Ramesh S Arunachalam
We hear a lot from central bankers on financial inclusion these days. That is welcome for a change but there is so much that every CENTRAL BANK can do to bring transparency to the financial inclusion process.
Let me start with the definition of financial inclusion and data pertaining to the same, as my first article in a series that will look at measurement of financial inclusion and related aspects.
Without a clear definition of financial inclusion and good ground level data, much of what we say in terms of inclusiveness in the financial sector is analogous to writing on water. Additionally, without proper baseline data, quoting facts and figures is meaningless as then, we would not be able to attribute whether financial inclusion occurred because of something we did consciously or it was simply an accident and/or act of GOD.
Having an internally consistent definition of financial inclusion is very critical. And generating data based on the same is even more important. Together, these can form the basis for our opinions and judgements, which in turn can shape policy and subsequent implementation appropriately.
Let me take the Indian context and much of this applies elsewhere too.
It follows from the above that we first need a reliable and valid definition of financial inclusion in terms of type of products and services (for example, it could be loans, savings, insurance, remittance, literacy and financial education services, ombudsman services etc) accessed through different institutions (Banks, Insurance Companies, SHGs, MFIs, Business Correspondents, Cooperatives etc) by various kinds of mutually exclusive individuals/households from different segments of society (especially, low income and excluded groups).
Please note that some of these financial inclusion services could be one time services (like going to an ombudsman), others (like loans) may be repeat services and some others like savings accounts (or pension accounts) could even be continuous long-term services.
Likewise, several institutions may combine to form a channel – for example, I could get a loan from an SHG that is linked to a bank which has been refinanced by a DFI like NABARD. I could also get a loan from an MFI that has borrowed from a DFI (SIDBI) and is on-lending to me. I could also get a loan from a small finance bank or a microfinance bank that accepts public deposits. And some this can happen digitally too! The permutations and combinations are endless here but please note that the above distinction between channels and institutions is very important for determining correct outreach of financial inclusion!
In fact, the real outreach of our financial inclusion services through the various channels and institutions is not transparently known today. I have said this before and I am saying it again. This is because there is overstatement of outreach figures through double and triple counting as sometimes data of different institutions within a channel is added up to give an incorrect outreach figure.
Sometimes, people have genuinely accessed services through different channels as well. This again provides an exaggerated picture of total outreach and penetration with regard to financial inclusion.
Given the above, the Reserve Bank of India’s (RBI’s) first task would be to ensure that it puts out a proper working definition of “financial inclusion” and ensures that all stakeholders promoting and/or looking at financial inclusion use the same consistent definition. Otherwise, outreach figures on financial inclusion would be meaningless and cannot be evaluated or compared in a serious manner.
A second important task for RBI is ensure that proper data (which can then become a baseline going forward) is available with regard to financial inclusion. Here, the priority task would be to know ASAP:
a. How many mutually exclusive individuals and mutually exclusive households have been financial included in any given financial year?
And when we say financially included, we need to be able to disaggregate this figure in terms of services/products accessed by these mutually exclusive individuals/families through different channels (and their institutions) and across various regions/states in India. If this basic data becomes available, then, we can analyse the data to get better analytics about the rural-urban divide, demographics and so on
As someone who has worked in over 570 districts of India over the last 28 years, I can say that the data with regard to SHGs needs to be more transparently and accurately estimated. What is lacking is objectively verifiable data on the number of well functioning SHGs, their demographics with transactions on loans and savings, overlap of members across SHGs (many SHGs have dual membership or in some cases, I have even seen membership in three to four SHGs) and the like.
Likewise, we lack transparent and accurate data with regard to MFIs and their clients as well. There is so much of overlap in clients across MFIs (as evident from the 2010 AP crisis) and I have repeatedly told MIX MARKET about problems with regard to their using MFI self-reported data.
Similarly, clients appear to be shared significantly across the MFI, the SHG Bank linkage, Cooperative and other models. All of these lead to significant exaggeration in outreach data.
Further, data on KYC, priority sector lending including to agriculture, BC models, insurance services and pensions also have their problems and thereby contribute to outreach exaggeration.
Thus, given that there is so much double and triple counting and exaggeration in the outreach data, it is imperative that we know the real outreach in terms of mutually exclusive individuals first and as mutually exclusive households next. I hope the RBI will set in motion appropriate processes so that transparent data which can lend itself to objective field verification is publicly available. We need to know how many mutually exclusive individuals/households have been reached by various financial inclusion efforts and this would also entail significant coordination with other regulators like IRDA and PFRDA, which again, the RBI, as the primary financial services regulator, would need to ensure through appropriate mechanisms.
b. And once we have the above basic data, we can then get to understand whether people who were financial included in a given year continued to be included in the subsequent years?
Now we get an interesting aspect and that is the dynamic nature of financial inclusion! Most people assume financial inclusion is a one time or static phenomenon. On the contrary, it is dynamic one where people float in and float out of the financial inclusion eco system. It is very similar to concept of floating population in big metros like Delhi or Mumbai or New York!
Take the case of all the clients who had their loans waived off as part of the farmers’ loan waiver scheme some years ago! After the waiver, several of these clients were classified as defaulters by the respective banks and hence, they could not regain access to the formal financial services that they once had been able to access. Likewise, as a Moneylife article (Financial inclusion of sugarcane farmers in modern-day India) showed, many sugar cane farmers who were once included (by virtue of having got a bundled loan for sugarcane) were subsequently excluded for reasons mentioned in the article. The same is the case with the 2010 AP micro-finance crisis where most of the clients in AP who did not pay back at the height of the crisis are now classified as defaulters (both in general terms as well as in the credit bureau) – as a consequence, no formal or quasi formal financial system will touch them hereafter. In fact, the erstwhile IRDP (Integrated Rural development Program) had included millions of people way back in the 1980s but many of these people left the financial ecosystem for various only to be re-included through some other scheme/program later. While I could give many more examples, the key issue here is that anyone who is included financially need not stay included always.
The above also implies that the linkage cited between ‘financial inclusion’ and ‘inclusive growth’ is at best tenuous because of the following aspects:
- Not all people who are financially included stay that way all the time. They float in and out of the financial eco system due to circumstances beyond their control and this is especially true of low income people in the urban informal sector and the rural poor
- Not all financially excluded
people are poor and vulnerable. Fox example, a large number of medium sized
traders and farmers in small shanty towns tend to be excluded for the
formal financial system but they are not necessarily poor or vulnerable.
And it is such people who have a better chance of staying financially
included, once they have gained access to a formal financial service
To summarise, the larger point that I am trying to make are the following:
a. We are in urgent need of a proper working definition of financial inclusion that can lend itself to reliable and valid measurement,
b. We require data on mutually exclusive individuals and households who have been financially included (in a given year),
c. We also need to have data on how many such mutually exclusive individuals and households who were financially included in a given year stayed included in the subsequent years, and
d. Lastly, we also need data on how many new mutually exclusive individuals and households enter the financial inclusion eco system in any given year?
And all of this data must be capable of disaggregation by products/services, channels (and their institutions), states/regions and so on. Only then will we be able to make meaningful analysis of all the hype surrounding financial inclusion.