

Research Questions

To contribute to this debate, I have used household data across districts for 2013–15 to examine the impact of FLCs on the ownership and use of bank accounts, while controlling for other confounding factors. An analysis at the district level is important for two reasons. First, under the FLC module, each bank has been entrusted with the responsibility of acting as a sponsor bank for an allocated district within a state. Second, even within a state, there are instances where a FLC was established in a district and a contagious one where it was not.

In addition to this central issue, I explore several related questions as well. First, do bank characteristics matter for financial inclusion? Second, what are the channels through which financial literacy influences financial inclusion? I focus on several such channels to understand which of these exert a perceptible impact on financial inclusion. And finally, does the organisational set-up of FLCs exert any influence on financial inclusion?

The analysis informs the existing literature in a few distinct ways. First, my analysis is a contribution to the ever-expanding literature on financial inclusion (Beck et al 2007; Allen et al 2016; Demirgüç-Kunt et al 2018). Reviewing the recent empirical literature, Demirgüç-Kunt et al (2017) find that the evidence strongly supports the positive impact of savings account on financial inclusion and digital payments. Focusing on a cross-national sample of over 2,500 banks, Ahamed and Mallick (2019) show that financial inclusion promotes financial stability in banks with a higher proportion of customer deposits. In the Indian case, Burgess and Pande (2005) document that rural branch expansion strategy during the social banking period made a significant dent on rural poverty. Utilising state-level data, Ghosh (2019a) uncovers strong complementarities between mobile telephony and financial inclusion, an effect that was compounded subsequent to the initiation of the biometric identification (Aadhaar) process. Unlike these studies, I analyse the impact of financial literacy and find a discernible effect on financial inclusion.

Second, my analysis relates to the flourishing literature on financial literacy more broadly and for India, in particular. Studies on this issue typically pertain to the United States (US) (Lusardi and Mitchell 2013) and other advanced economies, such as the United Kingdom (UK) (Atkinson et al 2007), Japan (Sekita 2011) and Switzerland (Brown et al 2018). Others rely on cross-sectional data to decipher the association between financial literacy and financial inclusion in a cross-country context (Grohmann et al 2018). Studies for emerging economies are admittedly limited and tentative at best (Shen et al 2017; Klapper et al 2013). Prior studies for India focus on only one state (Cole et al 2011; Calderone et al 2018), one region (Agarwalla et al 2015) or based on thin samples (RBI 2017), thereby substantially limiting their policy appeal. More recent research constructs a state-level financial literacy index and uncovers wide and significant gender- and education-related differences (Gunther and Ghosh 2018). In contrast, I focus on the impact of financial literacy on financial inclusion and find a positive impact on the use of finance.

Third, the paper relates to the literature that focuses on the channels through which financial literacy affects financial inclusion. Microeconomic studies such as Carpena et al (2011), Cole et al (2011) and Doi et al (2014) hint at the beneficial influence of financial education on financial literacy, but do not delineate the possible channels of such influence. Focusing on Uttar Pradesh, Calderone et al (2018) show that financial education programme leads to a nearly 50% increase in savings for rural households. Other research emphasises the relevance of bank information policies as a useful channel that can improve financial literacy (Fort et al 2016). Taking a cue from prior research, I examine the relevance of both conventional and non-conventional channels in driving financial literacy.

Financial Literacy in India

Financial literacy has assumed increasing prominence owing to the rising complexity of the financial products and services being offered along with information asymmetry regarding the same. The growing importance of financial literacy in the quest for inclusive growth has prompted central banks to undertake necessary measures to ensure a more financially informed and literate populace.

Accordingly, in 2007, based on the recommendations of an expert committee, the Indian central bank advised the banks to set up FLCs on a pilot basis in any one district in the state/union territory under their jurisdiction. Subsequently, based on an evaluation of the FLC model, banks were advised to directly set up FLCs in each of the lead district manager (LDM) offices in a time-bound manner.

Under the stipulated guidelines, the lead bank was needed to set up FLCs with the key objectives of facilitating financial inclusion through provision of two essentials, that is, literacy and easy access, for disseminating information regarding the central bank and general banking concepts to the various target groups, and for providing education on financial planning and responsible borrowing, including debt counselling and insurance.

Beginning 2007, the FLCs were gradually established in the country.2 Figure 1 highlights the year-wise establishment of FLCs.3 Illustratively, as many as 60 FLCs were established by 2007 and over 180 districts across 20 states were covered by FLCs in 2010.

Akin to Ghani et al (2014), I have divided the sample into districts having established FLCs on or before 2009 (period 1), districts having established FLCs in 2010–11 (period 2) and finally, those districts which established FLCs after 2011 (period 3).

Such policy focus on financial literacy is not unique to India. Several countries such as Russia, Belgium, Sweden and Turkey are implementing a national strategy for financial literacy. Others such as Czech Republic, Netherlands, Slovak Republic, Spain and the UK are revising their first national strategy for financial education based on the experience gained.

Data and Key Variables

Three sets of data, namely household-level, district-level and finally macroeconomic data have been used for this analysis.

Household-level data: The household level data is obtained from the Financial Inclusion Insights (FII) survey. The FII survey is operated by the global research group InterMedia and sponsored by the financial services for the poor initiative of the Bill and Melinda Gates Foundation. For India, three survey rounds have been undertaken till 2015. In each of these rounds, the survey was nationally representative covering all major states and union territories of adult individuals (aged 15 years and above).

The surveys follow a multistage, stratified and randomised sampling design.Operationally, the sample respondents were first allotted to states in proportion to their estimated adult population and thereafter, the resultant sample was proportionally allotted to urban and rural areas. In the second stage, households were selected using the random walk method. In the third and final stage of selection, one eligible respondent in each household was selected using the Kish grid process. The current analysis uses household-level data for the relevant variables, including, inter alia, information regarding the ownership and use of bank account, the age, gender, location as well as educational and income status of the respondent.

However, several adjustments were made in the existing data. First, data for certain states such as Delhi which is included as a catch-all in the survey data were deleted, as the FLCs are disaggregated by geography (East Delhi, West Delhi, etc), making it difficult to ensure a consistent match. Second, the state of Telangana is not treated separately from Andhra Pradesh. Third, given the thinness of the sample, the smallest north-eastern states are treated as state-composite, although Assam (the largest in terms of area) is categorised as a separate state.4 After these adjustments, the final sample comprises 21 state and state composites. Comprising over 44,000 individuals each year, the pooled sample consists of a maximum of 1,33,646 individuals in a total of 538 districts (Table 1), entailing an average of 250 respondents per district.

The data also provides information on whether a respondent has access to information from traditional and non-traditional sources. Based on availability, I employ a binary variable dependent on whether the respondent (i) has a mobile and/or landline phone; (ii) has a television (TV)/DVD, and finally; (iii) utilises the services of a bank agent. I employ these as channels through which the respondent can acquire financial literacy (World Bank 2014).5

District-level data: Three key variables at the district level are used. The first is the year of establishment of FLC in a district. Information on this is obtained from the website of the sponsor bank for each state, including State Level Bankers’ Committee (SLBC) documents.6 I also extracted information on the geographical location of the FLC, (that is, rural, urban, semi-urban or metropolitan) from the website of the Pradhan Mantri Jan Dhan Yojana. The sponsor bank website also provides information on the delivery method of training by the FLC (that is, single or otherwise).7 This information was then integrated with the survey data, thereby ensuring a consistent state–district-year match of financial inclusion with the relevant information on financial literacy. I employed district domestic product per capita as a control for demand-side conditions.

Macroeconomic and banking data: First, I culled out information on the financial (for example, asset, equity and non-performing loans [npls]) and physical (for example, number of branches) indicators of the sponsor bank associated with the FLC. At the aggregate level, I employed the real gross domestic product (GDP) growth to control for macroeconomic conditions.

Ownership and use of bank account: Table 2 (p 78) shows that year-wise variation in bank account ownership and use (Panels A1 and B1) disaggregated further by state-year (Panels A2 and B2). In both the cases, I find that there has been a significant improvement, although the use of bank accounts has on average, remained roughly 20–25 percentage points lower as compared with access.

The evidence across states (Panels A2 and B2) highlight substantial variation in the ownership and use of bank accounts. Without loss of generality, states which rank high on the pecking order of account ownership also rank high on use. The year-wise correlation between ownership and use of bank account are 54% in 2013, 73% in 2014 and 97% in 2015, respectively.

Panel C of the table depicts the establishment of FLCs over time and separately at the state level. Reflecting proactive policy response, the average number of FLCs has improved over time, from 1.8 in 2013 to 2.3 in 2015.

Key variables: A description of the relevant variables, including summary statistics is in Table 3 (p 79). On the financial inclusion side, I find that 56% of respondents had a bank account, whereas only in 31% of the cases these accounts were active, reiterating the divergence between ownership (supply) and use (demand).

As regards financial literacy, roughly 10% of the FLCs were established on or before 2009 and nearly 7% were established in 2012 or after. Geographically, nearly 57% of the FLCs are in urban areas and close to 5% are in rural areas. In-house delivery of training under FLCs is most common, accounting for close to 80%. Among bank characteristics, the sponsor bank has average equity of nearly 6% of its assets with NPLs of less than 5% and profitability averaging 0.5%. Looking at delivery channels, mobile and TV are typically available with most respondents, with 50% on average reporting the presence of mobile and close to 60% reporting having a TV or DVD. Using the services of a bank agent appears to the least preferred, at less than 0.5%.

Empirical Strategy

The empirical strategy examines the impact of financial literacy on bank account ownership and use, while controlling for other confounding factors. Accordingly, for household h in district d at time t, I estimate the following specification:

Bank_acchdt= α1 + β11 FLCdt2009 + β12 FLCdt2012

+γXhdt1 +Zdt + GDPt + ε1hdt …(1)

Active_Bank_acchdt = α2 + β21 FLC2009dt + β22 FLCdt2012

+γX2hdt+ Zdt +GDPt + ρ + εhdt2 …(2)

Equation 1 is the selection equation where the outcome variable is binary if the respondent has a bank account, else zero. X1 is a vector of household controls such as gender (female vs male), location (rural vs urban), income (based on the progress out of poverty index [PPI]), work, marital (single vs otherwise) and education status; Z denotes district-level controls and X1 is the random error term.

Equation 2 is the outcome equation where the outcome variable is binary if the respondent has used a bank account in the last 90 days, else zero; X2 is a vector of household determinants and X2 is the random error term.

For proper identification, it is important that X1 has at least variable that is different from X2. In this case, I use a dummy variable that equals one if a respondent has an Aadhaar card, else zero (in X1, that is not included in X2) based on the logic that the process of account ownership necessitates a valid identification document, while it is not so in the case of use of account. Roughly two-thirds of sample respondents have an Aadhaar card.

The coefficients of interest are β11 andβ12. The former estimates the average effect of the establishment of FLCs on financial inclusion during period 1, while the latter estimates the similar effect in period 3. Provided the establishment of FLCs improves financial inclusion, these coefficients would be positive. It can be argued that unobserved factors may influence the outcome variables in equations (1) and (2); in other words, the correlation (ρ) between ε1 and ε2 is non-zero. The Heckman Probit model addresses the sample selection bias by estimating the Inverse Mills ratio and adding to the outcome equation as an independent variable.

Results and Discussion

The estimation results are set out in Table 4 (p 80).

Access and usage of accounts: The coefficient on FLC is not statistically significant in column (1), suggesting that the establishment of FLCs does not exert any perceptible impact on access to bank account.

On the other hand, the coefficient on FLC 2009 equals -0.088 (column 3), so that initial FLCs dampen the use of bank accounts by roughly 9 percentage points. One way to interpret these results would be to suggest that during the initial days of the programme, awareness regarding the FLCs was limited. Besides, the FLCs were serving mostly walk-in clients; outdoor literacy drives were an exception. In addition, the literacy material available at the FLCs was primarily publicity material pertaining to various products of sponsor banks. As a result, the FLCs were not in a position to maintain arm’s length distance from sponsor banks, negating the very efficacy of the scheme.

The next set of estimation examines the relevance of geographical location of FLCs for financial inclusion. If the FLCs in a particular location affects financial inclusion, the interaction term would capture these differences. In column 4, I find that the interaction term FLC2009*RURAL is positive and statistically significant, so that the FLCs established in rural areas are more influential in positively impacting the access to bank accounts. When I look at the use of accounts, column 6 shows that the coefficient on FLC 2009 is negative, while that on FLC 2012 is positive. Both of them are statistically significant. In other words, the FLCs established at a later period positively affected the use of accounts; those established earlier were less effective.

Relatedly, the FLCs established in urban areas exert a positive impact on the use of bank account: a one standard deviation increase in urban FLCs is associated with a 9 percentage point increase in the use of accounts, an increase of nearly 30% relative to the mean. More generally, recognising the limitations of the initial training modules, the banks started preparing financial literacy material in vernacular languages using stories and pictorial representations, improving its appeal and accessibility to the respondents. The role of the financial counsellors was also streamlined, including improvements in staffing, resources and infrastructure, as well as their capacity-building. All these factors could explain the efficacy of the FLCs at a later date.

Summing up, the key takeaway is that FLCs are more effective in influencing the use of accounts as compared with access. I next undertake several robustness tests of the baseline findings.

Robustness tests: Several robustness tests are done to explore the relevance of sponsor bank characteristics, to analyse the usefulness of the various channels of financial literacy, and finally to understand the relevance of the delivery method of financial literacy in affecting financial inclusion. As earlier, all specifications include the full set of controls, but these are not reported for brevity. Estimation results are set out in Table 5.

Bank characteristics: Across columns (1) to (3), three key findings are of interest. First, and more generally, the impact of bank characteristics on financial inclusion operating via FLCs is manifested only in the later period. The coefficient of the interaction terms of FLC 2009 with each of the bank characteristics is not statistically significant. Second and in terms of specifics, the coefficient on FLC2012*NPL is negative and statistically significant both with regard to financial access and use, implying that banks with higher loan delinquency are less able to devote resources towards fostering financial inclusion. Third, establishment of the FLCs by sponsor banks with bigger branch network does not necessarily translate into financial inclusion, indicating that the physical branch infrastructure is not a necessary condition for improving financial inclusion. Based on the point estimates, a 10% increase in FLCs established by sponsor banks with low NPLs is found to increase the use of finance by 2.8% more vis-à-vis banks with high-NPLs, and alternately by 9.5% more for well-capitalised vis-à-vis low-capitalised banks.

Financial literacy channels: Next, I examine the channels through which financial literacy influences financial inclusion. Three features are of note in columns (4) to (6). First, all of the identified channels played a role in improving financial inclusion: the coefficient of each of the variables is generally significant across most specifications. Second, most of the interaction terms of FLCs with the identified channels were insignificant during the initial period. Third, as the process gathered momentum and the awareness about bank agents and financial literacy centres increased, the net effect was an improvement in financial inclusion. This is reflected in the fact that the interaction terms when significant, are positive.

Delivery method: The final set of columns examines the relevance of the delivery method of financial literacy in impacting financial inclusion. Results set out across columns (7) to (9) show that financial literacy programmes delivered in-house exert an impact on the use of bank accounts, primarily in the latter period.

To sum up, the findings indicate that FLCs established by well-capitalised sponsor banks with low levels of problem loans are better equipped to ensure financial inclusion. In addition, the results also show that both traditional as well as non-traditional channels are able to improve financial inclusion, although their impact via FLCs is manifested at a later period.


By now, there is substantive evidence which suggests that financial literacy can improve the efficacy of financial decision-making. However, there is limited evidence as to whether better financial decision-making is manifested in improved financial outcomes. Empirically, it is challenging to disentangle this effect since other unobserved factors could be driving both these observables. To address this shortcoming, I exploit a clear identification strategy to analyse the impact of financial literacy on financial inclusion. To the best of my knowledge, this is one of the earliest studies to examine the relationship between financial literacy and financial inclusion at the country level.

I have uncovered three important findings. First, the FLCs are more useful in influencing the use of bank accounts as compared with access. Importantly as well, the FLCs established at a later period were more effective in positively affecting the use of bank accounts as compared to those established initially. Second, well-capitalised banks with lower problem loans are better placed to deliver financial inclusion through their FLCs. Interestingly, neither bank size nor branch network appear to significantly influence financial inclusion. Third, notwithstanding the growing importance of electronic channels, traditional channels still remain relevant in impacting financial inclusion positively.

Correspondingly, the analysis raises useful policy pointers. First, that financial literacy has played an important role in improving account activity, but its impact on the access to bank accounts has been less compelling. This needs to be viewed in the context of the 60 percentage point gap between access to and use of finance for India (Demirgüç-Kunt et al 2018). Second, the growing efficacy of financial literacy during the latter stages suggests that addressing the impediments which plagued the process during the initial phase played an important role in furthering financial inclusion. It, therefore, becomes important to address the specific micro-level impediments that can further enhance its efficacy. Third, while there is no gainsaying the growing importance of electronic channels towards acquiring financial literacy, the role of traditional channels such as bank agents highlights their importance in augmenting financial literacy. Identifying appropriate “teachable moments” at various levels can enhance financial capabilities, make the financial literacy process more relevant and, in turn, the promise of a better outcome in the medium term.


1 In India, these FLCs also double up as credit counselling centres (CCCs). This contrasts with the experience of other countries that have dedicated Consumer Credit Counselling Service (CCCS), such as the National Foundation for Credit Counseling in the United States, the CCCS in the United Kingdom, the Credit Counseling Canada in Canada, Credit Counseling and Debt Management agency in Malaysia and the Credit Counseling of Singapore in Singapore, among others.

2 This has been complemented with several other initiatives, including a Financial Awareness Message booklet containing messages such as documents to be submitted while opening a bank account (KYC), maintaining creditworthiness and timely loan repayment. A pictorial booklet series titled “Raju” provides information about basic banking concepts while the “Money Kumar” clarifies the role and functions of the Indian central bank.

3 Up to 2015, coinciding with the final wave of survey data.

4 The state of Jammu and Kashmir and two union territories (Andaman and Nicobar Islands, and Lakshadweep Islands) were not part of the survey.

5 The data does not provide information as to whether the respondent has access to or reads a newspaper.

6 SLBC is an inter-institutional forum at the state level ensuring coordination between government and banks on matters pertaining to banking development.

7 For example, the Jnana Jyoti financial literacy and credit counselling trust is sponsored jointly by Vijaya Bank and Syndicate Bank, and likewise, Bank of Baroda has opened a financial literacy and credit counselling centre termed Sarathee. State Bank of India in contrast, runs its own financial literacy programmes.


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Updated On : 29th Mar, 2019


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