An investigation of the credit scoring methods used by Zimbabwean financial institutions

Abstract

There has been a surge in the level of non-performing loans in the Zimbabwean economy as a result of the information asymmetry problem that leads to the adverse selection and moral hazard problems in the credit markets. The study sought to look into the types of credit scoring techniques used by Zimbabwean financial institutions. To obtain the empirical data, questionnaires were administered to loan officers, operations managers and general managers of 19 banking institutions. The study adopted a survey approach in the sense that all banking institutions were covered. Structured interview questions were used to collect data from the respondents. A qualitative research approach was used for the purposes of this research, and the data collected was analysed through the use of content analytical summary tables, statistics and frequencies. The study found that all financial institutions use statistical scoring techniques as compared to ancient and subjective judgmental scoring techniques. As a result, the scoring techniques used by Zimbabwean financial institutions are good and are in line with international best practice. However, the problem lies in the variables that are inputted into these “good” scoring models. The levels of borrower information sharing are very low in the Zimbabwean economy. The study results also agree with a similar survey that was performed by the World Bank in 2013, which gave Zimbabwe a rating of one out of a maximum possible six, on the level of information sharing between financial institutions. The study also found that due to the low levels of information sharing, the loan approval process was generally very slow in Zimbabwe as compared to other countries such as South Africa where some financial institutions approve a loan application within a matter of a few minutes. In light of these findings this study recommends that, policy makers accelerate the setting up of a Credit Referencing Bureau.