Key features and microfinance practices

There are several unique practices related to microfinance service provision, including a) lending through groups, b) targeting women, c) focusing on poor and unserved borrowers, d) charging commercial interest rates, and e) a small transaction unit size (Armendáriz & Morduch 2010; Karlan & Goldberg 2011). This study uses these practices to conceptualise the use of effectuation, causation, and deliberate practice theories within the microfinance context and outline the scope of the empirical research (see section 2.5).

Group-based lending

MFIs use either individual or group-based lending mechanisms to provide microfinance services (see Figure 2.1).

As Figure 2.1 illustrates, there are two main group lending mechanisms: a) solidarity groups, and b) village banks (Armendáriz & Morduch 2010; Karlan & Goldberg 2011; Ledgerwood &

Lending mechanisms

Individual lending Group-based lending

Solidarity groups Village banking

Figure 2.1: Lending models

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Earne 2013). Solidarity groups consist of 3 to 10 members who guarantee each other's loans (Ledgerwood & Earne 2013). Grameen type groups where five members guarantee each other’s loans are the most common solidarity group. If any group member fails to repay a loan, guarantors are expected to repay. A collection of around six solidarity groups is called a centre and acts as a collection and loan disbursement unit in the village (Karlan & Goldberg 2011).

The other common type of group lending is the village banking mechanism, famous in Africa, Latin America, and some parts of Asia (Armendáriz & Morduch 2010). Around 10 to 30 members form a village bank where they manage a fund accumulated through member savings. Then, as a unit, they borrow from MFIs (Karlan & Goldberg 2011). Usually, village banks maintain a clear differentiation between savings collected from members and external loan funds (Karlan & Goldberg 2011; Ledgerwood & Earne 2013).

Individual lending is the provision of credit to individual members instead of a group and has similar characteristics to traditional banking. Some MFIs provide loans to individual group members who perform well in groups as a way of rewarding them. However, individual lending requires a thorough eligibility assessment before granting loans, close follow-up, and monitoring (Ledgerwood & Earne 2013). Unlike traditional banking, microfinance individual lending uses non-traditional collateral and collateral substitutes. For example, payments of utility bills as electricity, gas, phone, and rent are sometimes used to establish a borrower's transaction history (Ledgerwood & Earne 2013). In addition, compulsory savings and household items with low market value but with high personal value are used as collateral substitutes (Karlan & Goldberg 2011; Ledgerwood & Earne 2013).

There are positives and negatives associated with group and individual lending mechanisms. Group-based lending mechanisms operate with the principle of joint liability where the group is responsible for repaying loans (Armendáriz & Morduch 2010). This has benefits for both lenders and borrowers. Ghatak and Guinnane (1999) outline four main benefits of joint liability to lenders. First, joint liability reduces the cost of screening and mitigates MFI selection problems as borrowers themselves select others. Without joint liability, MFIs are unable to distinguish 'good' borrowers from 'bad' ones due to limited information. Thus, MFIs can ascertain the risk level of potential borrowers. Second, it ensures that borrowers use the loan properly and thus assure loan repayment. Third, joint liability reduces monitoring costs to the

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organisation, as MFIs know about the borrower’s ventures from peers. Fourth, MFIs can use joint liability to enforce repayment, if a member is reluctant to do so (Ghatak & Guinnane 1999). For the borrower, joint liability increases access to financial services as they often do not have collateral to secure a loan.

However, the costs and benefits of joint liability especially for borrowers, need to be carefully weighed. Joint liability is designed to reduce risks in financial service provision as it requires group members to monitor each other. Sometimes group members inflict penalties upon each other if they have selected risky projects and have over-burdened groups with additional risks (Armendáriz & Morduch 2010). Some even impose non-financial sanctions on members who do not repay microfinance loans. Thus, this 'policing' function of members on behalf of MFIs has the potential to damage existing social ties and networks within the community (Ghatak & Guinnane 1999).

Peer monitoring and joint liability might not be so effective in some geographical areas. For example in areas where there is high labour mobility, joint liability may not work as group members frequently change. In addition, in rural areas where households are scattered, areas with social divisions, and in urban areas where there are many migrants, peers may not have enough information to trust other members to the degree required by MFIs. Hence, individual lending without group liability is more practical in these communities (Armendáriz & Morduch 2010).

Furthermore, 'free riding' can occur where some members continuously default on their loans, compelling other group members to repay (Ghatak & Guinnane 1999). These 'good' borrowers who continuously repay their own and the loans of free riders are used by credit officers to pressure defaulting members by threatening to withdraw from the location (Armendáriz & Morduch 2010). These practices have a negative effect on 'good' borrowers who may exit from groups altogether (Armendáriz & Morduch 2010) (see e.g., Grameen Bank details explained in Armendáriz & Morduch 2010).

Focus on women

The practice of MFIs targeting women originated from the experience of the Grameen Bank where providing credit to women borrowers, rather than to men, was successful (Armendáriz

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& Morduch 2010). Table 2.2 shows the percentage of women in some key MFIs in South Asian countries.

Table 2.2: Percentage of women borrowers in selected MFIs

Country Institution % women out of the total borrowers

Afghanistan

(as of 31 December, 2014)

The First Micro Finance Bank 16.93% out of 51,737 FINCA – Afghanistan 77.72% out of 29,047 Bangladesh (as of 31 December, 2014) Brac 88.89% out of 4,239,936** ASA 91.76% out of 4,444,461 BURO 91.61% out of 841,475 Bhutan (as of 31 December, 2013)

Bhutan Development Bank Limited

38.70% out of 38,868 India

(as of 31 March, 2014)

Bandhan Financial services Private Limited

100% out of 5,409,866 SKS Microfinance Limited 100% out of 4,963,046 Shri Kshethra Dharmasthala Rural

Development Project

82.23% out of 4,309,265 Nepal

(as of 16July, 2014)

Nirdhan Utthan Bank Limited 99.08% out of 139,418 Pakistan

(As of 31 December, 2013)

Khushhali Bank 26.54% out of 408,986

ASA Pakistan 99.98% out of 179,588

Kashf Foundation 100% out of 230,810***

Sri Lanka

(As of 29 June, 2015)

Berendina Microfinance Institute 80% out of 66,208 Hambantota Women's

Development Federation

100% out of 23,890 Sewa Community Credit 89% out of 15, 666 Compiled from Mix Market (2015) and Lanka Microfinance Practitioners’ Association (2015) **as of 31 December, 2013

***as of 30 June, 2014

Table 2.2 highlights that while banks have comparatively fewer women clients, all other types of MFIs focus on women borrowers. NGO-MFIs, especially, have a significant percentage of women.

MFIs focus on women for several reasons (Armendáriz & Morduch 2010; D'Espallier et al. 2011; Fletschner 2009; Wahid 1999). First, in terms of loan repayment, women have been

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found to be more trustworthy than men (Armendáriz & Morduch 2010). D'Espallier et al. (2011) analysed 350 MFIs from 70 countries for over 11 years and confirmed that MFIs with a higher proportion of women have a lower portfolio-at-risk and loan write-off. Aggarwal et al. (2015) highlight that targeting women is associated with social trust and in countries where social trust is low, women's higher creditworthiness is highly important for loan repayments.

Second, MFIs target women because of the social impact, especially as they are responsible for household expenditure including childrens' education and health (Armendáriz and Morduch 2010). Khandker (2005) and Pitt and Khandker (1998) demonstrated that household expenditure significantly increases when microfinance loans are granted to women but did not increase when they were granted to men.2 Furthermore, microfinance services provided to women are invested in both productive and consumption activities allowing families to cope with crisis (Garikipati 2008).

Third, there is a greater urgency, as shown by the Grameen Bank, as women are more economically vulnerable (Wahid 1999). Women are more credit-constrained (Armendáriz & Morduch 2010; Fletschner 2009) and the level of poverty among women is higher than among men (Armendáriz & Morduch 2010). For example, the United Nation Human Development Report (2014) shows that the estimated GNI per capita is USD 8,956 among women compared to men at USD 18,277.

Fourth, microfinance lending mechanisms are considered to be more suitable for women (Wahid 1999; Johnson 2004). For example, a study on gendered patterns in financial markets in Central Kenya highlights that activities controlled by men are large, periodic, and sometimes irregular in contrast to women’s smaller but more frequent activities (Johnson 2004). Armendáriz and Morduch (2010) also point out that women are more conservative about their investment choices. In addition, women generally request smaller loans compared to their male counterparts and, as a result, only incur limited losses if they default (Agier & Szafarz 2013a). The opportunity cost of women participating in microfinance programs is lower than

2 _{Roodman and Morduch (2014) critiqued the methodology used to derive Pitt and Khandker (1998)'s} findings. Roodman and Morduch (2014, p. 583) argue that original results on poverty reduction disappear after dropping outliers and by using a robust linear estimator. However, Pitt (2014) counter these arguments and explain that the methodology used in Pitt and Khandker (1998) is valid, and findings indicate a reduction in poverty.

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for men as they generally work close to their households (Wahid 1999) and from an institutional perspective, the limited mobility of women is an advantage as MFIs can easily monitor borrowers (Armendáriz & Morduch 2010).

However, the 'feminisation' of debt and the near perfect repayment rates need to be examined in the light of social costs. For example, Wilson (2015) questions the logic of women targeted microfinance services as they maintain existing power relations and gendered social structures and reinforce the maintenance of oppressive gender relations. Ali (2014), Karim (2008) and Wilson (2015) say that microfinance schemes operate by considering the ‘honour and shame’ instilled in women as collateral to ensure repayments. The language used by other group members in case of default, creates social and psychological pressure and affects honour and dignity (Ali 2014). Furthermore, MFIs reinforce gendered assumptions about female roles and responsibilities such as: poor women have unlimited time; they are responsible for the welfare of children; and ‘good’ wives, daughters, and daughters-in-law make sacrifices for their families (Karim 2008; Wilson 2015). In addition, although women borrow, loans are often controlled by men in the family (Goetz & Gupta 1996; Garikipati 2008) because of the power relations within the household in a patriarchal society (Wilson 2015). In some cases, loans to single women are provided to male relatives beyond even the immediate household to guarantee a regular food supply (Goetz & Gupta 1996). Although women are a better credit risk and maintain repayments even with personal sacrifices, they are subjected to harsher credit rationing than men (Agier & Szafarz 2013a). Hence, although women often have prioritised access to credit from institutionalised sources, complex social ties and wider societal structures pose challenges for women in utilising credit.

Emphasis on the poor

A major objective of MFIs is to deliver services to poor and unserved or underserved communities. Pistelli et al. (2011) report that 86% and 77% of MFIs, from a sample of 405 institutions, had poverty reduction and reaching rural borrowers respectively as the key objectives. These claims are supported by empirical studies. For example, Navajas et al. (2000) report that MFIs in Bolivia reach the poor just above or below the poverty line. They also found that the share of poorer borrowers is higher among rural lenders.

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poor (Amin et al. 2003; Navajas et al. 2000), a situation acknowledged by MFIs as well. For example, Pistelli et al. (2011) found that, out of 1,577 mission statements of MFIs only 42 (2.6%) explicitly mentioned terms such as ‘poorest’, ‘extreme poor’ or ‘very poor’. Hermes and Lensink (2011) outline four main reasons for not serving the poorest. First, the poorest may be too risk averse to borrow and invest in their future. Second, these poorer borrowers are not usually accepted by other group members as they are considered a bad credit risk. Third, staff members may not include them in programs as these poorer borrowers are more risky. Fourth, microfinance delivery models may exclude poorer borrowers from the system due to design features.

Consequently, some MFIs have implemented additional programs to incorporate the very poor into mainstream microfinance lending programs. One such program is the ultra-poor program of Brac Bangladesh (El-Zoghbi et al. 2009; Hulme et al. 2011). This program is designed as a step-wise graduation to microfinance loans where, initially, the poorest are provided with consumption support and small cash grants or goods in-kind. Gradually these people are encouraged to start saving then are provided with skill training followed by asset transfers with subsidised payments. Successful borrowers are then linked with microfinance services (El- Zoghbi et al. 2009; Hulme et al. 2011).

Despite these efforts, Coleman (2006) and Kondo et al. (2008) found that the poor are not served to the extent that MFIs claim. Hence, although MFIs have an overall vision and mission of providing microfinance to the poor, in practice institutions may be serving a cross-section of borrowers ranging from the poorest to non-poor.

Market-based interest rates

MFIs provide loans with market-based interest rates covering the full cost of serving borrowers including administrative expenses, the cost of capital (including inflation), loan losses, and provisions for increasing equity (Goodwin-Groen 2002). However, the main element of the interest rate, the administrative expense (Dorfleitner et al. 2013), is higher in percentage terms for a small loan (i.e., USD 100) than the cost of making a larger loan (i.e., USD 10,000) (Goodwin-Groen 2002). This is because the poor often do not have credit histories and collateral. In addition, microfinance borrowers live in remote areas where doorstep service delivery increases overhead and administrative costs (Goodwin-Groen 2002). Furthermore,

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additional fees, compulsory savings, and insurance premiums in microfinance loans also increase the actual cost of a loan to a borrower.

Although high interest rates have been characteristic of the microfinance industry and evidence such as the financial diaries of Collins et al. (2009) indicate that the poor can repay MFI loans, most critics and the general public are uneasy about charging high rates. Accordingly, MFI interest rates have been subjected to public scrutiny in the last few years as a result of two main incidents. First, in 2005-2006, the district governments in 23 administrative districts in Andhra Pradesh in India closed 50 branches of four MFIs due to allegations of unethical collection practices including charging high interest rates and profiteering (CGAP 2010). The situation worsened when some borrowers, defaulting on payments, took their own lives (Marr & Tubaro 2011). Second, institutions transforming themselves into private commercial entities were criticised for taking undue advantage of the poor (Rosenberg et al. 2009). For example, Compartamos in Mexico and SKS in India in the initial public offerings sold their shares for an extremely high price making some sellers instant millionaires (Chen et al. 2010; CGAP 2010; Rosenberg et al. 2009). As a result, in some countries interest rate caps (i.e., ceilings) have been introduced to protect borrowers from usurious interest rates, though this may lead to MFIs retreating from rural or costly markets, slowing down market penetration, and introducing additional fees and charges limiting transparency in pricing (Helms & Reille 2004).

Small transaction unit size

Small transaction unit size is another main feature of MFIs. The logic of a small microfinance loan is the affordability of repayment by poor and low-income borrowers, although affordability may change according to the context. Figure 2.2 illustrates the differences in average loan size across various countries using Vision Fund managed MFIs.3

3 _{Vision Fund is selected here because of its worldwide reach. It covers Africa, the Middle East and} Eastern Europe, Asia, and Latin America and the Caribbean.

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MFIs use borrowers’ characteristics, such as gender and family size, to determine loan size (Mason 2014). For example, even within MFIs, women seem to get smaller loans compared to men as they are perceived to be running relatively small businesses (Agier & Szafarz 2011, 2013a; Mason 2014). The loan size changes with the marital status of borrowers where married and women-headed households receive larger loans compared to single, divorced or widowed borrowers (Fongthong 2012). Furthermore, borrower households with a number of income earners and a large asset base receive larger loans as they have multiple income sources for repayments (Fongthong 2012; Mason 2014). Borrowers who show loyalty to the MFI by obtaining repeated loans and groups with established credit histories also access larger microfinance loans compared to new entrants and new groups (Fongthong 2012; Godquin 2004; Mason 2014).

Loan officer characteristics (i.e., lenders’ features) also have an effect on the average loan size. For example, Agier (2012) indicates that experience gained by working in the same MFI assists loan officers in determining the size of the loan that borrowers are able to repay. In addition, Agier and Szafarz (2013a, 2013b) indicate that loan officers’ gender biases affect loan size decisions. In addition, Schreiner (2001) argues that loan features such as term of maturity, loan instalment size, and time gap between two loan instalments also affect the ultimate decision about loan size.

- 200 400 600 800 1,000 1,200 Eth io p ia G h an a Ke n ya Ma law i Ma li Rw an d a Se n egal Tan za n ia U gan d a Za m b ia Arm en ia Cam b o d ia In d ia Mo n golia My an m ar Ph ili p p in es Sri La n ka Vie tn am Boli via Dom in ican Rep u b lic Ecu ad o r El Sa lv ad o r G u at e m ala Ho n d u ras Me xico N icara gu a Pe ru

Figure 2.2: Average loan size of MFIs of Vision Fund

Source: Compiled using Vision Fund International (2014)

US

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This section (2.2) discussed the main features of microfinance services highlighting the overall context of this study. However, to explore specific features of the context of the study closer examination is required of Sri Lanka and its MFIs. The next section reports relevant characteristics of Sri Lanka and outlines its microfinance context.