December 2, 2016
Written by David Garrity
This post originally appeared on GVA Research.
Abstract
Disaster relief response has been characterized by the use of MFS as a vehicle for charitable donations, both directly from diaspora populations as well as campaigns organized by traditional relief organizations. The paper will develop a financial model and analysis of how scaling MFS can be commercially viable and sustainable. The analysis will assess the extent to which the deployment of MFS as a disaster risk mitigation measure may be enhanced by the provision of information on available risk profiles. The paper will assess the enabling environment for successful deployment of MFS as a mechanism for managing financial shocks in disaster relief and for mitigating individual risk. Statistical models have been developed using mobile network operator (MNO) call detail records (CDRs) to assess which subscribers may present better credit risks as well as how to best structure premium levels and payment methods to best fit subscribers’ abilities and needs. Based on such models and on the pricing structures of MFS, the paper will extrapolate from instances where farmers have secured insurance against weather-related crop failures and where MFS have been developed. The model will analyze available data on use of MFS as a risk-sharing mechanism, identifying the periods in which measurable increases occur in volume and amount of transfers. MFS adoption in developing countries follows a model in which remittances lead to the adoption of other MFS. The data overview indicates that the existence of established reciprocity and social networks drives volume and that establishment of trusted networks is critical to MFS achieving scale. Building on these findings, the analysis will identify enabling regulatory factors and will provide recommendations for various stakeholders. In conclusion, the analysis will examine how patterns of use of MFS provide an informational basis on which disaster risk reductioncan implemented in different form factors.
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