NABFINS

Message from the MD’s Desk

The year 2014 – 15 was an eventful year for Financial Services Sector in general and financial inclusion in particular.  The financial sector landscape is undergoing drastic changes.   The launch of Prime Minister’s Jan Dhan Yojana with a slogan “sab ka saath sab ka vikas’’ has reached a significant touchstone with majority of the households in the Country being covered by at least one savings bank account. Government has now followed up this with the next step of assigning a variety of financial services such as accident and life insurance to these accounts and sending direct benefits such as scholarships, pensions and subsidies to these accounts. Converging these savings accounts with the unique ID- Aadhaar and the ubiquitous mobiles is expected to be a game changer ushering in a revolution in the financial inclusion landscape.  The Reserve Bank of India’s (RBI) initiative to further the inclusion agenda by experimenting with new institutional forms like Small Finance Banks, Payment Banks is also expected to take a shape in the near future. Another apex organisation “MUDRA Limited” was also set up and it is expected to innovate new ways of channelling credit flows to small producers.

RBI has also attempted to streamline regulations covering NPA norms, capital requirements, provisioning requirements for all NBFCs which are systemically important and that which raises public deposits. With all these introductions and policy support, the focus on diverse financial inclusion is more intense and it is expected to usher in greater competition for the micro finance sector.

For NBFC-mFIs, the year 2014-15 witnessed a rather robust growth with the Gross Loan Portfolio (GLP) reporting 61% increase to `401 billion[1] when compared to the previous year. However, the increase in client coverage was more moderate (23 %) over the previous year. This is suggestive of increased quantum of loans and higher repeat loans to existing clients rather than fresh coverage of new clients by the sector.  Although, 32 states and 489 districts are stated to be covered by mFIs, the coverage appears to be asymmetrical with about 60% of the GLP reported in from 5 states viz; West Bengal, Tamil Nadu, Karnataka, Maharashtra and Uttar Pradesh.

As compared to the industry, our Company - NABFINs disbursed `764 crore to 20,010 SHGs touching about 3 Lakh households  during the year under review which is 24% increase over `631 crore disbursed during 2013-14 to 17,027 groups (2.5 lakh households).  The unique business model of our company which essentially leverages the institutional outreach and trust capital of our B&DC based on their pre-existing relationship for financial facilitation limits much accelerated growth. However, our Company recorded a moderated and consistent credit growth with matched expansion in client outreach as well. Operations of the Company are guided by the overarching principle of supporting the National agenda of financial inclusion across all difficult geographies. Though the GOI has been pursuing the accounts for all , a true financial inclusion can happen only with supportive financial literacy. We believe that this can be achieved using the local resource persons (active members of Women SHGs) to serve as enablers of true financial inclusion process. The Company has enabled coverage of new geographies during the year viz; additional districts in the Vidharbha region of Maharastra as also in Madhya Pradesh. I am happy to report that our Company has plans to expand to few more States in the ensuing year.

The other key vertical of our company has been  financing Second Level Institutions in the form of producer collectives, Producer Companies, Societies, SHG Federations  and other legal forms of collectives which has reported a business growth  of 96% with disbursement of `22 crore during 2014-15.  With this, our Company has disbursed `40 crore to 101 institutions.  With extension of credit guarantee by RABO Bank and SFAC, all efforts will be made to hasten the growth momentum under this vertical.

It is important to bring to your notice that the rate of interest charged by our Company is by far the least in the mFI sector.  Keeping a wafer thin interest margin, our Company is able to generate adequate profit to sustain its operations.  This is despite the fact that the margin is much below the regulatory cap of 10% and provides ample proof to the fact even at this rates, the microFinance business is viable and profitable.  While there can be various reasons for higher rates of interest including the model related differences, the fact remains that it is possible to reach the poor at affordable rates through appropriate models of credit delivery. This is an affirmation to our belief system about the business model which we predominantly employ. However, with repeated cycles of credit to these groups, the group members aspire for differential treatment and seek more diverse forms of financial services, which your institution should be able to service. This would also enable the institution to de-risk, diversify its portfolio, use differentiated delivery approaches to fulfil the emerging needs of the client segment that we serve. 

The world CFSI 2014[2] report states that microFinance is close to an inflection point ; what was an experiment in bottom-up development has become mainstream world over; and with that transition have come mainstream problems and notably among them the client over-indebtedness. This is true for mFIs in the Country too; with the preponderance of group based lending methodology like JLGs and SHGs in the microFinance space. The concern of multiple membership, multiple borrowings and consequent over indebtedness of the members which poses a significant risk to the business model; while to an extent the credit bureaus do track such over-borrowings; but, the inability to capture informal market borrowings, formal credit markets dominated by cooperative credit institutions and also group based lending models like SHGs have accentuated the challenge. However, it is expected that with pervasive technology, institutional mechanisms like e-KYC, digitisation of SHG accounts etc., the risks associated with the above factors would be mitigated to a greater extent.

Our Company is exposed to various risks that are an inherent part of any microFinance business. During the year, the Company witnessed a spurt in Non-Performing Assets partly triggered by aggregation of agency risk, operational risk as well as various client level issues.  The operational risks faced encompasses Information Technology related (system) risk. With the growth and expansion of the portfolio, the existing IT system needs rapid upgradation. Therefore, the Company plans to change to an agile and robust IT infrastructure to support loan payments and collections, loan monitoring and also integrated accounting back-end on the lines of a core banking system. The other risk containment effort includes placing adequate internal & process changes, enhanced supervisory controls to prevent recurrence in future. The measures taken inter alia include prevention of NPAs by timely identification and diagnosis of problems of irregular and PAR accounts, tracking and reviewing B&DC accounts etc. Thus, the Company has adopted a twofold strategy for controlling fresh accretion and resolution of existing NPAs.  The learnings from this are being factored into our present and future business approaches. The risk management has been moved into a pro-active mode to transform role of Risk into a Strategic function aligned with Business Objectives.  A new Audit Policy is being planned to control & manage risk through internal audit functions which will gradually shift to a Risk focused Internal Audit (RFIA) mechanism.  

Another aspect which has received utmost attention of the management is development of Human Resources. Our Company ensures staff satisfaction through continuous engagements with senior management, improving staff productivity and retention. Among the mFI sector, our Company faces one of the lowest attrition rates. In order to further strengthen the human resource pipeline and to meet the skill gap requirements of the Company in new and specialized areas, it plans to selectively recruit staff from key Business schools; as also attempt knowledge / skill mapping exercises for designing training interventions. The Company has also made an assessment of the staffing requirements, HR Development and Capacity enhancement requirement and would systematically address these aspects so as to improve awareness and efficiency at all levels.

With hardly half a decade of existence, our Company is in the cusp of transformation from a provider of credit for an array of livelihood activities to a provider of a basket of financial services to the underserved segment. This institutional transformational trajectory would entail experimenting with different client centric delivery approaches, diverse financial products and services.  With this goal, our Company plans to increase its outreach, diversify its risk and put adequate systems in place with appropriate technology not only to sustain its current business operations but also to cater to its future needs.  With the able support of the promoters – NABARD and other shareholders like Canara Bank, Union Bank of India, Dhanalaxmi Bank, Bank of Baroda, our Company would be able to meet the aspirational challenges to transform itself into a small finance bank.

As a responsible corporate citizen, our Company has committed to fulfil its obligations as a part of Corporate Social Responsibility.  Under the guidance of the CSR Committee, our Company had committed to health and sanitation facilities at schools in rural areas.  I am very happy to share with you that as on date, the committed task have been completed and all these facilities have been made available for use.  For the year 2015-16, our Company intends to continue its activities for which a budgetary allocation of `45 lakh has been made.

I would be remiss, if I fail to thank, Government of India, all the State Governments where NABFINS is operating, RBI, NABARD and other shareholders, Board of Directors, Statutory Auditors, Internal Auditors and Secretarial Auditor for their guidance and support.  Finally, I would be failing in my duty if I fail to thank our primary stakeholders, especially the poor households who are our reason for birth and survival for their continued trust and belief in our approaches and business model.

I also pledge to them that we would continue to work keeping their interest as our own interest and work for their development.

Thank you.

Dr. B. S. Suran

Managing Director

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[1] Source :  MFIN – Micrometer Issue 13 – data as of 31 March 2015

[2] microFinance Banana Skins 2014; Centre for the study of financial inclusion (CFSI survey)

The excessive credit focus in Agriculture has lead us no where !...still we continue to pursue the course ?

EXECUTIVE SUMMARY - of a study by NABARD in 2015


Amongst recent policy interventions implemented to revive the languishing agricultural sector in India, those pertaining to agricultural credit have been very much in the forefront. In particular, three major policy initiatives have shaped the past decade in institutional credit to agriculture. The policy of doubling of institutional credit to agriculture between 2004-05 and 2006-07 (over the 2004-05 base year) marked the first attempt to alleviate the financial constraints of farmers. In 2008-09, the Agricultural Debt Waiver and Debt Relief Scheme (ADWDRS) was introduced to waive specific outstanding debts for a large number of small farmers; this was followed by the interest subvention scheme, that sought to remedy the perceived negative impact of the waiver on loan repayment culture by rewarding timely repayment with loans carrying lower interest rates. These three schemes combined have, implicitly and explicitly, resulted in an increasing volume of institutional credit to agriculture. Whereas credit accounted for only 16% of the total value of paid out inputs in the triennium ending (TE) 1998-99, and 26.3% in TE 2003-04, by the end of the decade, in TE 2011-12, it had risen to as high as 80.3% of the estimated total paid out costs of inputs. Despite its importance, little is known about the effectiveness of credit in supporting agricultural growth as represented by the GDP and indeed the very nature of the relationship between formal agricultural credit and agricultural GDP. This research project is a modest effort in this direction. While acknowledging that questions of the impact of credit on agricultural output or value addition or productivity are best addressed through a textured understanding of household behaviour and micro studies, this study is based on the premise that aggregate secondary data too can reveal some of these important relationships. This study uses state-level data to examine the relationship between institutional credit to the agricultural sector and agricultural GDP at the national level.

Despite serious limitations of aggregation, which typically disregards distributional issues and often masks more than it reveals, it is also true that any systematic or pervasive relationship should reflect in aggregate data and offers a level of generalization not available in small scale surveys. The goal of this study is four-fold: How productive is institutional credit to the agricultural sector? What has been the trend since mid-1990s? What are the pathways through which credit impacts agriculture? How, if at all, have these pathways changed over the years? The analysis covers the period 1995-96 to 2011-12 using data that includes all major states within India. The study also conducts, data permitting, a disaggregate analysis of two sub-periods – the first phase denoting the Pre-doubling period (1995-96 to 2003-04) and the second representing the Post-doubling period (2004-05 to 2011-12). Where feasible, the study replicates the analysis at the state level. In this study, credit is conceptualized as an enabling input that influences agricultural GDP primarily via use of variable inputs and through investments in fixed capital that support agricultural production. To the extent that credit can also contribute to consumption smoothing of borrowers or better their capacity for risk bearing, credit could have a non-specific influence on agricultural GDP via variables that are typically unobserved by the researchers. To parse this complex relationship given the limitations of data, a combination of three approaches are used. The first is a simple model that regresses agricultural GDP on current credit flow using state level data. The second method estimates a hybrid profit-production function that regresses agricultural GDP on a vector of relevant inputs, prices and agricultural credit flow during that year. This is a direct approach to estimating the relationship between credit and agricultural GDP in reduced form. The possible indigeneity of credit is addressed by the use of a control function that “controls” for the estimated endogenous component of observed credit flow. The third method represents the `pathways approach’ which estimates input demand as a function of credit, among other things and controlling for indigeneity. The coefficients representing the responsiveness of input use to institutional credit are then used as components to construct the total impact of agricultural credit on agricultural GDP. The impact of credit on agricultural output is thus derived as the sum of the contribution of credit to the use of specific inputs, capital or the cropping pattern, weighted by the contribution of these to the total value of agricultural production.

The range of estimates obtained from the various methods suggest that the credit elasticity of agricultural GDP for the entire period 1995-96 to 2011-12 is 0..21, i.e. a 10% increase in institutional credit flow to agriculture in current prices is associated with a 2.1% increase in agricultural GDP the following year expressed in current prices. When controlling for prices represented by the wholesale price index, a 10% increase in nominal credit associated with a 0.97% increase in real GDP, indicating that inflation might be eroding some of gains made in nominal terms. Compared with these results in the simple one period lag model (method 1), the estimated credit elasticity is 0.04 when the model controls for the use of inputs and a vector of input and output prices and for the possible indigeneity of credit through a control function approach (method 2). The structural model incorporating the pathways through which credit influences agricultural GDP (method 3) yields estimates of credit elasticity of 0.21. These results however have weak statistical significance. The results from a period-wise disaggregate analysis is less conclusive. While the first model suggests that the elasticity continues to be statistically significant but has weakened in the post-doubling period, the other two approaches, one that controls for prices and input and the other the captures the pathways suggest that the relationship between credit and agricultural GDP may have declined, but none of the estimated credit elasticity coefficients are statistically significant implying that the hypothesis that the credit has no association with agricultural GDP cannot be rejected.

At the state level, estimates of credit elasticity of agricultural GDP from a simple one-period lag model, the only feasible option given the data, vary mostly between 0.05 and 0.7. For only a few exceptions, the credit elasticity turned out to be statistically insignificant. Further, at the state level, the time trend of elasticity estimates varies across states. In some states the relationship appears to have strengthened post doubling whereas for others it has weakened. Further clarity and insight can only be obtained through detailed case studies or primary surveys, owing to the paucity of state level data that precludes modelling efforts at the state level. This study goes beyond to understand the precise role of credit, in other words, the pathways through which it influences or is associated with agricultural GDP. The findings from the analysis suggest that all the inputs, are highly responsive to an increase in institutional credit to agriculture, after controlling for input prices, output prices, sectoral composition of agriculture, area sown and so on. A 10 % increase in credit flow in nominal terms leads to an increase by 1.7% in fertilizers (N, P, K) consumption in physical quantities, 5.1% increase in the tonnes of pesticides, 10.8% increase in tractor purchases. The credit elasticity of new pump sets energized is however not statistically significant. A disaggregate analysis, for the pre-doubling and post-doubling phases, suggest that the relative importance of the inputs have changed. Whereas in the pre-doubling phase, fertilizers were statistically significantly responsive, in the post-doubling phase credit appears to have a strong relationship with tractors. Overall, it seems quite clear that input use is sensitive to credit flow, whereas GDP of agriculture is not. This seems to indicate that the ability of credit to engineer growth in agricultural GDP is impeded by a problem of productivity and efficiency where the increase in input use and adjustments in the pattern of input use are not (yet) translating into higher agricultural GDP. Credit seems therefore to be an enabling input, but one whose effectiveness is undermined by low technical efficiency and productivity