Indian Growth and Development Review
Measuring total factor productivity change of microfinance institutions in India
using Malmquist productivity index
Dilip Ambarkhane, Ardhendu Shekhar Singh, Bhama Venkataramani,
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Measuring total factor
productivity change of
microfinance institutions in
India using Malmquist
productivity index
Downloaded by Stockholm University Library At 08:34 08 December 2018 (PT)
Dilip Ambarkhane and Ardhendu Shekhar Singh
Symbiosis School of Banking and Finance, Symbiosis International
(Deemed University), Pune, India, and
Malmquist
productivity
index
Received 13 December 2017
Revised 9 May 2018
18 September 2018
12 October 2018
Accepted 16 October 2018
Bhama Venkataramani
Symbiosis International (Deemed University), Pune, India
Abstract
Purpose – Microfinance institutions (MFIs) provide small loans and other financial services to the poor.
These institutions are established for helping the poor to raise income levels and to reduce poverty. Recently,
MFIs are required to reduce their dependence on grants and subsidies. Consequently, they face conflicting
objectives of improving reach and profitability. These can be achieved by improving productivity. This paper
aims to investigate productivity change in 21 major MFIs in India which are rated by Credit Rating and
Information Services of India Limited in 2014.
Design/methodology/approach – This paper attempts to examine total factor productivity change in
21 major Indian MFIs during the period from 2014 to 2016 using Malmquist productivity index. The inputs
and outputs are selected considering objectives of outreach and financial sustainability. The authors have
categorized MFIs in three categories, namely, large, medium and small, depending on asset size.
Findings – It is revealed that large MFIs are able to catch up with industry best practices by improving
their systems and processes, but they need to improve scale efficiency. The Reserve Bank of India has
recently initiated a policy of granting banking licenses to those financial institutions which have good
outreach and are financially strong. It can be used for shortlisting MFIs before granting permission to operate
as banks. The method can also be used for benchmarking them for productivity. It can also be replicated in
other countries.
Originality/value – In India, MFIs are playing important role in economic development by providing
microcredit to the poor. However, very few studies have been undertaken regarding productivity of MFIs in
India. The present study intends to fill this gap. It will facilitate benchmarking of MFIs as competitive and
sustainable financial institutions catering to the requirements of small borrowers.
Keywords India, Microfinance, Technical change, Total factor productivity, Malmquist
Paper type Research paper
1. Introduction
Microfinance industry is growing all over the world as it is attracting large sums of public
and private investments and most of these investments are “for-profit” (Copestake, 2007).
Several microfinance institutions (MFIs) are scaling up and a few of these have been
JEL classification – D24, G21
Indian Growth and Development
Review
© Emerald Publishing Limited
1753-8254
DOI 10.1108/IGDR-12-2017-0105
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IGDR
converted to banks especially in Latin America (Drake and Rhyne, 2002). To attract
commercial funds for scaling up, it is necessary to focus on financial performance and MFIs
run the risk of neglecting the social mission in the process (Greeley, 2006). Cull et al. (2009)
observe the necessity of commercial investment in microfinance industry and remark that
such institutions, with robust social mission, are in the best position to serve the poorest of
the poor. The authors observe that though the market is a strong force, the poor will not be
served without appropriate interventions.
Anyanwu (2004) identifies several challenges of growth to MFIs in Nigeria, such as funding,
sustainability and regulatory framework. González Vega (1998) observes that MFIs face major
challenges due to competition, state intervention, systemic risks and improper regulation.
The rapid expansion of loan portfolio increases credit default risk due to faulty
assessment. Moreover, expansion in new geographical areas involves higher infrastructure
cost. So there is also a risk of lapses in monitoring of loans due to burden on the system.
Therefore, fast growth is likely to weaken sustainability and there is a possibility of losing
focus on mission. Thus, ensuring healthy growth is a tough challenge before MFIs in India
and elsewhere (Schreiner et al., 1996).
MFI managers have to balance financial efficiency with the objective of providing quality
services to the poor and it is a challenge for regulators to provide regulatory framework
which will facilitate scaling up of microfinance with a focus on mission (Ahmed, 2005).
Microfinance sector in India, boosted by large scale private and foreign funds,
experienced a rapid growth during 2005 to 2010. High growth exposed microfinance industry
to various risks leading to serious irregularities such as, multiple lending, exorbitant interest
rates and use of coercive means of recovery. In 2010, Andhra Pradesh Government curbed
the activities of MFIs, which led to crisis in microfinance industry in India.
After the crisis, MFIs in India had taken several steps to improve productivity such as
use of information technology, rationalization of network and setting up of self-regulatory
organization. In 2012, the Reserve Bank of India had also issued regulatory guidelines.
Microfinance sector had recovered from the crisis by 2012 and had picked up further rapid
growth (IFMR Investments, 2014). During the period from 2012 to 2016 gross loan portfolio
of microfinance industry in India grew by 376 per cent from Rs 111.83bn to Rs 532.33bn
(Micrometer, 2016).
In 2015, RBI has granted “in principle” licenses 10 MFIs for working as small finance
banks (SFBs). In the new competitive environment, there will be pressure on profitability of
SFBs. It is likely that these will lose focus on financing the poorest of the poor. This paper
examines the question:
Q1. Whether microfinance industry in India is undergoing mission drift in the process
of scaling up?
It is necessary for MFIs to be financially efficient with a focus on financing the poor.
Moreover, few studies have concluded that financial sustainability and social efficiency can
both be achieved (Mersland and Strøm, 2010; Quayes, 2012; Louis et al., 2013).
This paper also attempts to provide a metrics to managers of MFIs, SFBs and regulators
that will help them measure the financial sustainability without losing focus on financing
the poor; especially during the period of growth.
1.1 Measurement of productivity
Productivity may be measured using a single factor index or a multi-factor index. However,
the single factor index is not an appropriate measure of the productivity of a firm because
there are multiple inputs/outputs and multiple factors affecting the productivity of a firm.
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Schreiner et al. (1996) attributes the success of Banco Sol to multiple factors such as its
improved operational efficiency, development of appropriate technology and efficiency of
scale while it was facing challenges that come with scaling up and rapid growth. Malmquist
productivity index, which is a multi-factor productivity index, comprises three indices
namely, technology change index, technical efficiency change (TEC) index and scale
efficiency change index and is a robust and appropriate measure of sustainable, multi-factor
productivity.
We have used the Malmquist multi-factor productivity index to measure the productivity
of selected MFIs. The inputs considered are, own funds and long term borrowings whereas
loan amount outstanding and profit are taken as outputs. Productivity of MFIs is found to
be impacted by several factors such as profit motive, geographical reach, business model
and market share.
This measure of productivity confines itself to measuring financial sustainability only;
whereas, MFIs have the dual objectives of achieving profitability and serving the poorest of
poor. Gebremichael and Rani (2012) observe that the objectives of double bottom line are
apparently conflicting in nature. Therefore, pursuit of financial sustainability alone will
cause the firm to drift away from the mission of financing the poor. So, a measure of
productivity capturing both dimensions will be a more comprehensive reflection of
productivity.
To examine mission drift, we use four parameters, namely average loan size, market
(rural/urban), focus (favorable bias towards women), lending methodology (group/
individual) as identified by Mersland and Strøm (2010). We found that there is a strong
mission drift in pursuit of financial sustainability.
To measure productivity comprehensively, we have developed an evaluation metrics
combining the Malmquist index along with the parameters suggested by Mersland and
Strøm (2010) which captures both financial sustainability and the extent of mission
attainment.
This will help the MFIs design a strategy to strike a balance between the conflicting
objectives of ensuring sustainability, while simultaneously controlling mission drift during
the period of high and rapid growth. This tool will also be useful for MFIs in establishing
internal controls. Further, this tool will allow the MFIs to identify the better performers in
the industry. In addition, regulatory bodies may use this tool for shortlisting MFIs for
licensing as SFBs.
The study is important because in the absence of benchmarking, internal controls and
robust regulatory framework; microfinance industry in India is likely to lose focus and
plunge into another crisis. As revealed through literature, very few studies have been
undertaken regarding productivity of MFIs in India. The present study intends to fill this
gap.
We have studied the productivity change in 21 major MFIs in India (with 2012 as base
year), which are rated by Credit Rating and Information Services of India Limited (Ratings,
2014). The sample constitutes 80 per cent of the market share measured by gross loan
portfolio.
This section is followed by literature review and Section 3 explains the methodology.
Section 4 contains findings and discussions and Section 5 deals with conclusion and policy
implications.
2. Literature review
The mission objectives of MFIs are to offer a wide range of services such as micro credit,
micro insurance and micro pension. Littlefield et al. (2003) observe that microfinance creates
Malmquist
productivity
index
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IGDR
wider socio-economic impact on the lives of the poor. Improvement in income levels of the
poor enables them to invest in children’s education and health. In addition, female clients of
MFIs become more confident with an increase in their income levels and their say in
household matters increases. This also enables them to fight gender inequalities in a better
way. Therefore, scaling up and growth of microfinance is necessary for achievement of
mission objectives.
Microfinance industry was dependent on grants and subsidies in early stages of its
development. However, of late, there is pressure on MFIs for reducing dependence on these
sources of finance and becoming financially self-sustainable. In the process of achieving
sustainability and scaling up, some MFIs are drifting from their mission which reflects in
their preference to increase profitability rather than to serve the poorest of the poor (Rauf
and Mahmood, 2009). As a result, they are financing marginally poor or non-poor and are
excluding extremely poor people. Muhammad Yunus (2011) commented that
commercialization is a worrisome “mission drift” for MFIs.
As such, MFIs face challenges of double bottom line viz. increasing outreach by
providing financial services to the poor and at the same time maintaining financial
sustainability (Hartarska, 2005; Otero, 1999; Brau and Woller, 2004).
2.1 Mission drift
Growth and scaling up of microfinance programs in India and elsewhere, are necessary, as it
is beneficial to the poor. However, commercial funding which is required for scaling up, can
result in excessive focus on profit at the cost of social objectives. So also, growth comes with
inherent challenges causing strain on profitability which may also lead to willing or
unwilling sacrifice of social objectives by MFI managers.
Hishigsuren (2007) has studied mission drift in respect of a microfinance organization
which serves poor women in rural India. The author found that mission drift of that
organization is not a planned decision of management but it is an outcome of the scaling up
process and the challenges that came with it.
However, some authors support the view that so long as there is overall poverty
reduction, there is no mission drift and MFIs need not necessarily serve the poorest of the
poor. Ghosh and Van Tassel (2008) offer theoretical explanation to the phenomenon of
“mission drift”. They observe that to be sustainable, MFIs move its portfolio from the
poorest of the poor to the less poor borrowers. This results in high profitability which in turn
increases their capability for reduction in poverty on a larger scale.
Serrano-Cinca and Gutiérrez-Nieto (2014) observe that mission of MFIs is poverty
reduction and women empowerment with a focus on rural people. The authors have
observed a mission drift in case of some MFIs.
In the process of scaling up and ensuring financial sustainability, MFIs may drift from
their mission. However, some studies have found that objectives of financial and social
efficiency are not necessarily inconsistent with each other.
Salim (2013) has studied objectives of profitability and poverty reduction in respect of
two largest MFIs operating in Bangladesh. The study reveals that the choices of branch
locations were driven more by poverty reduction parameters rather than those of profit
maximization.
Quayes (2012) has studied the relationship between financial self-sustainability and the
depth of outreach of MFIs in respect of 702 MFIs from 83 countries. It was found that
increase in outreach has positive relationship with financial sustainability. The study
concludes that attainment of financial sustainability is not a hindrance for achieving better
outreach.
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Louis et al. (2013) have examined whether increased focus on sustainability reduces
social impact of MFIs or otherwise. Contrary to the concerns, the study found that financial
efficiency is positively related with social efficiency.
Mersland and Strøm (2010) have studied mission drift in microfinance industry in the
world spanning 11 years (1998-2008). The authors have studied “rated” MFIs in 74 countries
using average loan size, market (Rural/Urban), bias towards women and lending
methodology (individual vs group) as mission parameters. They have found that there was
no evidence of mission drift.
2.2 Measuring efficiency of microfinance institutions
Many researchers have considered outreach and sustainability as the two most important
parameters to assess the performance of MFIs. Table I gives details of parameters used by
various researchers for measuring efficiency of MFIs.
There are two approaches to measuring efficiency of MFIs, namely, production approach
and intermediation approach (Wijesiri et al., 2015). The production approach considers these
institutions as firms which create financial products and services using manpower,
materials, technology and related costs. The intermediation approach, on the other hand,
views them as intermediaries which convert labor and capital into loans for the borrowers.
Irrespective of the approach, the productivity of MFIs should be measured on both
parameters, namely, social efficiency and financial sustainability (Mersland and Strøm,
2009).
The researchers have used number of persons, expenses or costs and/or total assets as
inputs. Data envelopment analysis (DEA) methodology considers a production-like
environment, in which inputs are converted to output. In a production process, inputs (as
envisaged in DEA) are considered identical in terms of utility. However, this does not
apply to persons working in an organization, as every person is different and has
different capabilities; moreover, these capabilities are subject to growth or diminution
depending on motivational factors. As such, number of persons in different
organizations, as an input, is not comparable and hence inappropriate. Also, the
researchers have not measured the efficiency with respect to the financial sustainability
and mission objective distinctly.
The researchers have found that financial sustainability and mission objectives are not
necessarily in dissonance with each other and that there are microfinance programs across
different parts of the world which are financially and socially efficient. This paper attempts
to measure the efficiency of MFIs considering both parameters namely, financial
sustainability and attainment of mission objectives, during the period of high and rapid
growth.
To measure financial sustainability, the authors have considered financial intermediation
approach. As per this approach, MFIs convert capital and borrowings (Liabilities/Resources)
into loan portfolio, thus generating profit. In India, MFIs are not allowed to accept deposits.
Therefore, capital and long term borrowings are appropriate inputs. The inputs such as cost
or expenses are considered while arriving at the profit.
To measure the attainment of mission objectives the authors have considered the ratio of
average loan size of MFIs to the average loan size of the industry, market coverage (urban,
rural), gender and lending methods as suggested by Mersland and Strøm (2010).
Serrano-Cinca and Gutiérrez-Nieto (2014) also observe that mission drift measured in
terms of increase in loan size is in consonance with objective of poverty reduction.
Malmquist
productivity
index
Table I.
Details of inputs and
outputs used by
various researchers
Labor cost and
Non-labor costs
Parameters used
Input
Number of savers
Number of borrowers and
Number of groups
Output
(continued)
The authors have used two social outputs (number of women borrowers and the index of poverty) and have found a positive, but low, correlation between social
efficiency and financial efficiency
Hassan and Sanchez (2009)
Total financial expenses(Financial expenses plus loan Gross loan portfolio
Total funds(savings or funds provided by third
loss)
parties)
Operational expenses and
Labor
Financial revenue and
Number of active borrowers
The efficiency of the MFIs is impacted by contextual issues like the country in which it is located and the organization type based on ownership i.e. NonGovernmental Organization (NGO) or non-NGO
Gutiérrez-Nieto et al. (2009)
Total Assets
Number of active women borrowers
Operating Cost and
Indicator of benefit to the poorest
Number of employees
Gross loan portfolio and
iv) Financial Revenue
Inefficiencies of MFIs are mainly of technical nature. Thus, to improve the efficiency of the MFIs, there is a need to enhance the managerial skills and improve
technology
Gutiérrez-Nieto et al. (2007)
Number of credit officers and
Interest and fee income
Operating expenses
Gross loan portfolio and
Number of loan accounts outstanding
The efficiency of the schemes is significantly influenced by maturity of schemes and distance from township. In remote areas, the schemes seem to be more
efficient
Qayyum and Ahmad (2006)
Number of Credit officers and
Loans disbursed
Cost per borrower
Nghiem et al. (2006)
Researcher
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IGDR
Parameters used
Input
Output
In East Africa, on an average, the banks and non-bank financial Institutions were relatively more efficient as compared to NGOs and Cooperatives
Segun and Anjugam (2013) (Intermediation
Credit officers (Nos) and
Gross loan portfolio
Approach)
Cost per borrower
Segun and Anjugam (2013)
Employees (Number) and
Outstanding loans
(Production Approach)
Personnel expenses
Inefficiencies of MFIs in Pakistan are mainly of technical nature. There is a need to enhance the managerial skills and improve technology
Kipesha (2012)
Total assets
Gross loan portfolio and
Personnel/staffs and
Financial revenue
Operating revenues
(continued)
As the MFIs grow old, their efficiency level increases but the size does not matter much. Higher outreach is associated with higher efficiency which negates the
general perception of trade-off between outreach and efficiency. Regulated MFIs are less efficient
Ahmad (2011)
Total assets and
Gross loan portfolio and
Number of personnel
Number of active borrowers
MFIs from South India have positive correlation with technical efficiency. This may be due to early development of MFIs in the southern states, conducive
atmosphere, Government support and policy of promoting microfinance as a poverty alleviation tool. The statistical significance of business per staff and log
(total asset) indicate the need for scaling up of MFIs to become efficient
Masood and Ahmad (2010)
Number of personnel and
Gross loan portfolio
Cost per borrower
Bank-MFIs outperform NGO-MFIs under intermediation approach. This may be the result of access of banks to local capital market
Pal (2010)
Number of credit officers and
Three year average outstanding loan portfolio
Cost per borrower
The source of inefficiency is pure technical rather than scale, suggesting that MFIs are either wasting resources or are not producing enough output
Haq et al. (2010)
Total operating expenses and
Gross loan portfolio and
(Intermediation approach)
Number of personnel
Total savings
(Production approach)
Cost per borrower and
Borrowers per staff member and
Cost per saver
Savers per staff member
Researcher
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Malmquist
productivity
index
Table I.
Table I.
Parameters used
Input
Output
Source: Compiled by authors
The complementary use of the DEA approach and the Performance Indicators Analysis provided a tool box for facilitating implementation of benchmarking,
aiming at reducing the trade-off between financial sustainability and poverty outreach of microfinance
Wijesiri et al. (2015)
Total assets
Financial revenue
Number of credit officers and
Number of female borrowers
Cost per borrower
In respect of MFIs in Sri Lanka, age and capital-to-assets ratio are significant determinants of financial efficiency whereas age, type of the institution and returnon-assets are the crucial determinants of social efficiency
MFI industry in MENA countries has exhibited a decline in technological change suggesting that there has been deterioration in the performance of the best
practicing MFIs. They have experienced mainly an increment of pure technical efficiency (improvement in management practices) rather than an improvement in
optimum size. They need to pursue technological progress to meet the dual objectives of reaching more poor and financial sustainability
Piot-Lepetit and Nzongang (2014)
Production and Financial Inputs
Financial and social outputs
(Production approach)
Equity
Loan portfolio
Assets
Other financial revenue and
Personnel cost
Operating revenue
Financial cost
Number of clients Poor and Women
Other operating cost
Piot-Lepetit and Nzongang (2014)
Deposits
Gross loan portfolio,
(Intermediation approach)
Operating Revenues and
Other Financial revenues
MFIs in sub Saharan Africa are inefficient in meeting the goals of either providing microfinance related services to their clients or intermediating funds between
borrowers and depositors
Bassem (2014)
Operating expenses and
Gross loan portfolio
Number of employees
Number of loans
Interest and Revenue
Researcher
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IGDR
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3. Methodology
As per OECD productivity manual (2001), the term total factor productivity (TFP) is
synonymous with multifactor productivity (Schreyer, 2001). The TFP is an outcome of two
major factors namely efficiency and technological change. The present study measures
change in TFP of 21 MFIs in India during the period 2012 to 2016.
We have used Malmquist productivity index which is a multifactor productivity
index. It is a chain index involving comparisons with consecutive periods. The index
measures smaller changes and thus it is meaningful (Coelli et al., 1998). Further, this
index is split into three indices, namely, technology change index, TEC index and scale
efficiency change index. The technology change index reveals the change in productivity
due to advancement of technology of the industry as a whole. TEC index indicates how
well the firm has caught up with the best practices of the industry. Scale efficiency
change index highlights change in efficiency due to scaling up of operations. Thus the
indices provide insights to the management regarding the areas in which inefficiencies
are emerging.
3.1 The Malmquist productivity index and change index
We have followed output-oriented Malmquist productivity change index as suggested by
Fare et al. (1994). It does not require information regarding input-output prices. Moreover,
the index permits division of TFP change into two components, namely, TEC and technical
change (TC). The TEC means catching up by the firm with the best practices of the industry,
and TC is change in the best practice or change in technology. The TEC can be further
divided into pure TEC and scale efficiency change.
The index calculation uses DEA for calculation of various distance functions. The
Malmquist Productivity Index (MPI) measures TFP change between two data points by
calculating the ratio of the distances of each data point relative to a common technology.
Thus MPI at time t with reference technology St (CRS)t is:
Dt xtþ1 ; ytþ1 =Dt xt ; yt
(1)
and at time t þ 1 with reference technology Stþ1 (CRS)tþ1 it is:
Dtþ1 xtþ1 ; ytþ1 =Dtþ1 xt ; yt
(2)
These are explained with the help of Figure 1.
Malmquist productivity change index is defined as geometric mean of two indices at the
times t and t þ 1.
MPI Change index = Geometric mean of ratios of equations (1) and (2):
hh i h tþ1 tþ1 tþ1 tþ1 t t ii1=2
* D
Dt xtþ1 ; ytþ1 =Dt xt ; yt
x ;y
x ;y
=D
This can be written as:
" #1=2
Dt xtþ1 ; ytþ1
Dt ðxt ; yt Þ
Dtþ1 xtþ1 ; ytþ1
Dtþ1 xtþ1 ; ytþ1
* tþ1
*
*
Dt ðxt ; yt Þ
Dt ðxt ; yt Þ
D ðxtþ1 ; ytþ1 Þ
Dtþ1 ðxt ; yt Þ
This is same as:
(3)
Malmquist
productivity
index
IGDR
Y
t+1
C
# (CRS)
F
(CRS)t
$ (VRS)
VRS t+1
F’
* (xt+1.yytt+1)
D
E
C
(VRS)t
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B
B’
*(xt ,yt )
A
O
Figure 1.
Malmquist
productivity index
xt
xt+1
X
Note: # (CRS): constant returns to scale $(VRS): variable
returns to scale
Source: Fare et al. 1994
"
#1=2
# " t Dtþ1 xtþ1 ; ytþ1
D xtþ1 ; ytþ1
Dt ðxt ; yt Þ
* tþ1
*
Dt ðxt ; yt Þ
D ðxtþ1 ; ytþ1 Þ Dtþ1 ðxt ; yt Þ
(4)
From Figure 1, equation (4) can be written as
#1=2
"
ðOFÞ ðOCÞ
ðOD=OFÞ
ðOD=OEÞ ðOA=OBÞ 1=2
ðOD=OFÞ
*
¼
*
*
*
ðOEÞ ðOBÞ
ðOA=OBÞ
ðOD=OFÞ ðOA=OCÞ
ðOA=OBÞ
From Figure 1 it is clear that the ratio (OF/OE) is shift in technology at t þ 1 and the ratio
(OC/OB) is shift in technology at t. The right hand term in the expression above is the
geometric mean of two shifts and thus represents TC.
The ratio (OD/OF) is Dtþ1(xtþ1,ytþ1) which is efficiency at t þ 1 using technology t þ 1
and the ratio (OA/OB) is Dt(xt,yt), i.e. efficiency at t using technology t. Thus the left hand
term in the expression above represents efficiency change, between times t and t þ 1. This
captures whether production is shifting closer to or away from the efficiency frontier over
time. This term captures diffusion of technology.
MPI change ¼ ðEfficiency changeÞ * ðTechnical changeÞ ¼ D Efficiency* D Technology
(5)
Above equation is derived considering CRS technology where Scale efficiency is 1.
Considering VRS technology, efficiency change is further divided as pure TEC and scale
efficiency change as under:
"
#
ðODÞ ðOF0 Þ h tþ1 tþ1 tþ1 i
ðOD=OFÞ5
5 D VRS x ; y
* ½Scale efficiency at t þ 1So also
*
ðOF0 Þ ðOFÞ
"
# t t
ðOAÞ ðOB0 Þ
DT
ðOA=OBÞ5
5
*
* ½Scale efficiency at t:
VRS x :y
ðOB0 Þ ðOBÞ
ðOD=OFÞ DVRS tþ1 xtþ1 ; ytþ1 * Scale efficiency at t þ 1:
¼
ðOA=OBÞ
DVRS t ðxt :yt Þ * Scale efficiency at t:
¼ ðPure technical efficiency changeÞ * ðScale efficiency changeÞ
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Thus D Efficiency ¼
¼ DðPTECÞ * DðSECÞ
Thus Malmquist productivity change index ¼
ðPure technical efficiency changeÞ * ðScale efficiency changeÞ * ðTechnology changeÞ
DðMPIÞ ¼ DðPTEÞ * DðSEÞ * DðTÞ
3.2 Profile of selected microfinance institutions
The selected 21 MFIs are among the top 25 MFIs rated by Credit Rating and Information
Services of India Ltd. (Ratings, 2014). Bandhan Financial Services has been excluded from
the list as it has started functioning as an SFB in August 2015, i.e. during period under
study. The other three MFIs, namely, Ashirwad Microfinance Private Ltd., Cashpor
Microcredit and Swadhar Finserve Pvt. Ltd, are excluded due to non-availability of data.
The sample comprises eight MFIs, namely, Disha, Equitas, ESAF, Janalaxmi, Rashtriya
Gramin Vikas Nidhi (RGVN), Suryodaya, Ujjivan and Utkarsha, which have been granted
“in principle” license by the RBI to operate as SFB in 2015. These MFIs except Janalaxmi
Financial Services have started working as banks since 2017. In addition, three MFIs,
namely, Bharat Financial Inclusion, Satin and Grama Vidiyal, are already listed. Thus these
11 MFIs have been classified as “for-profit” as their profit motive is clear. The other ten
MFIs are not listed and are serving the poor through group or individual lending. These are
classified as “not-for-profit”.
The sample is representative of microfinance industry in India as its market share
(measured by total size of loan portfolio) is estimated to be 80 per cent as on Sept 2013. By
and large, the selected MFIs are owned by private individuals or corporates including
Foreign Institutional Investors (FIIs) or Non Resident Indians (NRIs). Only 5 out of 21,
namely Bharat Financial Inclusion, Grama Vidiyal, RGVN, Satin and Ujjivan are public
limited companies and are listed.
Selected MFIs are dependent on banks and Non Banking Financial Companies (NBFCs)
for funding. In addition, portfolio securitization and Non-Convertible Debentures are the
major sources of funding. It is noteworthy that only one MFI, namely Kshetra, (Shri Kshetra
Dhramasthala Rural Development Trust) is a charitable trust which, in addition to receiving
funding from banks, attracts grants/donations to a small extent.
Only three MFIs in the sample, namely, Bharat Financial Inclusion, Janalaxmi Financial
Services and Ujjivan Financial Services, have national presence whereas all others are
Malmquist
productivity
index
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IGDR
regional in character and are expanding their presence in neighboring states. Average loan
size of the selected MFIs in 2016 varies between Rs 7,645 and Rs 23,773 (Appendix).
3.3 Selection of inputs and outputs
The present study considers inputs as capital and borrowings whereas outputs as
outstanding gross loan portfolio and profit.
The basic objective of MFIs is to increase access for microcredits to the poor and at the
same time ensure sustainability (Gutiérrez-Nieto et al., 2007). The selection of outputs and
inputs is based on these objectives. MFIs are essentially financial intermediaries with
resources i.e. capital and liabilities to grant loans and generate profit in the process. As MFIs
in India are not allowed to accept deposits, they are obtaining short term and long term
borrowings, in addition to capital. Short term borrowings can be withdrawn by the lender,
within a short period and therefore these are not considered as dependable resources for
lending. Thus capital and long term borrowings are the dependable resources against which
MFIs can lend. The authors have taken these two as inputs. So also, outstanding loan
portfolio and the profit generated are taken as outputs. The outputs are indicative of access
to microcredit and sustainability.
3.4 Study period
By 2010, various irregularities had occurred in microfinance industry which caused the
repayment crisis in Andhra Pradesh. The state government had intervened and the Andhra
Pradesh Micro Finance Institution Ordinance 2010 was promulgated, which had put several
restrictions on MFIs. It has made the registration compulsory, put a ceiling on interest rates
and imposed penalties for coercion in recovery. This was a regulatory shock and the crisis
had spread all across microfinance industry in the country.
Thereafter, Micro Finance Network (MFIN) was established as self-regulatory
organization of MFIs which was recognized by RBI. MFIN came out with first code of
conduct for MFIs in 2011. By 2012, microfinance industry had recovered from the crisis.
The change in productivity of MFIs is studied for 2012-2016, taking 2012 as a base year.
During this period, the microfinance industry had grown very fast, roughly at rate of 40 per
cent per annum. This was due to clarity in regulations which proved to be a confidence
building measure. MFI industry attracted funds through equity, loans from banks and
NBFCs and also through securitization of portfolio and non-convertible debentures. The
industry adopted good governance practices, information and communication technology
and had scaled up operations. There was another shock for the microfinance industry
during later part of 2016 when demonetization was announced, impact of which will appear
after 2016 only.
There was no shock or aberration other than regulatory developments. As such the study
period is important from the point of view of growth, sustainability and development of
policy implications for regulating microfinance industry.
4. Findings and discussions
A Malmquist productivity index greater than unity reflects the improvement in productivity
over a period of time and an index less than unity reflects decline in productivity. Likewise
improvement or deterioration in any of the components (Pure Technical Efficiency, Scale
Efficiency, Technology and TFP) of Malmquist index is indicated by the values of the
respective components relative to unity where, value greater than one shows improvement
and that less than one shows deterioration.
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TFP change (Tfpc) is an outcome (product) of three factors namely pure TEC (ptech),
scale efficiency change (sech) and technology change (techch). The technology change is
associated with best practice and is therefore related to industry. Pure technical efficiency
represents catching up by the firm with the best practice. This is done through enhancing
efficiency through improvement in internal processes and systems. Scale efficiency is the
efficiency related to economies of scale. The details of change in efficiency components
during 2012-16 for each MFI are given in Table II.
Table II shows that TFP of MFIs has gone up by 19.9 per cent (mean value) during the
period 2012 to 2016. However efficiency of technology has improved by 12.8 per cent, pure
technical efficiency by 2.5 per cent and scale efficiency by 3.7 per cent.
During the period under study, highest improvement in TFP was registered by MFI
Grama Vidiyal (179 per cent), followed by Arohan (96.6 per cent). At the bottom of the list
are MFIs Kshetra and SMILE, with decline in TFP by 29 per cent and 22.5 per cent
respectively.
Highest improvement in technology was showed by MFI, SV Credit lines (33.4 per cent),
followed by Bharat Financial Inclusion (29.0 per cent). However, MFI SMILE has recorded
maximum deterioration in technology (18.7 per cent) followed by Kshetra (7.8 per cent).
The MFI Grama Vidiyal recorded highest improvement in pure technical efficiency
(116.9 per cent), followed by Satin (46.5 per cent). However, MFI Kshetra showed largest
deterioration in pure technical efficiency of 22.8 per cent followed by Annapurna
(13.4 per cent).
Sr. No
MFI
Ptech
Sech
Effch (Ptech Sech)
Techch
Tfpc (Effch Techch)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Annapurna
Arohan
Bharat Financial Inclusion
BSS
Disha
Equitas
ESAF
Fusion
Grama Vidiyal
Grameen
Janalakshmi
Kshetra
Madura
RGVN
Satin
Smile
Sonata
Suryoday
SV Creditline
Ujjivian
Utkarsh
Mean
0.866
0.970
1.030
0.932
1.164
0.912
1.095
0.884
2.169
1.158
0.963
0.772
0.941
0.891
1.465
1.000
0.999
0.993
1.000
1.000
0.893
1.025
1.157
1.868
1.199
0.996
0.860
1.011
0.994
1.062
1.052
1.028
0.751
0.998
1.032
0.995
0.946
0.954
1.028
1.131
1.000
1.086
0.948
1.037
1.003
1.812
1.235
0.928
1.001
0.922
1.089
0.938
2.281
1.190
0.723
0.770
0.971
0.887
1.387
0.954
1.026
1.123
1.000
1.086
0.847
1.063
1.211
1.085
1.290
1.191
1.020
1.134
1.083
1.097
1.224
1.090
1.215
0.922
1.133
1.002
1.220
0.813
1.193
1.170
1.334
1.089
1.279
1.128
1.215
1.966
1.593
1.106
1.021
1.045
1.179
1.029
2.792
1.298
0.879
0.710
1.100
0.889
1.761
0.775
1.224
1.314
1.334
1.183
1.083
1.199
Notes: (Effch: Efficiency change Ptech: Pure TEC Sech: Scale Efficiency Change. Techch: Technology
Change Tfpc: Total Factor Productivity Change)
Source: Compiled by authors
Malmquist
productivity
index
Table II.
Malmquist index
summary of MFI’s
means
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IGDR
In respect of scale efficiency, MFI Arohan has topped the list with 86.8 per cent
improvement, followed by Bharat Financial Inclusion (19.9 per cent). However, there was
maximum decline in scale efficiency in respect of MFI Janalaxmi (24.9 per cent), followed by
Disha (14 per cent).
The year-wise summary of annual mean of different components of efficiency, for the
period under study, is given in Table III.
During the year 2012-13, technology change (which is an indicator of industry best
practices) is up by 31.3 per cent, scale efficiency is up by 27 per cent and there is 23.7 per cent
improvement in TFP. After the crisis of 2010, microfinance industry started recovering in
this year i.e. 2012-13.
In the following year, 2013-14, there is very high improvement (65.5 per cent) in pure
technical efficiency which is an indicator of “catching up” factor. This indicates that MFIs
largely followed industry best practices in this year. During this year, improvement in TFP
of MFIs under study is very high (74.3 per cent).
In the subsequent year 2014-15, TFP has drastically deteriorated by 78.3 per cent.
Technology change is marginally down by 0.6 per cent and scale efficiency is up by 2.8 per
cent, however “catch up” factor i.e. pure TEC is down by 76.6 per cent.
In 2015-16, technology change is up by 7.1 per cent, however, scale efficiency is down by
13.5 per cent; resulting in marginal improvement of 3.8 per cent in TFP.
The discussion above highlights year-on-year performance under each component
whereas Figure 2 highlights the change in productivity components with reference to unity.
4.1 Identifying factors affecting productivity
The productivity of MFIs was analyzed in the context of the nature of MFIs (profit versus
nonprofit), geographical reach, market share and business model.
To examine whether market share of MFI affects productivity, we have considered
percentage of loan portfolio of each MFI to total loan portfolio of the sample for the years
2012 and 2016. It is observed that market share of “for-profit” MFIs, which was 40.46 per
cent in 2012, has increased to 77.14 per cent in 2016, and correspondingly, market share of
“not-for-profit” MFIs has declined from 59.54 per cent in 2012 to 22.86 per cent in 2016.
Table IV gives firm-wise changes in pure efficiency, scale efficiency, efficiency change,
technology efficiency and TFP. In addition, mean values (geometric mean) of the
component-wise indices for each category of MFIs are given.
It is observed from Table IV that in “for-profit” category, two MFIs namely RGVN and
Janalakshmi are lowest in productivity change and their productivity has declined by 11.15
per cent and 12.1 per cent respectively. RGVN is operating in north eastern states of India
Table III.
Malmquist index
summary of annual
mean
Year
Ptech
Sech
Effch
Techch
Tfpc
2012-13
2013-14
2014-15
2015-16
Mean
0.742
1.660
0.894
1.003
1.025
1.270
0.997
1.025
0.890
1.037
0.942
1.655
0.917
0.893
1.063
1.313
1.053
1.047
1.118
1.128
1.237
1.743
0.960
0.998
1.199
Notes: (Effch: Efficiency change Ptech: Pure TEC Sech: Scale efficiency change, Techch: Technology
change Tfpc: TFP change)
Source: Compiled by authors
80
Malmquist
productivity
index
74.3
Percentage change in components (Year wise)
66
65.5
60
Percentage
40
31.3
27
20
8.3
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–5.8
– 20
2012-13
11.8
2013-14
5.3 4.7
0.3
0
Effch
23.7
Techch
0.3
Pech
– 10.7
2014-15
2.5
2015-16
Sech
Tfpc –2
–4
–11
–10.6
Figure 2.
Year wise percentage
change in the values
of components of
productivity index
–25.8
– 40
Components of productivity index
Source: Compiled by authors
MFI (For-profit)/ Geographical reach
pech
sech
effch
techch
tfpch
2012
2016
Bharat Financial Inclusion (National)
Disha (Regional)
Equitas (Regional)
ESAF (Regional)
Janalakshmi# (National)
RGVN (Regional)
Suryoday (Regional)
Ujjivian (National)
Utkarsh (Regional)
GramaVidiyal (Regional)
Satin# (Regional)
Mean (For-Profit)
1.03
1.164
0.912
1.095
0.963
0.891
0.993
1.000
0.893
2.169
1.465
1.101
1.199
0.86
1.011
0.994
0.751
0.995
1.131
1.086
0.948
1.052
0.946
0.990
1.235
1.001
0.922
1.089
0.723
0.887
1.123
1.086
0.847
2.281
1.387
1.091
1.29
1.02
1.134
1.083
1.215
1.002
1.170
1.089
1.279
1.224
1.270
1.157
1.593
1.021
1.045
1.179
0.879
0.889
1.314
1.183
1.083
2.792
1.761
1.262
14.57
0.93
3.78
1.45
1.62#
2.32
0.10
14.80
0.83
0.05
0.01#
40.46 ($)
14.48
0.66
7.43
5.55
12.56
1.41
3.00
14.61
4.13
3.87
9.43
77.14 ($)
MFI (Not-For-profit )
Annapurna (Regional)
Arohan (Regional)
BSS (Regional)
Fusion (Regional)
Grameen# (Regional)
Kshetra# (Regional)
Madura (Regional)
Smile (Regional)
Sonata (Regional)
SV Creditline (Regional)
Mean (Not-For-Profit)
pech
0.866
0.97
0.932
0.884
1.158
0.772
0.941
1.000
0.999
1.000
0.947
sech
1.157
1.868
0.996
1.062
1.028
0.998
1.032
0.954
1.028
1.000
1.090
effch
1.003
1.812
0.928
0.938
1.190
0.770
0.971
0.954
1.026
1.000
1.033
techch
1.211
1.085
1.191
1.097
1.090
0.922
1.133
0.813
1.193
1.334
1.097
tfpch
1.215
1.966
1.106
1.029
1.298
0.710
1.100
0.775
1.224
1.334
1.133
2012
0.20
0.09
2.82
0.84
1.92#
47.39#
0.80
3.26
0.96
1.26
59.54 ($)
2016
2.67
1.69
1.25
1.45
7.34
1.14
1.60
0.49
2.30
2.93
22.86 ($)
Note: ( % to sample size # More than 5% change in percentage to sample size. ($): total %)
Source: Compiled by authors
Table IV.
Category wise
component indices
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IGDR
where there is huge infrastructure deficit. Hence the cost of operations for RGVN is
comparatively high which has adversely affected its performance.
The MFI Janalakshmi has undertaken very rapid expansion geographically across the
country and in terms of number of clients and loan portfolio. It was operating in 13 states of
India in 2012 and has expanded in eight more states during the period 2012-16. In all, it is
operating in 21 states of the country and is national in character. Its customer base increased
from 1.2 million in 2012 to 4.6 million in 2016 and its loan portfolio has increased from Rs
23,830m in 2012 to Rs 115,260m in 2016. The MFI has developed large infrastructure with
9,669 branches and 87,402 employees. It has developed and implemented customer centric
business model and has invested in technology. In the process, it has achieved very high
(21.5 per cent) improvement in technology but has lost on all other components of
productivity. The rapid expansion before consolidating had adversely impacted its
productivity. This could have been avoided if the expansion had been gradual. Table IV
reveals that “for-profit” MFIs are performing better in terms of efficiency change,
technology change and TFP change as shown in Figure 3.
In “not-for-profit” category, there are two MFIs, namely, Kshetra and SMILE, with
deterioration in productivity. Keshtra is a temple trust operating not only on commercial
principles but also has undertaken several social activities such as health care, women
empowerment and education. In addition to financing the poor and small farmers the trust is
engaged in agriculture extension, development of self-help groups and employment
generation programs.
SMILE has very low profitability with average earning per share of Rs 1.94 during 2012-16
for book value per share of Rs 53.85. Its operations are mostly concentrated in Tamil Nadu,
though it has some presence in Puducherry and in few districts of Kerala. The average loan size
(2016) of SMILE microfinance is 40 per cent below industry level. It is focusing on financing the
poorer amongst the poor and its geographical base is narrow. As their clientele is poorer section
of the poor, spreading geographically and leveraging technology (as done by Satin) would have
increased their client base and hence improved their productivity.
Four MFIs namely Janalakshmi (þ10.94 per cent), Satin (þ9.42 per cent), Grameen
(þ5.42 per cent) and Kshetra (46.24 per cent) have shown significant (more than 5 per cent)
changes in relative sample share. (Figures in bracket show percentage change over from
2012 to 2016). Both MFIs Janalakshmi and Satin have undergone significant change in size.
However the productivity of former has deteriorated whereas that of latter has shown
significant improvement (Table IV). This is mainly because MFI Janalakshmi has expanded
30.00
Change in efficiency componets 2012-16
(For Profit and Not For Profit MFIs)
26.20
Percentage
25.00
20.00
15.70
15.00
10.00
5.00
Figure 3.
Category wise change
in components of
efficiency 2012-16
13.30
Not for Profit
9.70
9.10
3.30
0.00
effch
Source: Compiled by authors
techch
For Profit
tfpch
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with large infrastructure of 9669 branches and 87402 employees across the country, whereas
MFI Satin was operating with 364 branches and 3419 employees in 2016. It has expanded its
activities in 33,631 villages with the help of technology and group lending.
The MFI Grameen has migrated to Core Banking Solution and has started seven
Regional Processing Centers to improve the efficiency of operations. It was awarded
Microfinance India award 2015 for good governance, transparency, innovations in process,
product and technology, good human resource management and integration of social
performance and financial performance. This explains its 15.8 per cent improvement in pure
efficiency, 9 per cent improvement in technical efficiency and 29.8 per cent change in TFP
being highest in, “not-for-profit” category.
The MFI Kshetra has significantly reduced its lending operations and focused on social
activities which have resulted in deterioration of its efficiency parameters.
The MFIs Grama Vidiyal has shown highest improvement in productivity (179 per cent),
in “for-profit” category. Its loan portfolio has grown from Rs 22.02m in 2012 to Rs 13,426.9m
in 2016, with recovery rate of 99.97 per cent and membership of 11.17 million. The MFI has
managed to keep its infrastructure lean with the help of information technology and is
operating through 306 branches. It has been given credit rating A3þ by ICRA in 2015-16.
Moreover its industry compliance index score by MFIN is 98.25 per cent. This score
incorporates parameters for measuring, managing and integrating responsible business
practices. This explains its high improvement in pure efficiency (116.9 per cent) and
technology (22.4 per cent).
Arohan has shown highest improvement in productivity (96.6 per cent) in “not-for-profit”
category. The MFI has rapidly scaled up its operations by aggressively promoting its
products Saral, Bazar Plus and Pragati. It has started working as a banking correspondent
for IndusInd bank in Assam. Its loan portfolio has grown to Rs5660 million in 2016 from
Rs53 million in 2012. This is largely reflected in scale efficiency change (86.8 per cent).
Thus it is observed that there are several factors impacting productivity. Moreover it
cannot be conclusively inferred that increase in the market share of an MFI will impact its
productivity in one way or the other. It is the business model that seems to have a significant
impact.
4.2 Mission drift and sustainability
Microfinance industry is facing a major challenge of financial viability. There is a concern
amongst the stakeholders that in pursuit of sustainability, it is drifting away from its
mission of serving the poor and MFIs are moving towards the “better off” section amongst
them.
We evaluate the sustainability of microfinance industry in India from the point of view of
productivity as well as mission drift and examine the trade-off between their conflicting
objectives. We use the Malmquist productivity index as a measure of sustainability because
it considers profitability and outreach. To examine mission drift, we use the parameters,
average loan size, market (Rural/Urban), focus (favorable bias towards women), lending
methodology (group or individual) as identified by Mersland and Strøm (2010).
Table V illustrates the parameters that indicate a mission drift or mission focus.
The extent of focus on mission for each MFI is assessed by comparison with these two
extreme positions and is further analyzed in the context of productivity of the respective
MFI.
Table IV highlights that the market share of MFIs “for-profit” has increased from 40.46
per cent in 2012 to 77.14 per cent in 2016, indicating that there is a shift in the objective, i.e.
from serving the “poorest of the poor” to earning a profit for sustainability. The same table
Malmquist
productivity
index
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IGDR
also indicates that the market share of “not-for-profit” MFIs has reduced from 59.54 per cent
in 2012 to 22.86 per cent in 2016, also indicating the mission drift.
It is also observed that during the period under study, the average loan size has gone up
by 120 per cent for the industry (Micrometer May 2016). Also, the average loan size for the
sample has gone up by 92 per cent (Appendix). This shows that Microfinance Industry in
India is shifting its client base from poorest section amongst the poor towards those, who
are less poor. Most of the MFIs in the sample are having focus on financing women and are
following group lending model; but there is a discernible shift from rural to semi urban and
urban markets. This clearly indicates that by and large, Microfinance Industry in India is
undergoing a mission drift.
As per Appendix, the sample of 21 MFIs is classified on the basis of their average loan
size vis- a-vis the industry average for the year 2016 as shown in Table VI.
There are two MFIs namely Kshetra and SMILE which have controlled mission drift to a
large extent but have heavily deteriorated in productivity. The average loan size (2016) of
Shri Kshetra Dharamasthala Rural Development Project, (SKDRDP/Kshetra) is 38 per cent
below corresponding industry level. It has focused on rural financing to both men and
women though group and individual lending. However, its productivity has deteriorated by
29 per cent during 2012-16. SKDRDP is a temple trust and it has undertaken development of
Self Help Groups on large scale, which is a non-commercial activity. So also, the average
loan size (2016) of SMILE microfinance is 40 per cent below industry level. It has retained its
focus on women through group lending, though it is financing both rural and urban poor.
However, its productivity has declined during study period by 22.5 per cent.
Six MFIs in the sample are able to control mission drift significantly and at the same time
have improved productivity during the period under study. Their average loan size (2016) is
Sr. No.
Mission parameters
1
Ratio of average loan size of MFI to average loan
size of industry
Market coverage
Gender
2
3
Indication of
mission drift
Indication of
mission focus
High ratio
Low ratio
Urban
No specific
focus on
women
Individual
Rural
Women focus
Table V.
Parameters
4
Lending method
Group
indicating mission
drift or mission focus Source: Classification by authors based on indicators identified by Mersland and Strøm (2010)
No. of MFIs
2
6
Table VI.
2
Classification of
6
sample MFIs as per
5
average loan size vis- Total-21
a-vis industry level
(2016)
Average loan size vis-a-vis
industry level
Productivity
40-30% below
Deteriorated by 29-22.5%
30-10% below
Improved productivity
10-5% below
Improved productivity
65% of industry level. (At par)
Significant improvement in productivity
Significant improvement in productivity
5-43% above
(Actual loan size of sample varies from 40% below to 43% above industry level)
Source: Constructed by authors
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at least 10 per cent below industry average. These are Annapurna (11 per cent, þ21.5 per
cent), Arohan (26 per cent, þ96.6 per cent), Equitas (28 per cent, þ4.5 per cent), Fusion
(18 per cent, þ2.9 per cent,), Madura (19 per cent, þ10 per cent) and Utkarsha (15 per
cent, þ8.3 per cent) (The figures in the bracket refer to sample size with reference to industry
average in 2016 and productivity change during 2012-16). Out of these, only Utkarsha is
financing through group lending and others are financing individuals and through groups.
So also, Arohan and Equitas are financing both men and women whereas others are
financing largely women borrowers. As such, for these MFIs, there is no indication of tradeoff between their objectives of sustainability and the mission of serving the poor. However
trade-off is discernible in respect of all other MFIs in the sample as discussed below in detail.
The MFIs Disha and Grama Vidiyal were marginally below industry level in sample size
by 6 per cent and 8 per cent respectively. The productivity of Disha increased marginally by
2.1 per cent whereas Grama Vidiyal has shown highest growth in productivity (179.2 per
cent) during the period under study. Thus it can be concluded that in case of majority of
MFIs, focus on mission corresponds to lower productivity and vice versa. This shows
existence of tradeoff between profitability and mission focus in microfinance industry in
India.
Out of ten MFIs discussed above, three of them, namely, Disha, Equitas and Utkarsha,
have been granted “in principle” license by RBI for working as SFB. Out of these prospective
SFBs, Disha has shown marginal increase in productivity and marginal reduction in sample
size as compared to the industry average. The other two, Equitas and Utkarsha have shown
significant restraint on mission drift with simultaneous improvement in productivity.
The sample under study contains six MFIs namely Bharat Financial Inclusion (59 per
cent), Satin (76 per cent), RGVN (11.1 per cent), Suryodaya (31 per cent), SV Creditline (33.4
per cent), and Ujjivan (18 per cent) having average loan size at par with industry average (i.e.
within range of –5 per cent to þ5 per cent) (The figures in bracket represent percentage
change in productivity). These MFIs have achieved significant improvement in
productivity, with the exception of RGVN. It has focused on the North Eastern Region of the
country which has large infrastructure deficit. This is reflected in decline in its productivity.
Out of these, three MFIs namely, RGVN, Suryodaya and Ujjivan have been granted “in
principle” license by RBI for working as SFB.
The remaining five MFIs namely BSS (þ29 per cent, þ10.6 per cent), ESAF (20 per cent,
þ17.9 per cent), Grameen (27 per cent, þ29.8 per cent), Janalakshmi (43 per cent, 12.1 per
cent) and Sonata (þ6 per cent, þ22.4 per cent) have average loan size above industry
average (The figures in the bracket refer to sample size with reference to industry average in
2016 and productivity change during 2012-16). All these MFIs have shown high rise in
productivity (with the exception of Janalakshmi) and also high mission drift as measured by
large sample size compared to industry average. However ESAF and Grameen have been
largely having rural market with a focus on women borrowers financed through group
lending.
The MFI Janalakshmi is having largest mission drift indicated by highest average loan
size, and urban clientele. There is no indication of gender bias favoring women. They
finance both individuals and groups. It is the second largest MFI in the sample measured by
gross loan portfolio and it has scaled up fast during 2015-16 but has lost on productivity by
12.1 per cent during 2012-16. It has been granted “in principle” license by RBI for working as
SFB along with ESAF.
The Reserve Bank of India has granted “in principle” license to ten MFIs in 2015 for
working as SFBs, out of which eight are included in the sample. Out of these two, namely,
Malmquist
productivity
index
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IGDR
Ujjiavan and Janalakshmi, are national in character. Others are regional in character focused
in a particular state and are expanding in adjoining states (Table IV).
4.3 Regulating mission drift
As SFBs, these MFIs will be required to compete with the other players namely
Regional Rural Banks, Co-operative banks and Commercial banks in public and private
sector, in their respective areas. The competitors are lending in priority sector at much
lower rate and have taken up group lending, leveraging technology. Thus SFBs will be
required to lend at a much lower rate as compared to present rate of 22 per cent to 26 per
cent and will have to operate on much lower margins, as compared to present margin of
10 per cent.
In April 2015, RBI has prescribed a target of 75 per cent of loan portfolio for priority
sector advances for SFBs. Moreover, for NBFC-MFIs, the eligible annual household income
is increased from Rs 60,000 to Rs100,000 for semi urban and from Rs 100,000 to Rs 160,000
for urban households. So also, the limit for total indebtedness for individuals is increased
from Rs 50,000 to Rs 100,000. There is also a possibility of SFBs focusing on housing loans
in urban areas which are categorized as priority sector lending.
In view of the strong mission drift observed in microfinance industry in India, the
authors are of the opinion that present regulations are inadequate. It is necessary to develop
robust regulatory framework for MFIs and SFBs, with the objective of maintaining their
sustainability and focus on mission. In the absence of strict compliance to such regulations
there is every possibility that SFBs will be losing their present character and will turn out to
be replicas of their competitors.
4.3.1 Assessment metrics. The success of any initiative is dependent on clarity of mission,
establishment of well thought-out systems, processes and periodical assessment to ensure
that a desired level of quality in service or product has been achieved and maintained. To
monitor this, in addition to supervision of the process of service-delivery at every stage, an
assessment metrics is required. The metrics constructed by the authors, will not only
measure performance with respect to each of the indicators that are critical to the success of
the initiative, but will also grade MFIs in the context of acceptable performance. We suggest
that the performance of MFIs and SFBs be measured with respect to assessment indicators
and these may be further graded. The grade so attained will be the yardstick to either reward
or to take corrective measures for erring organizations. Strict monitoring of performance and
compliance will ensure success of the policy to promote SFBs. Towards this end, the authors
have constructed an assessment and grading metrics (Tables VII and VIII) to periodically
evaluate the performance of SFBs, grade their performance and also for using it for
evaluating the eligibility of MFIs for granting license as SFBs.
The evaluation metrics is constructed with an objective of striking a balance
between conflicting objectives of sustainability and financing the poor (measured
through average loan size vis-a-vis industry loan size). Therefore Tfpc above 1.4 is
considered as undesirable as it will imply excessive emphasis on sustainability at the
cost of mission focus. Hence maximum 20 marks are prescribed for Tfpc between 1.3
and 1.4 or above.
So also, sustainability is of paramount importance for MFIs and hence its deterioration
below 20 per cent is discouraged by assigning -20 marks for Tfpc score of 0.8 and below,
thereby indicating that excessive focus on mission parameters at the cost of sustainability is
also not desirable.
Suggested grading is given in Table VIII.
20
15
10
5
20
Below 20%
20% to-5%
5% to þ5%
þ5% to þ20%
Above 20%
20
15
10
5
0
Criterion-2
Average loan size vis-a-vis industry
Max.
Points
Avg loan size as % of industry
(20)
Note: In all parameter ranges upper limit is included
Source: Constructed by authors
1.4 or above to 1.3
1.3 to 1.15
1.15 to 1.0
1.0 to 0.8
0.8 and below
Sustainability parameter
Criterion-1
Tfpc
Max.
Points
(20)
Tfpc range
Above 70%
70% to 60%
60% to 50%
50% to 40%
40% and below
20
15
10
5
0
Above 70%
70% to 60%
60% to 50%
50% to 40%
40% and below
20
15
10
5
0
Mission parameters
Criterion-3
Criterion-4
Market reach
Gender
Max.
Maxi.
Points
Points
Rural
(20)
Financing women
(20)
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Above 70%
70% to 60%
60% to 50%
50% to 40%
40% and below
20
15
10
5
0
Criterion-5
Group lending
Max.
Financing
Points
groups
(20)
Malmquist
productivity
index
Table VII.
Evaluation metrics
IGDR
It is further suggested that license to work as SFB should not be given if grade for MFI is
below Bþ and the cutoff grade/score above Bþ may be decided depending on the
competition. Suitable incentive scheme may be introduced by MFIs with grades Bþ and
above and for those MFIs that are not applying for a license to function as SFBs.
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5. Conclusion and policy implications
In India, MFIs are playing an important role in economic development by providing
microcredit to the poor. MFIs have the dual objectives of achieving profitability and serving
the poorest of poor. Very few studies have been undertaken to measure productivity of MFIs
in India and the trade-off between sustainability and the objective of financing the poor. The
present study fills this gap and its contributions have several policy implications for
stakeholders for large-scale promotion of microfinance program in India.
We have measured productivity of 21 MFIs (which constitute 80 per cent gross loan
portfolio of microfinance industry as on September 2013) using Malmquist Productivity
Index, which is a measure of sustainability. The productivity of MFIs was analyzed in the
context of nature of MFIs (profit verses nonprofit), geographical spread, market share and
business model.
We have analyzed the tradeoff between sustainability and the objective of financing the
poor i.e. mission. To evaluate the focus on mission we have used 4 parameters namely,
average loan size, market (rural/semi urban, urban), gender (focus on women) and lending
methodology (group or individual). Lower the average loan size, more is considered the
focus on financing the poorer section of the population.
In case of majority of MFIs the average loan size is found to be significantly higher than
the industry average. Moreover, there is evidence of increasing shift towards financing in
semi urban and urban areas. This is indicative of mission drift in the industry.
Using the above mentioned parameters, the authors have developed an assessment and
grading metrics that can be used to assess the performance of MFIs and SFBs on the criteria
of sustainability and mission focus.
The same metrics can also be used to develop a robust framework for regulation of SFBs
in addition to the existing tools for assessment such as capital adequacy, asset quality,
management capability, earnings, liquidity and sensitivity to various risk factors
(CAMELS).
The Reserve Bank of India or Micro Finance Institutions Network can also use it to rate
MFIs. The rating will be useful to lenders, donors and borrowers. It will also be useful for
developing incentive schemes such as soft loans or subsidies for developing infrastructure.
The Reserve Bank of India can use it as one of the tools for granting permission to MFIs for
accepting deposits from public under section 45 of RBI Act.
Table VIII.
Suggested grading
Total score
Grade
Above 80
80 to 71
70 to 61
60 to 51
50 to 41
40 and below
Aþ
A
Bþ
B
Cþ
C
Source: constructed by authors
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The study will help benchmarking of MFIs in India. It will help organizations to compare
their performance with best practices in the industry and to identify the areas for
improvement. It can also be used for shortlisting MFIs as prospective SFBs. This
measurement can be adopted in other countries too.
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Corresponding author
Dilip Ambarkhane can be contacted at: dilipambarkhane@ssbf.edu.in
Malmquist
productivity
index
Table AI.
Details of parameters
for evaluating
sustainability and
mission drift
0.879
0.710
1.100
0.889
Janalakshmi
Kshetra
Madura
RGVN
15,873
9,988
17,645
15,906
15,969
15,739
14,180
15,751
16,601
23,773
10,365#
13,426
16,049
At par
40% below
6% above
At par
At par
At par
15% below
43% above
38% below
19% bellow
At par
29% above
6% below
28% below
20%above
18% below
8% below
27% above
At par
26% below
11% below
Avg. loan size
vis-a-vis industry
Rural around
80%
R/U Both
R/U Both
R/U Both
85% Rural
Rural
R/U Both
R-73%
U-27%
Urban
Rural
R/U Both
Mostly Rural
and
Semi-Urban
(SU)
R-SU
R/U Both
R/U Both
R/U Both
R/U Both
R/SU/U
R/SU/U
R/U Both
Rural
Largely women
Women
Women
Women
Women
Majority women
Women
No indication
No indication
Largely women
Financing men and
women both
100% women
groups
Women
Women
No indication
99% Women
Women focus
100% women
Primarily women
No indication
Observed
Mission parameters
Market
Gender bias
(R/U/Both)
towards women.
Notes: ( Granted license to work as an SFB, Within range of 5% to þ5%., # Estimated) Adopted from Mersland and Strøm (2010)
Sources: MFIN-Micrometer May 2016, Annual Reports of MFIs
1.761
0.775
1.224
1.314
1.334
1.183
1.083
92% increase
120% increase
21,488
15,657
11,961
19,966
13,682
15,212
21,054
1.106
1.021
1.045
1.179
1.029
2.792
1.298
Satin
Smile
Sonata
Suryoday
SV Creditline
Ujjivian
Utkarsh
Average(Sample)
Industry average
16,557
1.593
Bharat Financial
Inclusion
BSS
Disha
Equitas
ESAF
Fusion
Grama Vidiyal
Grameen
12,350
1.966
Arohan
14,781
1.215
Tfpc (2012-2016)
Avg. loan size
(2016) in Rs
Annapurna
MFI/Parameters
Sustainability
parameter
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Group lending
Group lending
Group lending
Group lending
Group lending
Group/Individual
Group lending
Both
Both
Both
Largely group
lending
Both
Both
Both
JLG Women groups
Both
100% group lending
100% group lending
Both.50% through
women SHGs
Group/Individual.
Both
100% group lending
Lending methodology
group/individual
IGDR
Appendix