Good Money’ Chasing ‘Bad Money’: Implications for MFIs Management and Governance in Ghana – Microfinance in Africa

Good Money’ Chasing ‘Bad Money’: Implications for MFIs Management and Governance in Ghana - Microfinance in AfricaThe mix market (MIX) collects and validates financial, operational, product, client, and social performance data from MFIs in all regions of the developing world, standardizing the data for comparability. The information is made available    on MIX Market, a global, web-based, microfinance information platform, which features financial and social performance information for more than 1,900 MFIs as well as information about funders, networks, and service providers. Table 1 shows the performance of selected African MFIs that report on the MIX.
Across Africa, Ghana has the largest number (54 institutions) of MFIs that report on to the MIX market as of 2010. One interesting thing about the Ghanaian microfinance sector is that despite its highest number of institutions, total loans and deposits are far less than Kenya which has halve of the number of institutions in Ghana. The country with the least number of MFIs is Liberia. With the exception of Kenya, all MFIs have higher average loan sizes per borrower than average deposit per borrower. The implication is that default among clients could cause serious problems for MFIs because deposits cannot cover loans in times of default. Again, it is even not proper to use deposits to defray default loans.
The theoretical framework upon which this study is based is the agency theory. The theory posits that in the presence of information asymmetry, the agent (managers and board members) is likely to pursue interests that may hurt the principal (in this case the depositors whose monies are being used for on-lending and investors).

Information asymmetries are important in economic theory. Stiglitz and Weiss sparked a large theoretical literature on the role of asymmetric information in credit markets that has influenced economic policy and lending practice worldwide. Theories show that information frictions and ensuing credit market failures can create inefficiency at both the micro and the macro level, via underinvestment (Mankiw, 1986; Gale 1990; Banerjee & Newman, 1993; Hubbard 1998), overinvestment, or poverty traps (Mookherjee & Ray, 2002). In addition, when borrowers and lenders do not share common information, optimal financial contracts often involve agency costs, which are costs required in monitoring investment projects (Williamson, 1986; Bernanke & Gertler, 1989, 1990). While borrowers typically possess inside information about the investment projects, they have little incentive to disclose such information. Efforts made by a third party to obtain additional information are often costly. Furthermore, since lenders cannot distinguish between honest and dishonest borrowers prior to issuing loans, the incorporation of a lemons premium into the market interest rate discourages honest borrowers. Given that the necessary information is not available, credit rationing by way of limiting loan size arises in the market (Jaffee & Russell, 1976). As such, without proper information transfer, credit markets will perform poorly as loans are given to “wrong” borrowers while genuine borrowers with good characteristics may sometimes be turned down. Two main theories that information asymmetry produces are adverse selection and moral hazards which affect repayment rates among microfinance clients in the credit market. There are several reasons why clients default thus generating bad loans. Finance theorists’ view of access to credit exists due to adverse selection, moral hazard and contract enforcement problems can be used to explain why most clients default. Stiglitz and Weiss originated the adverse selection theory (AST) in which they explained why the interest rate could not equate the supply and demand in the credit market. As discussed by Stiglitz and Weiss borrowers have inside information about the nature of the project they want to finance and may reap substantial rewards from talking up their projects. Moreover, while the lender gains if the loan is repaid with interest, it is not a beneficiary of any upside gain in the client’s performance; it is, however, a victim of any downside losses in the case of default. Lenders, like MFIs, therefore face difficulties in discriminating between good and bad credit borrowers and simply increasing the price of credit to all potential borrowers can lead to adverse selection; rather than driving potential non-payers out of the market (Pollard, 2003).