Foreign Exchange and Disaster Risk Management in Microfinance Institutions

Master's Thesis from the year 2008 in the subject Business economics - Banking Stock Exchanges Insurance Accounting grade: 100 Wiesbaden University of Applied Sciences course: International Finance language: English abstract: Microfinance Institutions (MFI) have left the role of altruistic instruments for donor-assistance and turned into profitable financial institutions and interesting investment opportunities for international financial investors. However well-intentioned investments can dramatically increase a MFIs risk exposure and institutions without proper risk management can easily be forced into closure in the aftermath of environmental or economical distress. Moreover MFIs operate predominant in developing countries counting for 94% of all natural disasters worldwide and the vulnerability of their clients is exorbitant high due to their establishment in simple accommodation facilities and the strong dependence on agricultural business. Foreign exchange and disaster risks are considered to be two of the most jeopardising threats for MFIs characterised by close interrelations and ignored by the majority of institutions investors and credit users. This work compiles a holistic risk management approach starting with the sound assessment of foreign exchange and disaster risks with the aid of modern tools such as hazard modelling and the value-at-risk model. Based on the institutions particular risk-bearing capacity different strategies to minimise and transfer these risks have been evaluated. More than twenty methods from operational hedges to innovative instruments like indexed weather derivatives or currency and catastrophe swaps are investigated concerning their availability applicability effectiveness and efficiency in the microfinance context. Furthermore this work seeks to design the strategies in a way that overcomes particular obstacles like the Samaritans dilemma to create sustainable security along with rising self responsibi