System dynamics to turnaround an Indian microfinance institution

Abstract

Purpose – The purpose of this paper is to present a policy comparison tool for Indian Microfinance Institutions (MFIs) so that they can choose the best policy for implementation. It provides for turnaround of a troubled MFI by analyzing the performance of different policies. Design/methodology/approach – The paper has done a web survey to identify the need of a strategic tool for MFI. It has built a Decision Support System (DSS) using system dynamics. A corporate model of MFI has been constructed using iThink 10.0.2 software. A quantitative validity test has been done to find the robustness of the model. Finally four policies are tested and the performance indicators have been used to suggest the best policy. Apart from this DSS is used to test the implementation range of a policy. Findings – “Integration of Microfinance with country’s mainstream financial system along with provisioning 1 percent of outstanding loans” is recommended for the MFI as this will increase the financial performance. Research limitations/implications – In its present form the corporate model developed for MFI is not applicable for judging social performance. Therefore MFIs might be sceptic toward it. However, incorporation of certain performance indicators such as financial-self-sufficiency ratio might help in overcoming this reluctance. Practical implications – “Integration of Microfinance with country’s mainstream financial system along with restricting provision” will generate better performance for the MFI. Therefore this policy should be implemented by the MFI. There are other considerations which need to be taken into account while implementing this policy. The integration may require outsourcing of certain operations to banks, utilization of bank branches to disseminate knowledge related to the conduct of transactions, usage of customized bank software to handle the day-to-day business, development of new softwares for mobile messaging to help poor customers avail of schemes run by the banks, fill loan application forms online, send reminders for loan recovery; provide incentives such as upgradation of poor customers to become regular customers of banks. Social implications – By improving the health of the MFI a bigger goal to reach the poor will be achieved in the long run. The MFI has around five million clients at present and if the company becomes insolvent then the future of these clients is going to be impacted. The organization has interacted closely with these clients and therefore knows how to upgrade their financial state. Originality/value – The tool is first of its kind in the microfinance industry. So far the microfinance technology providers have dealt with Management Information System and Information and Communication Technology. The tool has been built to present a quantitative model for overall operations of the MFI. The simulation of this model helps in predicting future scenarios.