Rural Remote Microfinance and Selfish Genes

The title to this document draws from the writings of Richard Dawkins on what he calls the selfish gene. The argument he puts forward is that certain genes survive over time through seemingly conscious adaptive behaviour. Some of the characteristics of selfish genes allow them to learn and create stable systems over time that survive. This paper argues that parallels can be drawn with respect to microfinance in rural areas where it is challenging for programs to survive in costly, unpredictable environments.

It is noted here that rural remote communities remain largely underserved except through informal mechanisms. In providing services financial institutions can expect high transaction costs, low rates of internal capital mobilisation due to poor physical infrastructure and a low density population making outreach expensive.

The paper argues that member-owned institutions have the potential to push the “rural frontier” into more remote areas because they are both self-replicating and adaptive. They are able to build on the best of local and most strategic of linked arrangements. In these ways, it is suggested, MOIs resemble selfish genes that are capable of surviving, creating stable systems in unpredictable environments. In order to survive they need to become part of the financial system.

The right mix of local and linked arrangements includes drawing from local social capital and governance as a strategy for many MOIs and linkages that may involve different types of second-tiers such as federations, apexes or clusters with varying levels of inter-governance. Linkages could also be more arms-length where it is mainly a source for borrowing and depositing surplus capital.

Following a discussion on member-owned institutions, remote rural access and the role of self-replication and adaptation, the paper analyses why the right mix of local and linked arrangements is matters to practitioners, donors and technical service providers and regulators. The paper concludes with the view that stable self-organising systems survive because they know how to learn.

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