Bio-based and Applied Economics 3(3): 271-283, 2014 ISSN 2280-6180 (print) © Firenze University Press ISSN 2280-6172 (online) www.fupress.com/bae Full Research Article DOI: 10.13128/BAE-13551 Performance and productivity changes in microfinance banks in South-West Nigeria Musa a. OlasupO1,*, CarOline a. afOlaMi2, adebayO M. shittu2, a.a.a. agbOOla3 1 Development Finance Office, Central Bank of Nigeria, Abeokuta. Ogun State, Nigeria 2 Department of Agricultural Economics and Farm Management, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria 3 Department of Mathematics, Federal University of Agriculture, Abeokuta, Ogun State, Nigeria Abstract. The Nigerian Microfinance sub-sector is yet to attain the desired level of global best practice. This paper thus investigated the performance and productivity changes of MFBs in South-West Nigeria, from 2006 to 2010, having had the Microfi- nance Policy launched in 2004. From the use of relevant accounting ratios, the study revealed that only 16% of the sampled MFBs met the recommended maximum PAR value of 5% in 2006. It was also revealed that 31% of the sampled MFBs reported a debt/equity ratio above the recommended value of 2 in 2006, while 32% had gearing of over 2 in 2010. The Malmquist productivity index revealed that the MFBs expe- rienced fluctuating performances in their productivity changes, with pure technical efficiency improvements in 2007 and 2009. Overall, the performance and productiv- ity changes experienced by the MFBs depicted a sub-sector with huge potentials and hence require nurturing to achieve its goals. Keywords. Microfinance banks, performance, Malmquist productivity index, pro- ductivity changes. JEL Codes. O16 1. Introduction Microfinance institutions (MFIs) in sub-Saharan Africa comprises a variety of diverse and geographically dispersed institutions that offer financial services to low-income cli- ents: non-governmental organizations (NGOs), non-bank financial institutions, coopera- tives, rural banks, savings and postal financial institutions, microfinance banks (MFBs) and an increasing number of deposit money banks (DMBs). MFIs provide a range of financial services (loans, savings, micro-insurance, micro-leasing, funds transfer, pension services etc.) to poor households. Their worldwide growth in numbers has had a positive impact by providing the poor with microfinance services and has helped create an encour- aging socio-economic environment for many households of these developing countries. * Corresponding author: maolasupo@cbn.gov.ng. 272 M.A. Olasupo, C.A. Afolami, A.M. Shittu, A.A.A. Agboola The nature of these institutions is quite different from traditional financial institutions (Deposit Money Banks) as they are smaller in size, limited in their services towards the poor households and often provide small collateral-free group loans. The basic operational objectives of MFIs revolve around two approaches or paradigms namely the “institutionist” and the “welfarist paradigms”. The “institutionist paradigm”, which affirms that MFIs should generate enough revenue to meet their operating and financing costs and the “welfarist paradigm”, which includes a focus on poverty allevia- tion and depth of outreach along with achieving financial sustainability. Brau and Woller (2004) posited that an efficient MFI management should promote these two objectives. Vetrivel and Kumarmangalam (2010) submitted that the fundamental problem is not so much of unaffordable terms of loans as the lack of access to credit itself. The lack of access to credit for the poor is attributable to practical difficulties largely due to the discrepancy between the mode of operation followed by financial institutions and the economic char- acteristics and financing needs of low-income households. They concluded that Microfi- nance Institutions (MFIs) worldwide have shown that micro enterprises loans can be prof- itable for borrowers and lenders alike, making microfinance one of the most effective pov- erty reducing strategies. Lafourcade et al. (2005) reported that MFIs in Africa are dynamic and growing. In their study, they confirmed that African MFIs are among the most productive globally, as measured by the number of borrowers and savers by staff member among other positive indices. They also noted that African MFIs face many challenges. Technological innova- tions, product refinements, and ongoing efforts to strengthen the capacity of African MFIs are needed to reduce costs, increase outreach, and boost overall profitability. These fur- ther underscore the need to increase the service delivery capacity of these MFIs amidst the enormous potential in the market. In recognition of the important roles of Microfinance in the overall development of the Nigerian economy, the Federal Government of Nigeria launched a Microfinance Policy for Nigeria in the year 2005. The Microfinance Policy, Regulatory and Supervisory Frame- work for Nigeria was one of the key innovations adopted to diversify the supply axis of the financial market with a major policy thrust of significantly enhancing the latent capac- ity of the poor for entrepreneurship through the provision of microfinance services to enable them engage in economic activities and be more self-reliant, increase employment opportunities, enhance household income and create wealth (CBN, 2005). MFBs are expected to empower the economic active poor in the grassroots especially those that do not have access to the conventional banks. The major economic activity of these targeted clients is agriculture or agro-allied as they are mostly involved in various nodes of the agricultural value chain. The agriculture and agro-allied activities covered by the MFBs include: crop production, animal husbandry, cassava processing, feed mill- ing etc. CBN (2012) gave the breakdown of the sectoral funding by MFBs as: Agriculture and Forestry (6.31%); Mining and Quarrying (0.65%); Manufacturing and Food process- ing (3.10%); Real Estate and Construction (5.27%); Transport and Commerce (74.60%); and others (10.07%). Hence, a meaningful effort to improve their economic prowess could help jump-start the agricultural revolution. Kulik and Molinari (2004) suggested that for MFIs to meet this huge potential, it is critical that they achieve financial self-sustainability with little or no dependence on donor 273Performance and productivity changes funds. The further stated that despite the excellent prospects of the sector, with low loan default rates and untapped demand for financial services by low-income groups, only 1% of the MFIs are self-sustainable and average Adjusted Return on Asset (ROA) is still neg- ative across all continents. The also highlighted the MFI’s lack of access to recent tech- nology as a prime reason for their poor performance. This submission was buttressed by Frankiewicz (2003), who posited that Information technology (IT) can be a strategic tool for microfinance in Africa. It can facilitate more efficient and effective collection, process- ing and use of data; it exposes microfinance institutions to offer new products and better customer service; it enables greater outreach; and facilitate integration with the rest of the financial sector. The global financial crisis of 2007 also had a significant effect on microfinancing worl- wide as microfinance institutions experienced liquidity crunches; increased cost of funds and foreign exchange; reduced disposable income for loan beneficiaries and an increase in portfolio arrears (Kruijff and Harstenstein, 2013). The Nigerian microfinance sub-sector was not too exposed to these adversities due to the stringent regulatory requirements that guides their operations. Microfinance Banks are not involved in foreign exchange transactions; they get little or nothing as grants or foreign aids; their exposure to credit risks is also limited due to their low gearing. However, they were not exempted from the rising portfolio in arrears due to the general reduction in the disposal income of their beneficiaries. This paper will seek to determine the performance and productivity changes of Microfinance Banks in South-West Nigeria over the period of 2006 to 2010 in the light of the Central Bank of Nigeria’s (CBN) revocation exercise of September 2010 that revoked the operating licenses of 224 MFBs after the Target Examination conducted on 820 MFBs. The result of the examination showed that the affected banks were ‘Terminally Distressed’ and ‘Technically Insolvent’ and/or had closed shop for at least six months. Some of the factors adduced for their failure among others include: high level of non-performing loans, resulting in high portfolio at risk; gross undercapitalization in relation to their lev- el of operations; poor corporate governance and incompetent boards; high level of non- performing insider-related credits, and other forms of insider abuse; heavy investment in capital markets with resultant diminution in the value of investment after the meltdown; poor asset-liability management owing to portfolio mismatch etc. Hence an investigation into the operational performance of the MFBs will provide further insight into their level of preparedness as catalyst in the financial intermediation process of the economic active poor in the country. 2. Research methodology Thapa (2007) posited that sustainability in microfinance can be financial, manageri- al or organizational but that financial sustainability dominates as a measure of efficiency, profitability and productivity. The institutionality and financial sustainability of any MFI lies in its ability to cover all operational expenses from income earned through finan- cial services after making proper adjustments for inflation, subsidies etc (Natilson et al., 2001; Rosenberg, 2009; Dzene and Asiedu, 2010). Shah (1999) and Natilson et al. (2001) suggested repayment rates, operating cost ratio, portfolio quality as additional measures upon which MFIs performance can be hinged. Performance measurement is defined as 274 M.A. Olasupo, C.A. Afolami, A.M. Shittu, A.A.A. Agboola the process of developing indicators to assess progress towards certain predefined goals and reviewing performance against these measures. It is also the use of statistical evidence to determine progress toward specifically defined organizational objectives. Natural meas- ures of performance often involves productivity ratios of output(s) to input(s) with larger values of this ratio associated with better performance. Performance measurement is often done in comparison to either the previous performances or to the performance of similar units or certain benchmarks in the industry. Performance measurement using ratio analy- sis is the most widely used technique in financial analysis. An accounting ratio is a pro- portion or fraction or percentage, expressing a relationship between one item in a set of financial statements and another item in the same financial statements. Ratio analysis is the most important device for interpreting the performance of organizations from their financial statements. The essence of any interpretation of financial statements is comparison (comparison of current with past figures of the same firm and with its budget or forecast, and com- parison with the performance of similar firms in the industry). In order to facilitate this comparison, it is customary to express figures in ratios or percentages, so that a disparity in size between two firms does not prevent comparison of their results. Production is the transformation of inputs into outputs or it could be defined as any activity that creates present or future utility. It may also be equivalently described as a process that transforms inputs into outputs (Frank, 2008). Data Envelopment Analysis (DEA) was proposed by Charnes et al. (1978) and Banker et al. (1984). The use of DEA in this study is appealing due to the fact that: DEA can easily accommodate both multi- ple inputs and outputs unlike the Stochastic Frontier production function; DEA does not require the imposition of a specific functional form on the model. This allows the tech- nological frontier to be constructed without imposing a parametric functional form on technology or deviations from it (inefficiencies); and it permits the construction of a sur- face over the data, which allows comparison of one production method (or best producer) with others, in terms of a performance index. There are three alternatives for measuring the productivity changes. These alternatives include: Fisher Index, Tornqvist Index and The Malmquist Index. Lovell (1996) remarked that given a set of panel data, one may use DEA-like linear programs and a Malmquist Total Factor Productivity (TFP) index to measure productivity change. The Malmquist approach does not require the assumption of efficient production, but instead identifies the ‘best-practice’ firms in every period, which gives an efficient production frontier, and measures each Decision Making Unit’s (DMU’s) output relative to the frontier. According to Grifell-Tatjé and Lovell (1996), the Malmquist index has some advan- tages relative to other productivity indices. For example, it does not require input prices or output prices, which makes it particularly useful in situations where prices are misrep- resented or non-existent. It also does not require the profit maximization or cost mini- mization assumption and hence makes it useful in situations where the objectives of pro- ducers differ, are unknown or not achieved. Färe et al. (1994) showed that the Malmquist productivity index can be decomposed into two components – technical efficiency change and technical change. The value of this decomposition is that it provides insight into the sources of productivity change. The main disadvantage of the Malmquist index is the necessity to compute distance functions. There are many different methods that could be 275Performance and productivity changes used to measure the distance function, which makes up the Malmquist productivity index. One of the more popular methods has been the DEA-like linear programming method suggested by Färe et al (1994). The Malmquist productivity index can be used to identify productivity differences between two firms or one firm over two-time periods by calculating the ratio of the dis- tances of each data point relative to a common technology. Given period t+1 technology as the reference technology, the Malmquist (output-orientated) TFP change index between period t (base period) and period t+1 can be written as: M (xt+1, yt+1,xt , yt) ={Dt (xt+1, yt+1) Dt+1 (xt+1, yt+1) / Dt (xt , yt) Dt+1 (xt, yt)}1/2 (1) where the notation D represents the distance function, x and y are inputs and outputs respectively, and the value of M is the Malmquist productivity index. A value of M greater than one (i.e. M >1) denotes productivity growth, while a value less than one (M<1) indi- cates productivity decline, and M=1 indicates no productivity change. This represents the productivity of the production point (xt+1, yt+1) relative to the production point (xt, yt). Calculation of the Malmquist index for adjacent periods includes four different dis- tance functions – Dt(yt, xt), Dt(yt+1, xt+1), Dt+1(yt, xt) and Dt+1(yt+1, xt+1). The function in equation (1) can further be broken down into its components: Efficiency Change = Dt+1 (xt+1, yt+1) / Dt (xt, yt) (2), and Technical Change = [(Dt (xt+1, yt+1) / Dt+1 (xt+1, yt+1) (Dt (xt , yt) / Dt+1 (xt, yt)]1/2 (3) The efficiency change in equation (2) represents the change of technical efficien- cy (EFFCH) between time t and t+1, which is the change in the relative distance of the observed production from the maximum potential production. The technical change (TECHCH) is the geometric mean of the two productivity indexes, representing shift in production technologies between time t and t+1. In addition, the technical efficiency change can be further broken down into: Pure Technical Efficiency = Dt+1 (xt+1, yt+1) / Dt (xt , yt) (4) Scale Efficiency Change = Dt+1(v) (xt+1, yt+1)/ Dt+1(c) (xt+1, yt+1) * Dt(v) (xt+1, yt+1)/ Dt(c) (xt+1, yt+1) 1/2 Dt+1(v) (xt, yt)/ Dt+1(c) (xt, yt) Dt(v) (xt, yt)/ Dt(c) (xt, yt) (5) The scale efficiency change component in equation (5) is actually the geometric mean of two scale efficiencies. The first is relative to the period t+1 technology and the second is relative to period t technology. The extra subscripts of v and c, relate to the VRS and CRS technologies, respectively. 276 M.A. Olasupo, C.A. Afolami, A.M. Shittu, A.A.A. Agboola 2.1 Study data and Sources This study took a census of all the 86 Microfinance Banks in Ogun, Oyo and Ondo States and observed their operation activities from 2006 to 2010. MFBs for this study were limited to Unit MFBs (MFBs with minimum capital requirement of N20 million) to create a fair platform to assess the operations of firms on a similar operational level. 2.2 Performance measurement using accounting ratios The performance indicators of the MFBs were measured around key operational indi- ces like portfolio quality, financial management, efficiency and productivity and also prof- itability and sustainability. There are many ratios used in banking and microfinance but this study will adopt ratios based on the toolkit referred to as “SEEP ratios”. SEEP (Small Enterprise Education and Promotion Network) has published a framework that advocates industry standard ratios for the monitoring of microfinance institutions in credit opera- tions. The framework builds on a consensus of practitioners, donors (including CGAP {Consultative Group to Assist the Poor}), evaluators and others in the microfinance indus- try (including The MIX {Microfinance Information Exchange. 2.3 Malmquist Productivity Index (MPI) There are many different methods that could be used to measure the distance func- tion, which makes up the Malmquist productivity index. In the empirical part of this study, following similar input and output choices by Martinez-Gonzalez (2008) in the esti- mation of the efficiency scores of MFIs, DEAP computer program was used to construct Malmquist indices using DEA-like methods (Coelli, Rao and Battese, 2005). Since the MFB’s objective is on achieving meaningful increase in outputs, within the context of a given level of inputs, the Malmquist (output-orientated) TFP change index between peri- od t (base period) and period t+1 can be written as: M (xt+1, yt+1,xt , yt) ={Dt (xt+1, yt+1) Dt+1 (xt+1, yt+1) / Dt (xt , yt) Dt+1 (xt, yt)}1/2 (6) where, M = Malmquist Productivity Index, and D = Distance function x and y = inputs and outputs respectively across time period t to t+1. where x1 = MFB’s operating expenses (N); x2 = MFB’s salaries and wages (N); y1 = MFB’s gross loan portfolio (N); y2 = MFB’s total savings. The choice of the output oriented Malmquist index was motivated by the underlying assumption that microfinance is all about service delivery whose primary objectives are better measured in terms of its output vis-à-vis outreach, financial sustainability and wel- fare impact. 277Performance and productivity changes 3. Results and discussion In general, the sampled MFBs total savings mobilized grew from N3.672 billion ($22.95 million) in 2006 to N4.720 billion ($29.50 million) in 2010, while women savings represented 63% and 57% of the total savings in 2006 and 2010 respectively. The quan- tum of loans sought by the MFBs’ clients was N3.877 billion ($24.231million) in 2006, it grew to N5.275 billion ($32.969 million) in 2008 and reached N7.298 billion ($45.612 mil- lion) in 2010. Credit gap (variance between loans applied for by beneficiaries and loan approved by the bank) of between 17% and 20% were observed over the study period. The MFBs outstanding loans as a percentage of loans disbursed was 21% in 2006, 22% in 2007, 21% in both 2008 and 2009, and 19% in 2010. The total annual loans disbursed to agricultural related activities grew marginally by 1% in 2007, but made significant leaps by recording growth figures of 20%, 21% and 5% in 2008, 2009 and 2010 respectively. The combined total assets of the sampled MFBs grew by 13% in 2007, 12% in 2008, 8% in 2009, and 7% in 2010. The combined total liabilities of the sampled MFBs rose by 11% in 2007, 12% in 2008, 8% in 2009 and 7% in 2010. 3.1 Performance Indicators for MFBs The study attempted to compare the ratios of the sampled MFBs with the global aver- age for MFIs reported by the Central Bank of Nigeria (CBN). However, it should be noted that the reported global average was aggregated for all countries irrespective of the degree of development of their microfinance sub-sector and hence it might show huge variance with the ratios obtained from the Nigerian Microfinance Sub-sector that is still at the infancy stage. 3.1.1 Portfolio at Risk (PAR) This is the outstanding principal amount of all loans that have at least one installment past due for one or more days. The amount includes the unpaid principal but excludes the accrued interest. It measures the potential for future losses based on the current perfor- mance of the portfolio. However, the average annual PAR of the sampled MFBs was 17%, 18%, 17%, 18% and 17% for 2006 to 2010 respectively. Only 16% of the sampled MFBs met the recommended maximum PAR value of 5% in 2006. The value dropped to 14% in 2007, further declined to 8% in 2008, slumped to 6% in 2009 and increased marginally to 7% in 2010. The high PAR value recorded by the MFBs might be due to inadequate loan tracking mechanism, weak loan recovery practices and the lack of institutional support to enforce loan repayment. 3.1.2 Portfolio to Assets This ratio measures how much of the asset base of the MFBs that are invested in high performing loan portfolio. The average annual portfolio to asset ratio of the sampled MFBs were 57%, 55%, 58%, 66% and 69% for 2006, 2007, 2008, 2009 and 2010 respective- ly. The study also revealed that 34% of the sampled MFBs had a portfolio to asset ratio of below 40% in 2006, the percentage of MFBs rose to 37% in 2007, slumped to 23% in 2008, 278 M.A. Olasupo, C.A. Afolami, A.M. Shittu, A.A.A. Agboola rose marginally to 26% in 2009 and crashed to 22% in 2010. The Nigeria Microfinance Sub-sector is still assumed to be at its infancy stage and following the learning curve prin- ciple of perfection through repeated trials, more MFBs are expected to have higher port- folio to asset ratio with time. 3.1.3 Debt to Equity Ratio (Leverage) Leverage reflects the MFBs capital strength at a point in time. It depicts the portion of equity and debt that the MFB uses to finance its assets. Increased debt becomes meaning- ful only if the resultant increase in earnings outweighs the cost of financing the debt. The study revealed that the annual average debt/equity ratios of the sampled MFBs were 2.65 in 2006, 2.21 in 2007, 2.20 in 2008, 2.15 in 2009 and 2.15 in 2010. The study also showed that only 31% of the sampled MFBs reported a debt/equity ratio of above 2 in 2006. The percentage of MFBs declined to 26% in 2007, rose to 29% in 2008, 30% in 2009 and 33% in 2010.The increasing trend from 2008 showed a better efficient matching of debts and equity by the MFBs and hence depicted a more efficient financial management system. 3.1.4 Cost per Client This ratio measures the quantum of the MFBs operating expenses (excluding the cost of funds or provisions for bad loans) that is required to serve a client. It connotes the expensive nature of the operations of the MFBs. The study showed that the sampled MFBs incurred an average of N4,214.17 ($26.36) per client in 2006, N4,350.00 ($27.19) in 2007, N4,863.95 ($30.40) in 2008, N4,560.07 ($28.50) in 2009 and N4,283.84($26.77) in 2010. This average cost per client is considered quite high as a significant number of the clients falls within the borrowers’ range of N5,000.00 to N50,000.00 ($31.25 to $310.25). This high cost per client ratio could adversely affect the MFBs efficiency and productivity. 3.1.5 Borrowers per Loan Officer It depicts the productivity of loan officers in serving the client caseload. The ratio is not expected to be too high as it might lead to client overload for each loan officer, result- ing in poor customer satisfaction, ineffective loan monitoring and high default rate. The study showed an annual borrowers/loan officer ratio of 232 in 2006, and it continually rose to 266 in 2007, 269 in 2008, 289 in 2009 and 313 in 2010. 3.1.6 Return on Assets (ROA) ROA depicts the management of the MFBs assets to maximize profit. It indicates the profitability of the MFBs before leverage. It measures the amount of profit the MFBs make per naira of its assets. The study revealed an average ROA value of 8% in 2006 (i.e the MFBs made an average of 7.81 kobo for each naira worth of asset. The average ROA value was 7%, 7%, 8% and 9% for 2007 to 2010 respectively. The high rate of returns on assets as com- pared to the global average could be adduced to the high interest rates charged by the MFBs. Due to the short duration of the credit facilities provided by the MFBs, most MFBs charge between 2% to 5% monthly on their credit facilities. However, the ROA is quite small com- pared to the average cost of capital that ranged between 18% and 22% over the study period. 279Performance and productivity changes 3.1.7 Return on Equity (ROE) It measures the rate of return on the shareholders’ equity of the MFBs. It shows the MFBs’ efficiency at generating profits from every unit of shareholders’ fund. The study reported annual average ROE value of 26% in 2006, 21% in 2007, 19% in 2008, 21% in 2009 and 24% in 2010. The study further revealed that 60% of the sampled MFBs had ROE ratio of above 15% in 2006, the valued declined to 57% in 2007, 56% in 2008 and 2009 and rose to 63% in 2010. Overall, the various ratios depicted an evolving sub-sector with enormous amount of potentials. The revelations from the sampled MFBs might not deviate much from the industry’s average and hence the Regulatory authorities must keep a tab on the activities of the MFBs through the formulation of policies that will create conducive environment for their growth. Table 1. Average Performance of Sampled MFBs (2006 to 2010) using Ratio Analysis. Year 2006 2007 2008 2009 2010 Mean Global average Portfolio at risk >30 days (%) 17.47 17.65 17.01 18.06 17.33 17.504 4.6 Portfolio/asset 57.4 55.21 58.14 65.96 69.03 61.148 NA Debt/equity 2.65 2.21 2.2 2.15 2.15 2.272 2.9 Cost per client (n) 4,214.17 4,350.00 4,863.95 4,560.07 4,283.84 4,454.406 NA Borrowers per loan officer 232 266 269 289 313 273.8 238 Returns to asset (%) 7.81 7.31 6.84 7.77 8.61 7.668 1.5 Returns to equity (%) 26.09 21.33 19.49 20.52 23.63 22.212 7.1 Source: Author’s Computation (2013). NA = Not available. 3.2 Malmquist Productivity Index As earlier stated, an attractive feature of the Malmquist index is that it decomposes into pure technical efficiency change and technological change. Table 2 summarized the decom- posed mean annual MPI or Total Factor Productivity (TFP) over the study period. The MPI is decomposed into technical efficiency change and technological change of period t+1 rela- tive to period t. The efficiency change is further divided into pure technical efficiency change and scale efficiency change (changes due to input-output combination efficiencies). The MFBs experienced fluctuating performances in their productivity changes. Table 2 revealed improvements in the MFBs pure technical efficiency of 1.006 and 1.01 in year 2006-07 and 2008-09 while they suffered deterioration in their pure technical efficiency with values of 0.91 and 0.834 in periods 2007-08 and 2009-10 respectively. However, there were improvements in their scale efficiency in years 2006-07, 2008-09 and 2009-10, while they only suffered scale efficiency deterioration in year 2007-08 with a value of 0.967. The MFBs suffered technological decline throughout the periods with values of 0.96, 0.985, 0.658 and 0.46 in years 2006-07, 2007-08, 2008-09 and 2009-10 respectively. This trend 280 M.A. Olasupo, C.A. Afolami, A.M. Shittu, A.A.A. Agboola is quite disturbing as the sharp declines in years 2008-09 and 2009-10 showed the MFBs are not leveraging on available technology to improve on their efficiency. Technological innovations will help simplify the operations of MFBs as they struggle to balance their operational objectives of outreach and financial sustainability. The observed technologi- cal decline from 2006 to 2010 corroborates the submissions of Oladejo and Olowookere (2011) and Moya Musa et al. (2012) on the poor deployment of technology among MFIs. Overall, the MFBs experienced Total Factor Productivity improvements only in year 2006- 07, while there were deteriorations in years 2007-08, 2008-09 and 2009-10. Figure 1 showed trend in mean annual technical and technological changes of the sampled MFBs and corroborated the earlier assertion that the MFBs had better techni- cal efficiency changes than their technological efficiency changes. It further underscores the relevance of technology in the modern business environment and MFBs should be encouraged to leverage on available technology to ease their operations and enhance their accounting and loan tracking proficiencies. Table 2. Summary of the Malmquist Productivity Index for the (2006 to 2010). Concept 06-07 07-08 08-09 09-10 Efficiency Change 1.142 0.88 1.445 1.661 Technological Change 0.96 0.985 0.658 0.46 Pure Efficiency Change 1.066 0.91 1.01 0.834 Scale Efficiency Change 1.071 0.967 1.431 1.993 Total Factor Productivity Change 1.097 0.867 0.951 0.764 Author’s Computation (2013): Figure 1. Trend in Mean Annual Technological (TECH) and Technical Changes (EFF) for MFBs (2006- 2010).   281Performance and productivity changes 4. Summary and conclusion In assessing the performance and productivity changes of MFBs in South-West Nige- ria as an indicator to the happenings in the Nigerian Microfinance sub-sector, the study noticed a steady growth in the operations of the MFBs but also revealed a lot of opportu- nities for improvements. The performance indicators of the MFBs using relevant ratios indicated gross incon- sistencies in the MFBs performance as benchmarked against global standards. Though the Nigerian Microfinance Sub-sector is still emerging, huge deviations from global stand- ards indicated the enormous effort required to mainstream MFBs towards best-practices. The study revealed an annual average PAR < 30 days of between 17.01% and 18.06% as compared to global PAR < 30 days value of 4.6%. PAR is crucial to the MFBs’ survival as it measures the potential for future losses based on the current performance of the loan portfolio. MFBs should be encouraged to tighten their loan tracking and recovery mech- anisms. Regulatory authorities could also assist the MFBs to establish enforce-able loan recovery systems. The annual average portfolio to assets ratio of the MFBs ranged from 55% to 69%. The MFBs reported an average leverage of 2.32, which though lower than the reported global average of 2.9 but very close to the 2.4 average reported for Africa. The average cost per client ratio of the MFBs was N4,454.41 ($27.84), a value perceived as being too high considering the fact that significant number of the clients still borrow between the N5,000 to N50,000 ($31.25 to $310.25) range. The return on assets (ROA) and return on equity (ROE) of the MFBs were quite impressive as compared with report- ed global averages but this could be highly connected to the high interest rates currently being charged for the services of the MFBs. The average interest rate among the sampled MFBs ranged from 3% to 6% per month. The Malmquist productivity index showed inconsistencies in the technical and tech- nological changes as the MFBs had more pronounced changes in their technical produc- tivity changes than their technological productivity changes. It was revealed that the MFBs had no technological productivity improvements as the MFBs experienced technological productivity decline throughout the study period of 2006 to 2010. This positive correla- tion between performance and technology amplifies the relevance of technology to the overall performance and sustainability of MFBs in Nigeria. In this age of information technology, it is expedient for MFBs to collaborate and evolve operational softwares that will ease their customer tracking, loan monitoring, operational performances and provides cost effective and efficient means of achieving their business objectives. MFBs should be encouraged to leverage on available technology and improve their service delivery for bet- ter efficiency and profitability. Overall, the MFBs had alternating advancements and dete- riorations across all forms of the constituents of their Total Factor Productivity Changes but had the best trend in their scale efficiency changes over the period. MFBs are advised to pay attention to each constituent of their Total Factor Productivity as advancements in some areas and deterioration in other areas will continue to hamper advancements in their overall TFP. 282 M.A. Olasupo, C.A. Afolami, A.M. Shittu, A.A.A. Agboola 5. Recommendation The study depicted the Nigerian Microfinance sub-sector as an emerging one with huge potentials to achieve its desired goals and objectives as an engine for sustainable eco- nomic growth and development. Based on the findings of this study, the following recom- mendations were made: 1. The high mean PAR ratio of 18% found in the study for the sampled MFBs portends great danger for the sub-sector. The CBN should establish a credit bureau for MFBs. This will aid MFBs effort in loan tracking and handling of default cases towards reducing their high Portfolio at Risk (PAR). Regulatory authorities should also insti- tute enforce-able loan recovery systems to mitigate against cases of deliberate default. 2. The Malmquist Productivity Index showed technological decline among the sam- pled MFBs over the study period. MFBs should invest in technology by leveraging on available business solution applications and also invest in research and development. Efficient use of IT will aid their customer profiling, loan monitoring and recovery and ultimately help reduce their PAR. 3. MFBs are critical to the success of the Financial Inclusion Policy of the CBN as they are closer to the financially excluded populace. The Central Bank of Nigeria (CBN) should invest in the development of robust operational softwares for the management information system (MIS) and operational efficiency of MFBs. Subsidizing the cost of acquisition to the MFBs will encourage them to adopt the use of information tech- nology in their operations as cost of acquisition could deter them from leveraging on relevant technological innovations. References Banker, R.D., Charnes, A., Cooper, W.W. (1984). 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