  Inspired by recent ideas on how the analysis of complex financial risks can
benefit from analogies with independent research areas, we propose an
unorthodox framework for mapping microfinance credit risk---a major obstacle to
the sustainability of lenders outreaching to the poor. Specifically, using the
elements of network theory, we constructed an agent-based model that obeys the
stylised rules of microfinance industry. We found that in a deteriorating
economic environment confounded with adverse selection, a form of latent moral
hazard may cause a regime shift from a high to a low loan repayment
probability. An after-the-fact recovery, when possible, required the economic
environment to improve beyond that which led to the shift in the first place.
These findings suggest a small set of measurable quantities for mapping
microfinance credit risk and, consequently, for balancing the requirements to
reasonably price loans and to operate on a fully self-financed basis. We
illustrate how the proposed mapping works using a 10-year monthly data set from
one of the best-known microfinance representatives, Grameen Bank in Bangladesh.
Finally, we discuss an entirely new perspective for managing microfinance
credit risk based on enticing spontaneous cooperation by building social
capital.
