Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/18222
Title: Default risk and debt recovery strategies of microfinance providers: A comparative study in Sri Lanka.
Authors: Kalpani, B. L. W.
Abeysekera, R.
Keywords: Case study method
Debt recovery strategies
Default risk
Microfinance
Issue Date: 2017
Publisher: International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka.
Citation: Kalpani, B. L. W., and Abeysekera, R. (2017). Default risk and debt recovery strategies of microfinance providers: A comparative study in Sri Lanka. International Research Symposium on Pure and Applied Sciences, 2017 Faculty of Science, University of Kelaniya, Sri Lanka.p.135.
Abstract: The objective of this research is to identify and compare strategies used by six different Microfinance Institutions (MFIS) in Sri Lanka in order to minimize the risk of loan default and to recover debt. It also evaluates the effectiveness of the debt recovery strategies. According to Fitch ratings, over exposure to microfinance at Sri Lankan non-bank financial institutions (NBFIs) could pose risk to their credit profiles. The exposure among Fitch-rated NBFIs stood at just 4% of total loans of these entities as recently as March 2014, but this had increased to 27% by December 2015. The case study method used in this study is motivated by the need to understand the strategies that the MFIs are adopting to deal with the issues of non-performing loans in their portfolios. In this research, the conceptualized model has been developed to form the basis and it has been modified according to the Sri Lankan context covering MFI’s categorization. The model has been developed with a comprehensive review of the literature. MFIs will be mainly categorized on the basis of ownership. Then, it will be further subcategorized under the basis of non-profit or profit organizations. Further, it will be filtered according to the mentioned Portfolio at Risk (PAR) classification. Lending method will also be a part of filtering the institutions since it also affects the recovery strategy formulation. The data will be gathered primarily based on in-depth interviews. The findings contributes to both the knowledge domain and the practical domain.
URI: http://repository.kln.ac.lk/handle/123456789/18222
Appears in Collections:IRSPAS 2017

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