4.3 Measures of Outreach and Sustainability
4.3.1 Outreach Dimensions
4.3.1.1 Depth of Outreach
Depth of outreach can be estimated by assessing how low down the poverty chain clients serviced by MFOs are, and whether they belong to any specifically disadvantaged or difficult to reach groups, such as women. Navajas etal., (2000) used an index of the fulfillment of basic needs to assess the poverty level of clients of several Bolivian MFOs. This index was based on housing, access to public services, levels of education and access to health services, and was compared to a similar index for all urban and rural households in parts of Bolivia.
This type of analysis requires a detailed survey of the clientele of MFOs, which was beyond the scope of this study of four MFOs in KZN.
Yaron (1992) and Christen et al., (1994) suggest several proxy measures to assess the depth of outreach. These are based on average loan size, percentage of rural clients and percentage of a specifically disadvantaged group of individuals in the portfolio of the MFO. Average loan size is used as a primary indicator of depth of outreach since it is a readily available proxy for income level. Previous research has shown that MFOs offering small loans tend to serve the very poor clients and that larger loans correlate with higher-income clients.
The loan size proxy assumes that loan size is determined by cash flow, with poor borrowers having low incomes and hence small cash flows, enabling them to only service small loans (Christen etal., 1994). There are, however, some precautions to interpreting small loan size, as loan size may reflect the status of the lender rather than the borrower. If MFOs have funding constraints, they often restrict the money that they lend to each client (Christenetal., 1994). Navajaset al., (2000) found that the Bolivian MFOs lend to the higher-earning poor as defined by the index of fulfillment of needs. This may distort the measure of average loan size. But when compared to financial organisations that do not provide financial services to
low-income individuals, average loan SIze may be a reasonable indication of depth of outreach.
In assessing depth of outreach an important caveat is that individuals that access loans must be credit-worthy. Credit-worthy poor individuals may have relatively higher incomes than the poorest of the poor and thus would have higher average loans. The ultimate measure of depth of outreach is to assess whether MFOs have reached the poorest of the poor, those that demand loans and that are credit-worthy. The study by Navajaset a!., (2000) was not able to do this. Navajas et al., (2000) found that rural borrowers were poorer than urban borrowers, and hence that the percentage distribution of rural clients was a proxy for depth of outreach.
A similar premise holds of the percentage of women clients in a portfolio. Norms of female seclusion in rural areas are common, giving women limited access to financial services and material and human resources (Yaron, 1994). Savings facilities can potentially reach a far greater number of poor clients than lending, with international research showing that the average deposit size is much smaller than the average size of the loan extended (Yaron, 1994). A similar premise relating savings to income holds as that for loans. The average balance in a savings account may to some extent be a better indicator of depth of outreach than average loan size. The only problem is that not all MFOs offer savings facilities.
4.3.1.2 Worth toUsers
Worth to users can be measured by repeat use of financial services by poor borrowers. Repeat use can answer the question of whether the gains for poor customers exceed the costs (Schreiner, 1997). Schreiner (1997) suggests two measures for repeated use ofloans. The first measures loans per borrower since birth, and the second measures the drop-out rate. Both measures are relatively simple to compute and provide a relatively quick answer to a complex
question. However, there are important caveats to these measures, the first being that of defining 'good' and 'bad' ranges for these measures. Secondly, the drop-out rate of an organisation can grow without signaling worse performance. Thirdly, a fast growing client base and increasing term can distort both measures since existing borrowers are swamped by new borrowers. Finally, the drop-out rate does not indicate whether a borrower has just rested, defaulted or quit borrowing from the organisation. Data for computing a drop-out rate were not readily available from the KZN MFOs and will thus not be reported on in detail.
4.3.1.3 Cost to Users
Cost to users is intimately linked not only to the cost of fmancial services but also to transaction costs incurred by borrowers in accessing financial services. The direct costs of fmancial services are measured by interest charges, non-interest costs and deposit transaction fees. Transaction costs in the KZN study are not measured directly, but are proxied by the proximity of branches to the customer base and time taken to interact with the fmancial services (loan approval times, time taken to withdraw deposits, mechanisms used to disperse the funds). Group loans may impose costs on borrowers through peer monitoring efforts required by the joint liability rules (Yaron, 1992; Gonzalez-Vegaet al." 1997). The pledging of collateral can impose certain costs on borrowers such as bond registration costs, maintenance of the value of the asset and forfeited use of the asset. Similarly, deposit technologies can impose transaction costs on savers if the process of accessing savings is bureaucratic and time-consuming, and if the deposits are not paid out immediately or are not in cash, but in kind (Gonzalez-Vegaetal." 1997). Since transaction costs for borrowers and savers are closely linked to the fmancial technology used by MFOs, this will be covered in the evaluation of financial technologies.