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LEVERAGING MICROFINANCE AS AN IMPROVISED TOOL FOR UP-SCALING ACCESSIBILITY TO FINANCIAL PRODUCTS & SERVICES IN THE HINTERLAND OF INDIA Dr. Prasun Kumar Das, School of Rural Management, KIIT University, India

ABSTRACT With the economic resurgence of rural India, all the financial institutions be it a Commercial Bank, NBFC, MFI or Insurance company, rushing towards rural sector to exploit newer economic opportunities with their own products and services. Now the ‘opportunities at the bottom of the pyramid (BOP)’ has shifted the focus of the financial sector towards microfinance as an improvised instrument (products & services) to propel higher business growth coupled with generation of handsome revenues. India now occupies a significant place and niche in the global microfinance through promotion of Self Help Groups (SHGs) and the homegrown SHGBank linkage model. The Indian model offers a greater promise and potential to address poverty and livelihood as it focused on building social capital through providing access to financial products and services through linkage with the mainstream. Impact assessment being rather limited so far, it is hard to measure and quantify the effect of this Indian version of microfinance delivered by the formal financial institutions on improvement of livelihood but undoubtedly a lot need to be accomplished in terms of outreach and innovation to make a serious dent on the overall economic growth of the rural sector. However, the logic and rationale of SHG based microfinance have been established firmly enough that microfinance has effectively graduated from an experiment for eradicating poverty to a widely accepted paradigm of financial access for the teeming million rural populations of India through deepening of delivery channels.

KEY WORDS: Microfinance, SHG-Bank linkage, Livelihood, Outreach, Delivery channels, Accessibility to finance.

"Microfinance in India is approaching a historic 'tipping point' that could lead to a massive poverty reduction in the next five to ten years." - Grameen Foundation US in 2005.

"Microfinance is not a charity. It is a way to extend the same rights and services to low-income households that are available to everyone else. It is recognition that poor people are the solution, not the problem." - Kofi Annan, Secretary General, United Nations in 2004

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INTRODUCTION In India, we have been experimenting with various alternatives to reach the banking services, primarily credit, in rural areas through several initiatives since last forty years to bring the equality. Early initiatives in this regard were taken by building an institutional framework beginning with the focus on the cooperative credit institutions followed by the nationalization of major domestic banks and later the creation of the Regional Rural Banks (RRBs).

Simultaneously, several measures including establishment of the Lead Bank Scheme, directed lending for the Priority Sectors, banking sector's linkage with the Government sponsored programmes targeted at the poor, Differential Rate of Interest Scheme, the Service Area Approach, the SHG-Bank linkage programme and introduction of the Kisan (Farmer) Credit Card (KCC) were undertaken.

India has one of most extensive banking infrastructures in the world. However, millions of people in India do not have access to basic banking services like savings and credit. Various new and innovative banking channels including the information & communication technologies have been developed and implemented to bring maximum number of people under the formal banking system through the use of the vast network of rural and semi urban bank branches. Despite this endeavor, the fact remains that the banking services are not made available to the majority of the population residing in the rural and semi-urban areas and one glaring example of the same is that only 27% of total farm households are indebted to formal sources (of which one-third also borrow from informal sources). There may be host of reasons for this exclusion but both public and private commercial banks in India perceived rural banking as a high-risk, high-cost business i.e. a business with high transaction costs and high levels of uncertainty. Rural borrowers, on their part, felt that banking procedures were cumbersome and that banks were not very willing to give them credit.

While informal financial services have always been an integral part of the traditional economy of India, even semi-formal and formal financial services through agricultural cooperatives and nonbanking finance companies are within physical reach (less than 5 km) of perhaps 99 per cent of the population of the country. The development of the semi formal financial sector does not gained momentum until the last half of 1980s. With the introduction of the SHG-Bank linkage programme (SBLP) launched by National Bank for Agriculture and Rural Development (NABARD) on pilot basis during 1992 pointed out the huge potentialities of this sector in the rural India.

Formal financial services are, in theory, available to low income families mainly through 33,553 rural and semi-urban branches of commercial banks, 13,932 rural and semi-urban branches of Regional Rural Banks, 1,09,000 primary cooperatives, 1,000 NGO-MFIs and around 20 MFIs registered as companies (Section 25 of Indian Companies Act, 1956) and nearly three million SHGs. Even more numerous are the myriad of informal agents constituting a great range of financial service providers across the country. The rural branches of the commercial banks and the Regional Rural Banks (RRBs), in particular, were established specifically in order to meet the credit requirements of the poor – small and marginal farmers, landless workers, artisans and small entrepreneurs and should, therefore, have emerged as a major source of microfinance. A

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total of 140,000 institutional outlets serving the rural sector, which ensure the availability of the financial and banking requirement.

In the early 1980s, the regulators of the financial sector including the Govt. of India realized the need for microfinance to provide the rural poor with savings and microcredit services. With the passage of time, there were more refinement in the objectives and vision, the RBI ensured that the loans available through microcredit schemes launched by various commercial banks were more accessible to the poor people as compared to normal bank loans. It also compared favorably with non-institutional moneylenders in terms of cost and quick availability.

This paper reviews the available channels of formal financial system for delivery of microfinance and different business models thereof. An attempt was made to find out the potentiality of micro banking in the rural market and the present scale of delivery by the different players of the formal financial system with their share holding pattern. An effort was also made to list out the enabling factors and their impact to increase accessibility and also the effective measures expected from the regulators for smooth sailing and stabilizing the system of micro banking in India.

SECTION-I: MICROFINANCE IN INDIA Defining microfinance During 1990s, microfinance was by and large understood as an activity that was adopting business principles but carried on by an “alternative sector” other than the Government & commercial sector, and done exclusively or predominantly with the “poor”. While it typically meant lending small amounts to smooth consumption, a similar loan provided by a rural branch of commercial bank or RRBs for instance was not necessarily considered microfinance. MFIs & SHGs were therefore, mainly acknowledged as microfinance providers. This ambiguity of defining the microfinance has been a stumbling block for years which was now been sorted out with the intervention of the Reserve Bank of India. According to the latest guidelines issued by the Reserve Bank of India, an amount of loan not exceeding INR.50000.00 (US $ 1250.00) to an individual or a micro-entrepreneur would qualify as microfinance.

Demand side of microfinance Traditionally, the microfinance clientele were self-employed micro-entrepreneurs for whom credit served the purpose of consumption, smoothening, investment in productive assets or working capital for income generation activities. It is estimated that in India there exist approximately 75 million poor households, out of which 60 million are rural and semi-urban and 15 million urban households. One estimate assumes that the total annual requirement of credit for the rural and semi-urban poor families would be at least US$ 5.10 billion on the basis of a minimum need of US$.85.00 per family. Another estimate for requirement of credit (excluding housing) is 26.25 billion US$ assuming that annual average credit usage are US$ 150.00 per rural household, and US$ 200.00 for poor urban household. An additional US$ 4.20 billion is estimated to be required for housing per year. Apart from micro-credit, they require savings and insurance as well, which together is a real big picture.

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Supply side of microfinance The commercial banks in India since 1970s was in the branch expansion mode and with certain restrictions imposed by the Reserve Bank of India, they were in compulsion to open rural and semi-urban network of branches to serve the rural and semi-urban clientele either in the form of farm credit or non farm credit. Apart from the banking sector since 1990s, the financial sector has witnessed changing pattern in rural finance space with the introduction of SHGs and the aggressive entry of NBFCs & MFIs at a latter stage. The key players along with the purpose and the products of the supply side providing microfinance are appended in Table-1.

Table1. Supply side of Microfinance in India

Key players

Example

Purpose

Banks

All commercial banks both All purposes under public & private sector

Meso-level NBFCs

Fullerton financial

India,

Products 1. SHG –Bank linkage 2.MFI- Bank linkage

Citi Consumer finance, Customized products Asset finance, Productive finance

MFIs (NBFCs BASIX, SKS Fin, Bandhan & NGOs)

Small income Customized products generating activities, Consumption

Co-operative Societies

PACS*, Agri. Marketing Small income Need based products org. generating activities, Consumption

Informal sources

Money lenders, creditors

trade Consumption

*PACS- Primary Agriculture Credit Society (Source: Author, 2009)

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No products as such

Apart from the above key players in the microfinance space, Apex financial Institutions like NABARD, Small Industries Development Bank of India (SIDBI), housing organizations like National Housing Bank (NHB), Housing & Urban development Corporation (HUDCO) etc., are also encouraging the Banks, MFIs, NBFCs, SHG Federation and Housing Finance Companies (HFCs) in the private sector to promote microfinance through financial, technical and capacity building inputs.

Demand Supply Gap All said & done the fact remains that the micro-entrepreneurs (the self-employed poor) have little access to the formal financial system in developing economies like India. A study conducted in Uttar Pradesh, the biggest state of India (Das, 2009) shows that each commercial bank branch is covering a population of 26,013 with coverage of 13,634 adult populations which is the classic example of existing gap in the system. It was also estimated that at best, formal financial institutions discussed above could reach the top 35 per cent of the economically active population, which leaves the bottom 65 per cent without access to formal financial services.

Microfinance institutions (MFIs) as semi-formal delivery channel have grown rapidly to meet this demand. However, their outreach remains very small compared with the demand and it has been estimated that less than 5 per cent of those poor households had access to microfinance services. The new generation MFIs armed with the technological backing is growing at a faster rate due to the space left by the commercial banks that have the inherent advantage to serve the rural people and bridge the huge gap. As per the latest available information from the discussion with the bankers, the public sector banks are now geared to take up the challenges posed by the NBFCs & MFIs with restructuring their products & services especially for the rural clientele.

The SHG-Bank linkage, the flagship programme of the commercial banks has now been considered as a business proposition and expected to upscale the operation. In spite of the impressive figure, the supply side of micro finance in India is still recently grossly inadequate to fill the gap between de3mand and supply but it holds the promise to act as a great opportunity for the financial sector of the economy as a whole and commercial banks in particular.

Business models of microfinance Commercial Banks are playing a major role in providing microfinance through their unique business model, which has emerged as the flagship model for providing microfinance services in the country. It is a proven tool of extending to the un-banked rural clientele access to formal financial services. The whole story of the SHG- Bank linkage programme (SBLP) can be easily read from the summary Table 2 given below:

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Table 2. SHG Bank linkage programme in India (Highlights as on 31.03.2008)

Sl No

Particulars

1.

2.

3.

No of SHG linked per cent of women groups No. of participating Banks i) Commercial Banks ii) Regional Rural Banks iii) Co-operative Banks No. of States/UT covered No. of Districts Covered Outstanding Bank loan (US$) No. of Households assisted (million) Av. Loan per SHG – New (US$) - Repeat (US$) Av. Loan per family – New (US$) - Repeat (US$) Model –wise linkage in percentage (cumulative) i) SHG formed & financed by Banks ii) SHG formed by other agencies but directly financed by Banks iii) SHG formed by Banks using financial intermediaries

4.

5.

6.

7.

8.

9.

10.

Cumulative as on 31.03.2008 3477965 90 per cent 498 50 96 352 31 587 2.58 billion 58.3 925.00 1640.00 66.00 118.00 17 per cent 75 per cent 8 per cent

(Source: NABARD, 2007-08) During the year (2007-08) 7,39,875 new SHGs were credit linked with banks and bank loan of US$ 880.74 million disbursed, taking the cumulative number of SHGs credit linked to 34,77,965 as on 31 March 2008. In addition 1,86,883 existing SHGs were provided repeat loan of US$ 351.16 million. As on 31 March 2007, 4.16 million SHGs maintained savings and had savings of US$ 731.80 million outstanding with the banking sector. The total loan outstanding as on 31.03.2007 stood at US$ 2.58 billion. The programme has covered more than 58 million poor households, making it the largest Micro Finance programme in the world (NABARD, 2007-08).

Encouraged by the success of the above business model, the commercial banks/Reserve Bank of India/NABARD promoted the linkage of Micro- Finance Institutions (MFIs) with the banking sector. The MFI–bank linkage model too has assumed importance because of credit support extended by banks for on lending to clients by MFIs. As per the Annual Report of NABARD, 2007-08, the commercial banks disbursed a loan of US $ 239.90 million to 334 MFIs as on 31.03.2008 and the loan outstanding stood at US $ 330.10 million to 550 MFIs.

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SECTION-II: RURAL MARKET & POTENTIALITY OF MICRO BANKING Market of microfinance The demand for microfinance services – savings, credit and insurance – is apparently insatiable in India. In that sense, India is perhaps the largest emerging market for microfinance services in the world. This can be proved from the following facts.

The National Council for Applied Economic Research (NCAER), India reported (2007) that the low-income population in rural India has come down from around 65 per cent during the early 1990s to 25 per cent during the recent survey.

Meanwhile, middle-income households in rural India have gone up from 33 per cent to 70 per cent. Almost 50 million households have transcended from low income to the middle income.

As per the estimates, there is an increase in the savings by rural India to the extent of 31 per cent.

The urban-rural remittances have increased largely as the migrant population began sending their earnings to the villages.

This reflected in a sudden spurt in demand from India’s increasingly assertive and affluent hinterland. Rural India now accounts for around 53 per cent fast moving consumer goods market. Even more telling, close to 59 per cent of demand for consumer durables emanates from rural India.

These are not just statistics, rather these culminates into the potentiality and demand for micro banking in the hinterland of India and the microfinance has the potential to be the most suitable tool to tap this emerging market.

The potential and captive market of microfinance in India is really a very important area of research. In this paper, we have tried to estimate the potential market which starts with the number below poverty line (BPL) population in India and as per the most conservative estimates, the average number of BPL population will be around 57.90 to 7.73 million. To determine the amount of on lending funds requirement for these BPL clientele, on annual average loan size of US $ 100.00 to US $ 250 has been considered (Average loan size is taken from historical data of last 5 years of the MFIs). Applying these loan amounts to the BPL population identified above, the annual credit demand could go to US $ 5790.00 million to US $ 1447.50 million (Table 3).

Apart from the above estimate, if we calculate the SHG-Bank linkage programme (SBLP) of the commercial banks, the market of microfinance will be even bigger and attractive as a very lucrative business proposition.

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Table 3. Annual microfinance demand (using National Poverty Line Statistics) Av. Loan Size (Estimated) (in US $)

Potential clients (BPL) (in million)

Financial requirements (in million US $)

Financial requirements ( in INR billion)*

100 125 150 175 200 225 250

57.90 57.90 57.90 57.90 57.90 57.90 57.90

5790.00 7237.50 8685.00 10132.50 11580.00 13027.50 14475.00

231.60 289.50 347.40 405.30 463.20 521.10 579.00

* Assumed US $ 1 = INR 48

Readiness of the microfinance service providers To tap such a big market for microfinance, the commercial banks are revamping their already existing rural and semi-urban branches, which are traditionally poorly run, poorly staffed, and were an economic liability to them. Now the commercial banks with their vast network of rural and semi-urban branches are also facing the heat of the competition from the NBFCs, MFIs and NGOs who are now aggressively tapping the rural market and filling up the space left by the commercial banks.

No doubt, rural banking had a pioneering role to play in sowing the seeds of development in the agrarian society, but few of these Public Sector Banks are reaping the reach rewards now. If they do not look smart and innovate the products for catering the rural market with a cadre of dedicated manpower. They could loose the first mover advantage.

Private sector banking giants in India like ICICI Bank Ltd & HDFC Bank Ltd. has taken a different route to tap this rural market by financing to the MFIs for on lending to the individual entrepreneur and supporting the microfinance programme for its success. Out of the Public Sector Banks, The State Bank of India has implemented the Business Facilitator/Business Correspondent model for financial inclusion and taps the rural market by increasing their reach through these outsourced agents. As economic opportunities mushroom across rural India and the commercial banking sector continues to slumber, the non-banking financial companies and MFIs are awakening from the booming demand of the rural households armed with new products and services. There are also disparities in geographic distribution of the bank branches of the commercial banks and the credit extension, which is also an important bottleneck for success of micro finance movements in India.

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While studying the level of access to the financial service providers it was found that the accessibility of the formal institutional sources of financial services are low compared to the semi-formal sources like MFIs, SHGs etc. but the most accessible form of financial services are still the informal sources like money lenders, trade creditors, local shop keepers etc.

Cost of Transaction in microfinance The effective interest rate in the microcredit is ranging between 20-45% per annum, which includes various factors such as processing fees, repayment frequency and number of installments etc. This explains how a flat interest rate of 15% per annum, can amount to an effective interest rate of 38% per annum (Shamik Ravi, 2006). A study made by Yadav & Kumbhare (2008) concludes that the effective cost of borrowing in the SHG-Bank linkage model varied between 10.40 – 18.15 %. This also includes the cost of intermediation (i.e. promotional cost). Another study conducted in Uttar Pradesh, India (Das, 2009) recorded average cost of transaction at 10.05% in the commercial banks but at the same time average rate of interest being paid by the unbanked population to the informal sector was 28.67% which is pretty high..

SECTION-III: COMMERCIAL BANKS TO IMPROVE EFFECTIVENESS FOR MICROFINANCE Commercial Banks vis-à-vis microfinance Our research findings came from in-depth study of 12 major commercial banks in India reveals that initially a great deal of microfinance undertaken by commercial banks was because of government mandates to lend to this sector rather than for business reasons. The types of commercial bank involvement in microfinance can be classified as follows: • Government-subsidised lending programs channelled through the banks • Government-mandated lending targets met by banks subsidising interest rates • Government-mandated lending targets with banks charging commercial interest rates.

• Microfinance as a profitable business Microfinance- past experience of commercial banks The large majority of commercial bankers interviewed in the process had little positive experience of banking with the poor although they are in this business for last 30 years. They experience non-payment by the poor, look at the high costs, and assume the problem is with the poor rather than with the design or delivery of their bank's products. They also distrust NGOs that provide financial services to micro-entrepreneurs, because they are not-for-profit institutions and not subject to any regulation. As a result, the majority of commercial bankers perceive microfinance as risky, unprofitable and not fitting with their core business objectives. By contrast, commercial bankers with a positive perception of microfinance had seen successful microfinance in practice, undertaken a comprehensive analysis of the size and performance of the microfinance market, and designed lending and savings products that were profitable and could reach significant scale.

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Microfinance by Commercial Banks: Sustainability and scalability When assessed based on achieving both high portfolio quality and significant scale of outreach to the poor, most of the commercial bank microfinance programmes that were mandated by governments can only be considered as failures. The exceptions were those programs that charged a commercial rate of interest. They had a higher portfolio quality than other programmes but they were still not profitable. This almost universal failure is not explained by the different policy contexts across the region of the vast country like India. Further, because microfinance has not been a profitable business, government mandates have been unsuccessful in encouraging commercial banks to become involved in microfinance. The banks must have the incentive to design better products for micro-entrepreneurs, which can be acceptable across the rural people and profitable as well.

Innovation in products & services: the Buzzword in microfinance There is an immediate need to expand the range of products available in the market, both on the savings side and on the credit and insurance sides. As the micro-finance sector grows and develops, MFIs are expected to play a greater role in the times ahead. In 2000, the RBI had allowed banks to adopt their own model of lending to micro-finance and choose any intermediaries for the purpose. As a result, new models are being experimented with by banks.

The Task Force on Supportive Policy and Regulatory Framework for Microfinance had recommended the promotion of Self Regulatory Organizations (SROs), evolving from within the MFI sector.

Key success factors for commercial bank involvement in microfinance Based on our research, and corroborated by other studies, the following were found to be key success factors for microfinance in commercial banks and to tap the untapped potential of the rural market with thumping presence: • Create a small specialised bank or a separate microfinance unit within a large commercial bank.

• Treat savings as equally important to lending (now a days considered as an important resource).

• Charge interest rates to cover all the costs of the lending products (including the service charges) with a prompt service as per the convenience of the customer.

• Ensure excellent MIS and portfolio management by using latest information technology.

• Adoption of Business correspondent and Business facilitator model for increasing the outreach.

• Create a special/dedicated cadre for rural/semi-urban branches who will handle the micro banking portfolio and train/motivate them.

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CONCLUSION The most effective way for governments to encourage commercial banks to become involved in microfinance to make this programme most successful in the world then it has to ensure an appropriate regulatory and prudential framework. The elements of an optimal policy context are: • • • • • •

sound macroeconomic policies and basic infrastructure in the rural/semi-urban areas to ensure a growing economy minimal restrictions to profitable lending, particularly no interest rate caps in the microfinance. enhance the limit of microfinance from existing Rs.50000 to Rs.1.00 lakh so that the bankers find it cost effective. enhanced ability to establish a small commercial bank which can focus on this sector (such as a low minimum capital requirement) appropriate prudential regulations for this market including capital adequacy ratios, asset quality indicators and unsecured loan limits.

Concessions in regulatory capital requirement in case of taking a sizable amount/portfolio in microfinance.

Having all these elements in place will not guarantee that commercial banks in India will enhance the scale of microfinance lending. However, there certainly would not be external constraints for up scaling the microfinance movement in India through the most vibrant segment of the Financial Sector of India with special emphasis on building and streamlining Microfinance Institutions and providing enabling environment to operate.

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REFERENCES: Das, P. K. (2009) ‘Research report on Feasibility of Business Correspondent/Facilitators models for financial inclusion in the state of Uttar Pradesh, India’ submitted to Indian Institute of Banking & Finance, Mumbai, India. May, 2009 (Unpublished).

Ghate, Prabhu (2007): ‘Microfinance in India – A state of the sector Report. Book’ published by Access development services & Ford Foundation, New Delhi, India.

NABARD (2008): Annual Report. Website: www.nabard.org Ravi, Shamik (2006): Is micro-credit too costly? - Face –Off in The Economic Times, September 15, 2006. Website: www. economictimes.indiatimes.com Srinivasan, R. & Sriram, S (2003): Microfinance in India: Discussion. IIM, Bangalore Management Review, June, 2003, p-6-21.

Thorat, Usha (2007): ‘Banking in the hinterland’. Key note address at the conference on “Banking in the hinterland” organized by IBA at Mumbai on February 14, 2007.website: www.rbi.org.

Yadav, Shalini and Kumbhare, S. L. (2008): Transaction costs under SHG-Bank Linkage programme. Bank Quest .Vol 79, No. 1, p 30-34.

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ARE CUSTOMER RELATIONSHIPS THE KEY TO PRODUCTIVITY IN MICROFINANCE INSTITUTIONS? Karl Dayson and Pål Vik, Department of Sociology, University of Salford, United Kingdom

ABSTRACT Increasing the productivity of loan officers is a key concern for managers of Microfinance Institutions (MFIs) as it is a key driver of overall sustainability. Yet there is a dearth of research analyzing the use of time among MFI staff. In this paper, we analyze timesheet data of staff members of four UK MFIs. We find that the MFIs whose lending staff spent a greater proportion of their time on direct face-to-face customer contact also had the greatest efficiency and loan officer productivity. This appears to contradict the experience of the mainstream financial sector which has raised productivity by decreasing the amount of face-to-face contact with its customer base. We suggest that the explanation for this contradiction lies in the differences in lending methodology. Banks rely on credit scoring technologies which allow them to process loan applications through web and telephone-based channels. MFIs rely to a greater extent on relationship lending whereby the loan officers collect and make their decision based on soft and non-codifiable information as well as hard and codifiable data. In this case the key to increasing loan officer productivity lies in increasing the proportion of time spent with potential customers and in making the interview itself more efficient.

KEYWORDS:

Staff productivity, microfinance

INTRODUCTION The productivity and efficiency of lending staff is important for the overall performance of Microfinance Institutions (MFIs) (Woller and Schreiner, 2001). Raising loan officer productivity enables MFIs to decrease the per-unit cost without passing on the cost to the consumer, which could have a negative effect on the institution’s ability to compete for customers. It is perhaps of particular importance for MFIs operating in industrialized countries because staff costs, of which loan officer costs is often a considerable proportion, constitute a large proportion of operating costs (see e.g. Dayson et al, 2008).

There are three principal ways in which the MFIs may do this. First, staff incentive schemes are believed to increase the productivity of loan officers (Holtman, 2001; McKim and Hughart, 2005). Staff incentives are typically linked to the number of loans issued, number of new clients, quality of portfolio (arrears) or a combination of these (Aubert et al, 2004). Already widely used in the mainstream banking sector, survey data suggest that the proportion of MFIs with a staff incentive scheme has grown considerably over the past 10-15 years (McKim and Hughart, 2005).

The proportion of MFIs with a staff incentive scheme grew from 6% in 1990 to 63% in 2003, constituting a more than tenfold growth (McKim and Hughart, 2005). Of the 106 MFIs with staff incentive schemes surveyed by McKim and Hughart (2005), 79% reported that staff incentives had a high or very high and positive effect on the productivity of loan officers. However, in summarizing the experience of the Bolivian MFI PRODEM, Bazoberry (2001) argues that incentive schemes rewarding branches or individual loan officers stifle cooperation, increase Bonus Material

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fraudulent behavior of loan officers and branches, pressurize loan officers to pay bad loans out of their own salary and distort staff motivation. Increasingly questions are also being raised about the distorting effect of staff incentives on the business objectives in the mainstream financial sector leading to a focus on short-term profit rather than longer-term institutional viability.

Second, the introduction of IT and banking transaction technologies can increase loan officer productivity by reducing the time spent on collecting payments and inputting and processing data. The introduction of such technology has enabled the mainstream banking sector to reduce their operating costs. In the case of the US banking sector, the average transaction cost of a faceto-face transaction is reduced from US$1.07 to US$0.27 (ATM) or one penny if it is conducted online (DiDio, 1998 cf. Nath et al, 2001). In the case of Spain, Hernando and Nieto (2007) find that the adoption of internet technology in the delivery of services by Spanish banks in the period 1994-2002 resulted in a reduction in staff costs.

For the microfinance sector technological innovation has centered on reducing the time and costs associated with collecting loan repayments (Ivatury and Mas, 2008). Examples include using mobile phones to repay loans. To date, the implementation of such technology has largely been confined to “those relatively few MFIs [with sufficient] financial resources and skills” (Ivatury and Mas, 2008, p. 10).

Finally, the MFIs may introduce credit scoring systems, defined as “computer-based management tools which rely upon statistical techniques to predict the credit performance of consumers” (Leyshon and Thrift, 1999, p.444). Credit scoring is believed to increase loan officer productivity by reducing the time the loan officer spends on data collection and underwriting (Allan and Frame, 2005), and, if accurate, it may also reduce the time spent on delinquency control (Schreiner, 2003). Most credit scoring systems rely on hard and easily verifiable data generally held by credit rating agencies (Leyshon and Thrift, 1999; Dellien and Schreiner, 2005; Allan and Frame, 2005). Credit scoring is widely used in the mainstream banking sector (Leyshon and Thrift, 1999; Burton et al, 2004; Berger et al, 2009). Furthermore, if combined with IT and telephony, credit scoring also enables loans to be processed via the internet or the phone.

However, to date few MFIs have implemented credit scoring technology (Dellien and Schreiner, 2005), as it is organizationally and technically demanding for MFIs to adopt. MFIs often have inadequate databases to support the use of credit scoring (Schreiner, 2003). Moreover, credit scoring may also be an inappropriate technology for the target clients of MFIs. Credit scoring is less suitable for assessing the risk of default of joint-liability groups (Schreiner, 2003) and MFI target clients often do not have a credit history because they borrow from informal sources or companies not delivering information to credit rating agencies (Competition Commission, 2006).

In many cases, MFI target clients have a poor credit history excluding them from accessing mainstream finance.

Although loan officer productivity is often – indirectly or directly – analyzed as a driver of overall sustainability (e.g. Woller and Schreiner, 2001), there is a dearth in in-depth research analyzing time-use within MFIs. One of the few examples of such research is Dayson’s (2005) analysis of the use of time by staff members of four UK MFIs. One of Dayson’s main findings 112

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was that loan officers spent considerable time on giving money and debt advice to unsuccessful loan applicants.

In response to this lack of research, this paper presents the findings of an analysis of the use of time over a three-week period of 30 staff members from four UK MFIs. We find that the MFIs whose lending staff spent a greater proportion of their time on direct face-to-face customer contact also had the greatest efficiency and loan officer productivity. This appears to contradict the experience of the mainstream banking sector, which has raised productivity by decreasing the face-to-face interaction between loan officers and loan applicants. We suggest that this can be explained by differences in the lending model. The banks’ use of credit scoring enables them to process loan applications via the web or the telephone, while MFIs tend to rely on collecting and analyzing soft, uncodifiable information that does not lend itself to web or telephone-based sales channels.

The remainder of this paper is organized into four sections. The first section outlines the UK microfinance sector and the second details the methodology applied. The third section presents the findings, while we discuss the findings and conclude in the fourth section.

THE UK MICROFINANCE SECTOR The non-member based MFIs in the UK (often referred to as Community Development Financial Institutions (CDFIs)) are independent and self-regulated, and most are affiliated to the Community Development Finance Association (CDFA) as a trade body.

Although some UK MFIs were set up in the 1980s, most of the over 70 MFIs currently operating in the UK were set up in the late 1990s with financial and technical support from the New Labour government. Intimately linked to the New Labour discourse on fostering entrepreneurship and self-employment in deprived neighborhoods and among low-income groups as opposed to tax-based income distribution (Affleck and Mellor, 2006), the MFIs initially focused exclusively on providing business loans to aspiring and existing entrepreneurs unable to access finance from the mainstream banking sector.

Although most MFIs still focus on business lending, a growing number of MFIs are also seeking to provide affordable credit (at subsidized rates) to credit-impaired households without access to finance through the mainstream finance sector. It is estimated that there are around 2.3 million users of high-cost licensed home credit lenders in the UK, equivalent to around 6% of the adult population (Ellis et al, 2006), constituting a target market for personal lending MFIs (Dayson et al, 1999).

The UK microfinance sector is still an immature sector. According to the latest industry survey from the CDFA, 49% had been in operation for less than 5 years and another 23% had been founded less than 10 years ago (CDFA, 2008). In 2008, the sector made over 12,000 loans for consumption, housing, small enterprise and social enterprise purposes (Table 1). The total outstanding loan portfolio was just above US$450 million.

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Table 1: The UK microfinance sector Personal loans

Housing loans

Enterprise loans

Social enterprise

Total

Number of loans

7,406

303

3,921

1,346

12,976

Total value OLP (US$ m)*

5.0

1.0

66.2

381.0

453.2

% MFIs offering…**

14

3

69

17

…

Source: CDFA 2008 survey of UK MFIs (CDFA, 2009) Notes: * Based on conversion rate of £1 = US$1.65 ** Based on CDFA 2007 survey as these figures not released for 2008 survey; OLP = Outstanding loan portfolio

METHODOLOGY Four UK MFIs were selected for the case study research (Table 2). The MFIs were selected because they were willing to participate and disclose financial and organizational data, and because combined the institutions cover the whole of the UK. Given the sensitive nature of the data disclosed the participating MFIs are assigned the letters A to D in place of their real names.

Table 2: The MFIs studied MFI A MFI B Number of employees (FT positions) Operational sustainability ratio (%) Total value OLP (US$ ‘000)* Financial products (% of OLP)

PL (74) BL (26)

Loans granted by product

PL: 1262 BL: 78

Other services Branches

SP

MFI C

MFI D

10

12

5

11

61.3

11.4

46.3

30.3

1,550’

329’

902’

723’

3

PL (37) BL (34) SEL (29) PL: 202 BL: 46 SEL: 2 DMA 2

PL (54) BL (46) PL: 310 BL: 23 ..

2

PL (58) BL (41) HIL (1) PL: 562 BL: 41 HIL: 4 DMA 2

Source: Loan portfolio data provided by the MFIs for the financial year of April 2006 to March 2007 Notes: * Assessed on March 31 2007 Abbreviations: PL = Personal loans, BL = Business loans, SEL = Social Enterprise Loan, HIL = Home Improvement Loans, SP = Savings products, DMA = Debt and Money Advice, FT = Full-time, OLP = Outstanding loan portfolio

The MFIs differ in terms of their business strategies and product portfolio. MFI A specializes in personal finance and has since April 2007 stopped offering business loans. MFI A operates in areas with large groups of the population at the margins of mainstream finance evenly spread allowing for large-scale personal lending. Conversely, MFI B, MFI D and, to a lesser extent, MFI C offer a wide range of services to households, social enterprises and small businesses, including advice and home improvement loans.

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FINDINGS In order to ascertain the level of staff productivity and efficiency staff members filled in a daily timesheet over a three-week period. In total, 30 out of 33 MFI staff members submitted timesheets (Table 3), and semi-structured interviews were conducted with 14 staff members across the three staff groups (admin, lending staff and management) from the four MFIs.

Table 3: Participating staff members MFI A

MFI C

MFI D

MFI B

Total

Total staff

7

6

11

6

30

Admin

2

1

2

1

6

Lenders

3

3

6

3

15

Management

2

2

3

2

9

The data was weighted according to the normal distribution of staff across the staff categories to ensure that non-participating staff members did not skew the results.

Overall time use by MFI Table 4 displays the weighted timesheet data according to activity by MFI for all staff members.

Each activity consists of numerous tasks. For example, making loans consist of loan interviews, reviewing application, issuing of loan and loan administration. A key distinction made is the distinction between the time spent on sustaining activities – tasks not easily linked to the provision of financial products (e.g. office management, reporting and promotional activities) – vs. time spent on core activities directly linked to the provision and monitoring of loans.

Table 4: Proportion of time spent by all staff by MFI (% of productive time) MFI A

MFI B

MFI C

MFI D

Average score

Loan enquiries

7.1

2.5

8.0

3.5

5.3

Money advice

1.9

0.3

0.8

0.1

0.8

No shows

2.7

0.1

0.0

1.0

1.0

Making loans

31.4

33.7

21.9

29.2

29.1

Month-end reports

4.3

1.7

4.6

2.2

3.2

Servicing loans

2.7

2.4

5.1

3.8

3.5

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Delinquency control

7.9

10.0

13.3

12.6

11.0

Promotional activities

3.5

9.7

11.5

17.0

10.4

Office management

36.6

36.9

33.9

29.1

34.1

Other activities

1.9

2.7

0.9

1.5

1.8

Notes: Reported as percentages based on weighted data Source: Timesheets submitted by MFI employees for the period 25.06.07-13.07.07

The MFIs appear to spend their time on four activities. First, tasks relating to office management constitute the single biggest activity for all the personal lending MFIs with the exception of MFI D. There seems to be a certain minimum time a MFI has to dedicate to general office tasks (a minimum of 5%), staff meetings (around 5%), queries (4-6%) and report preparation (3-5%).

Second, tasks involved in making a loan constitute the second most time-consuming category, hovering between 20 and 40% of productive time. Once the loan has been made, relatively little time is dedicated to servicing loans (2-5%). This reflects the insistence among MFIs on servicing the loans through automated bank transfers. Third, once a client falls in arrears with their payments, the MFIs display considerable willingness to invest time in chasing arrears (8-13% for the personal lending MFIs). The emphasis on delinquency control appeared to be driven by a fear that inaction on part of the MFI could foment a non-payment culture among borrowers.

Finally, MFIs also appear to invest extensive time on promotional activities (external meetings, presentations, outreach activities, marketing, liaising with partners and networking). With the exception of MFI A, the MFIs spend between 10 and 17% of their time on promotional activities.

MFI D spends the greatest proportion of its time on promotional activities largely because it has a dedicated outreach worker. Because the MFIs in the sample are still dependent on granted loan capital and other forms of subsidies, they must invest time on maintaining contracts and relations with public and private sector organizations. This may explain the time invested in external relationship management and promotional activities.

Administrator time use by MFI Table 5 shows how the administrators across the participating MFIs spend their time.

Table 5: Proportion of time spent by admin staff by category (% of productive time)

116

MFI A

MFI B

MFI C

MFI D

Average score

Loan enquiries

4.9

4.5

11.5

14.9

9.0

Money advice

0.0

1.6

3.4

0.0

1.3

No shows

0.0

0.0

0.0

0.0

0.0

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Making loans

19.8

2.9

21.4

9.9

13.5

Month-end reports

1.5

3.2

3.7

3.3

2.9

Servicing loans

13.7

15.5

16.0

23.2

17.1

Delinquency control

10.7

0.0

15.7

11.9

9.6

Promotional activities

0.0

0.0

8.9

0.3

2.3

Office management

40.3

69.9

19.4

36.5

41.5

Other activities

9.1

2.4

0.0

0.0

2.9

Notes: Reported as percentages based on weighted data Source: Timesheets submitted by MFI employees for the period 25.06.07-13.07.07

Here there is more variation than could be observed for the MFIs as a whole. This variance centers principally on the extent to which the administrators get involved in loan provision, dealing with loan enquiries and giving applicants money advice. On the one hand there are MFIs whose administrative staff members specialize almost purely on office management tasks, with very limited involvement in the MFI’s core activities. This is very much the case of MFI B, where the administrator spends minimal time on lending activities (with the exception of servicing loans). On the other, the administrators at some MFIs have an extensive involvement in the making, servicing and monitoring of loans, which is the case at MFI A. The rationale behind this division of labor seems to be to maximize the exposure of lending staff to clients. As we will see when looking at the timesheet data for the loans officers, the model seems to achieve that, as MFI A lending staff spend more time than the loans officer of any other MFI on dealing with potential customers.

The two above-mentioned divisions of labor may only work in larger organizations. The administrator in MFI C, the smallest MFI in the sample, has a non-specialized role getting involved in all aspects of the operation of the MFI. Manager time use by MFI Table 6 displays the use of time among managers across the MFIs. Table 6: Proportion of time spent by management by category MFI A

MFI B

MFI C

MFI D

Average score

Loan enquiries

1.6

1.2

3.8

0.7

1.8

Money advice

0.0

0.0

0.0

0.0

0.0

No shows

0.0

0.0

0.0

0.0

0.0

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Making loans

17.2

11.4

12.1

3.2

11.0

Month-end reports

12.4

4.0

7.7

6.1

7.6

Servicing loans

0.0

0.9

4.9

0.1

1.5

Delinquency control

7.4

1.7

7.6

0.9

4.4

Promotional activities

6.9

25.8

13.9

35.1

20.4

Office management

54.5

54.0

48.3

47.5

51.1

Other activities

0.0

1.0

1.7

6.4

2.3

Notes: Reported as percentages of productive time based on weighted data Source: Timesheets submitted by MFI employees for the period 25.06.07-13.07.07

One of the factors distinguishing the MFIs is the degree of management involvement in making loans. On the one hand, the management of MFI D only have very limited involvement in making loans. This appeared to be related to reliance on contractual income and the complexity of funding arrangements. On the other, there are managers who are much more involved in the loan process, particularly MFI A and MFI C. In the case of the former, the managers spend more than 6% of their time on interviews alone, which is more than the managers in all the other MFIs combined. This is largely a reflection of the organizational culture of MFI A. All the organization’s activities are centered on increasing the loan book through seeing potential clients. To be able to do that, managers cover for loans officers on leave and generally offer extensive lending support.

Loan officer time use by MFI Finally, we turn to the use of time among the loan officers across the participating MFIs (Table 7). The loans officers play a crucial role in a MFI as they have the most extensive contact with the client base and often build relations with customers, vital in informing ending decisions and in limiting defaults and loan losses.

Table 7: Proportion of time spent by lending staff by category

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MFI A

MFI B

MFI C

MFI D

Average score

Loan enquiries

11.8

2.6

13.4

1.7

7.4

Money advice

4.0

0.1

0.8

0.1

1.3

No shows

5.6

0.1

0.1

1.7

1.9

Making loans

46.5

54.4

38.5

48.9

47.1

Month-end reports

0.0

0.0

0.0

0.0

0.0

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Servicing loans

0.0

0.0

0.0

0.0

0.0

Delinquency control

7.2

17.4

21.6

18.9

16.3

Promotional activities

2.8

2.9

8.7

6.9

5.3

Office management

21.8

18.8

16.9

19.7

19.3

Other activities

0.3

3.7

0.0

2.1

1.5

Notes: Reported as percentages based on weighted data Source: Timesheets submitted by MFI employees for the period 25.06.07-13.07.07

Making loans constitutes the single most time-consuming activity for loans officers for all of the MFIs. On average the loan officers across all of the MFIs also spend 20% of their time on office management. There is more variation in terms of delinquency control. Three out of the four MFIs spend around 20% on delinquency control. This activity generally involves monitoring daily, weekly or monthly bank reports of direct debits, and acting accordingly by calling, paying visits to or sending letters to the clients. The loan officers are to varying degrees supported by administrators and managers in monitoring and acting upon non-payment.

Lending staff at MFI A spend considerably less time on delinquency control than the other MFIs because of its automated arrears monitoring system. This system requires loan officers to make a call to delinquent clients, whilst all other aspects of the delinquency control (further follow-ups and debt collection) are dealt with by administrative and management staff.

This time-saving arrears reporting system combined with the way in which support and management staff are organized enables lending staff at MFI A to focus on seeing potential clients. Personal loans officers at MFI A spend around 45% of their time dealing directly with clients compared to approximately 30% (MFI C), 25% (MFI B) and 15% (MFI D) for the other MFIs. The model of MFI A centers on maximizing the loans officers’ exposure to clients. It does this by assigning most other tasks not directly linked to the loan interviews to the administrators and to the management. The estimates on number of loans per full-time loan officer suggest that this enables MFI A interview and process 40% more loan applicants compared with the second-most productive MFI (Table 8).

Table 8: Personal loans officer productivity

Annual # of loans process per FT loan officer

MFI A

MFI B

MFI C

MFI D

Average score

440

308

205

253

320

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Notes: Estimated based on number of loan applicants seen during timesheet exercise Assumes 60% success rate based on data from MFI B Source: Timesheets submitted by MFI employees for the period 25.06.07-13.07.07

Three factors appear to explain the variation in loan officer productivity. First, the number of applicants a loans officer can interview is conditional on the availability of appropriate meetings rooms. In the case of MFI B, two loans officers and two debt advisors share one meeting room, limiting the number of loan applicants a loans officer can see in the course of a working day.

Second, the data also suggest that a high proportion of repeat business is conducive for loan officer productivity as they are considerably less costly to process and generally less risky. MFI A which displayed the greatest loan officer productivity also had the greatest proportion of repeat clients: 56% of loans issued in the financial year of 2006/2007 were to repeat customers, compared to 7% (MFI B), 33% (MFI D) and 52% (MFI C). Finally, the timesheet data suggest that there is a link between the proportion of productive time spent on seeing clients and loan officer productivity as depicted in Figure 1.

% loan officer time spent on direct customer contact

Figure 1: Direct customer contact and loan officer productivity MFI A

40.00

TIME = -1.33 + 0. 09 * PROD R-Sq uare = 0.69 35.00

30.00

MFI C 25.00

MFI B

20.00

MFI D

200.00

300.00

400.00

Number of loans made per FT loan officer per year

In summation, MFI A which puts the greatest emphasis on maximizing the time loans officers spend on interviewing, by involving administrators and managers in offering lending support, also processes the greatest number of loans per full-time loan officer position. Further, our findings suggest that part of maximizing lending staff exposure to potential customers may also lie in outsourcing administrative aspects of arrears control and possibly other areas to external companies.

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DISCUSSION AND CONCLUDING REMARKS The productivity of loan officers is an important lever for MFIs to reduce operating costs and increase income, crucially without passing on the costs to the clients. Hypothetically there are three ways in which MFIs can achieve this. First, the MFIs can introduce staff bonuses linked to the number of loans issued per loan officer. Second, the introduction of mobile phone and other banking transaction technology can decrease the time spent by loan officers on collecting loan payments and processing data. Third, the MFI can develop and implement a credit scoring methodology to decrease the amount of time the loan officer spends on collecting, verifying and analyzing client data.

The mainstream financial sector in developed and developing countries has sought to decrease the extent of face-to-face contact in order to increase productivity and efficiency. Mathematical and technological advances have enabled financial institutions to move towards internet and telephone based financial intermediation. The use of such technology has reduced the costs and increased the staff productivity among financial institutions.

However, we conducted an analysis of timesheet data of staff members of four UK Microfinance Institutions (MFIs) and found that the opposite appears to be true. The MFIs whose lending staff spent a greater proportion of their time on direct face-to-face customer contact also had the greatest efficiency and loan officer productivity. Provided there is sufficient demand for the products of the MFI, by organizing the non-lending in such a way to maximize the exposure of the lending staff and by allowing non-lending staff to step in for interviews when necessary, the MFI can raise the loan officer productivity considerably.

Our findings suggest that increasing lending staff’s exposure to loan applicants may also be achieved through outsourcing administrative tasks. Finally, we also found that the MFIs which displayed the greatest loan officer productivity also had the greatest proportion of repeat clients.

Repeat business involves lower transactions costs and generally constitutes a smaller risk for the MFI. How can we explain this dichotomy in raising productivity between the UK banking and MFI sector? The answer can be found in the divergent business models of the banking and the microfinance sector. The traditional MFI model is based on a relationship lending model, whereby lending decisions are based on soft, non-codifiable information (character and reliability of lender) as well as income-expenditure projections. Conversely, the mainstream bank lending model is based on transaction lending which is based on the strength of the balance sheet and income statements, or the outcome of credit scoring.

The typology developed above is simplified and in reality most MFIs operate somewhere on a continuum between the two models. In Western Europe, most lending is in the form of individual rather than group lending (Jayo et al, 2008; CDFA, 2009). However, to date few if any Western European MFIs have used credit scoring, possibly because the market gap they are covering Bonus Material

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seeks a more personalized service than that offered by mainstream financial institutions. The traditional microfinance group lending methodology is still the dominant methodology in South, South-East and Central Asia (Harper, 2007). Conversely, in South America lending is predominantly in the form of individual loans (MIX, 2008). In addition to geographical patterns, age and size is also likely to be a determinant of the lending methodology. Institutions that have reached greater maturity and that have a greater client base may be in a stronger position to develop and implement a credit scoring technology.

The implication of this is that the pathways to increased productivity may differ depending on the typology of the organization. MFIs that have moved more towards a mainstream lending methodology are likely to benefit in terms of loan officer productivity from investing in internet and telephone-based sales channels. This is especially the case for MFIs that have adopted credit scoring whose hard, codifiable data lend themselves well to such channels. Conversely, MFIs whose lending is centered on a more traditional microfinance model are more likely to increase loan officer productivity by maximizing the lending staff’s exposure to potential customers, namely reorganize staff to increase time frontline staff spend on seeing potential customers and implement time-saving outsourcing mechanisms.

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Bazoberry, Eduardo (2001). “We Aren’t Selling Vacuum Cleaners: PRODEM’s Experiences with Staff Incentives,” The Micro Banking Bulletin – Focus on Productivity, issue 6, April, p.

11-14 Berger, A. N., Cowan, A. M. and Frame, W. S. (2009). “The Surprising Use of Credit Score in Small Business Lending by Community Banks and the Attendant Effects on Credit Availability and Risk,” Federal Reserve Bank of Atlanta Working Paper, 2009-9, March, p. 1-23.

Berger, Allan N. & Frame, W. Scott (2005). Small Business Credit Scoring and Credit Availability. Federal Reserve Bank of Atlanta, March 2005.

Berger, Allen N. & Udell, Gregory. F. (2002). “Small business credit availability and relationship lending: the importance of bank organizational structure,” The Economic Journal, vol. 112, p. F32-F35.

Burton et al. (2004). “Making a Market: the UK Retail Financial Services Industry and the Rise of the Complex Sub-prime Credit Market”, Competition & Change, vol. 8(1), p. 3-25.

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CDFA (2008). Inside Out 2007 – The State of Community Development Finance. London: CDFA. CDFA (2009). Inside Out 2008 – The State of Community Development Finance. London: CDFA. Competition Commission (2006). Home credit market investigation. Report prepared by the UK Competition Commission, November 2006.

Dayson, K., Paterson, B., Salt, A., and Vik, P. (2008). Lloyds TSB Operational Sustainability Research Project – Final Technical Report. Report prepared for Lloyds TSB March 2008.

Dayson, K., Paterson, R. and Powell, J. (1999). Investing in people and places. University of Salford.

Dayson, Karl (2005). Are community finance institutions doing too much? Paper presented at the Institute of Small Business Entrepreneurs conference, Blackpool.

Dellien, H. & Schreiner, M. (2005). Credit Scoring, Banks, and Microfinance: Balancing HighTech with High-Touch. Women’s World Banking and Microfinance Risk Management, December 18.

Ellis, Anna, Collard, Sharon & Forster, Rob (2006). Illegal lending in the UK. Research report prepared for the UK Department of Trade and Industry, November 2006.

Harper, Malcolm (2007). “What’s wrong with groups?” In Thomas Dichter & Malcolm Harper (Eds.) What’s wrong with microfinance?, p.35-48. Rugby: Intermediate Technology Publications Ltd. Hernando, I. & Nieto, M. J. (2007). “Is the internet delivery channel changing banks’ performance? The case of Spanish banks,” Journal of Banking and Finance, vol. 31, p. 10831099.

Holtman, Martin (2001). “Designing Financial Incentives to Increase Loan Officer Productivity: Handle With Care!” The Micro Banking Bulletin – Focus on Productivity, issue 6, April, p. 5-11 Ivatury, Gautam & Mas, Ignacio (2008). “The Early Experience of Branchless Banking,” CGAP Focus Notes, no. 46, April, p. 1-16 Jayo, B., Rico, S. and Lacalle, M. (2008). “Overview of the Microcredit Sector in the European Union, 2006-2007,” EMN Working Paper, no. 5, July, p. 1-68.

Leyshon, A. & Thrift, N. (1999). “Lists come alive: electronic systems of knowledge and the rise of credit-scoring in retail banking,” Economy and Society, vol. 23(3), August, p. 434-466.

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Leyshon, A., & Thrift, N. (1995). “Geographies of financial exclusion: financial abandonment in Britain and the United States,” Transactions of the Institute of British Geographers, vol. 20(3), p.

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McKim, Andrew & Hughart, Matthew (2005). Staff Incentive Schemes in Practice: Findings from a Global Survey of Microfinance Institutions. Microfinance Network and CGAP, September 2005.

MIX (2008). Latin America Microfinance Analysis and Benchmarking Report, 2008. A report from the Microfinance Information Exchange, September 2008.

Nath, R., Schrick, P. & Parzinger, M. (2001). “Bankers’ Perspectives on Internet Banking,” Eservice Journal, Volume 1(1), p. 21-36 Schreiner, Mark (2003). “Scoring: the next breakthrough in microcredit?” CGAP Occasional Paper, no. 7, January, p. 1-62 Woller, Gary & Schreiner, Mark (2001). Poverty lending, financial self-sufficiency, and the six aspects of outreach. Small Enterprise and Education Promotion Network.

ACKNOWLEDGEMENT The authors would like to thank Lloyds TSB for funding the research project and the management and staff at the participating MFIs for sharing their knowledge, experiences and innovative practices with the research team. The authors are also indebted to their colleagues Anthony Salt and Bob Paterson for their contribution to the research project.

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