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> Posted by Ignacio Mas, Independent Consultant
Too much of post-microcredit financial inclusion still operates as a numbers game. We declare victors and write up successes based on headline customer acquisition rates, without looking much at underlying usage patterns. We continue to quote customer uptake or account registration numbers when providers give us nothing else to go by. We declare customers active and ourselves satisfied when customers use the service once every 1-3 months – can you imagine the education, electricity, water and sanitation people doing that? We judge customer relevance by scrutinizing average per-customer transaction volumes and sizes, even though those are usually driven entirely by the top ten percent of the distribution. If we looked deeper, we would find that many of those who are deemed to be underbanked are actually irrelevantly banked.
Glossing over usage data is a symptom that we are an industry which thrives on hype, an almost inevitable consequence when you mix a commendable spirit of do-goodism, deep donor pockets, and insatiable social media platforms. But it also has a lot to do with the fact that we actually know very little about what drives customer usage and value of formal financial services, beyond the occasional loan and remote payment.
Especially in the savings space, we are lacking an overall perspective on how to tackle the problem of relevance. We feel we need data, so we engage researchers to run excruciatingly detailed financial diaries, quantitative surveys, and randomized control trials. We feel we need product ideas, so we hire consultants to tell us what is successful elsewhere, though alas that is generally based on those awkward headline customer acquisition numbers. We feel we need processes, so we engage branded designers to run innovative rapid prototyping exercises. But it feels difficult to make all this come together purposefully.
A more structured approach would be based on formulating some key questions which can help sharpen our focus and narrow the solution search space. Let me propose three such questions, again focused on savings: Read the rest of this entry »
> Posted by Jeffrey Riecke, Communications Associate, CFI
Accurately assessing financial inclusion levels is fundamental for guiding inclusion efforts, but doing so on a large scale remains an issue, in spite of a growing supply of data and resources. A new composite index from the International Monetary Fund aims to change this. The new tool incorporates multiple inclusion dimensions and advanced methodologies, creating the ability to generate easily comparable inclusion calculations at the country, region, income, or even operational level.
ATM, Bangkok, Thailand
The new index addresses criticisms of previous financial inclusion indices, particularly the inability to accurately incorporate multiple financial inclusion dimensions into one tool. The index was built using data from IMF’s Financial Access Survey and from the World Bank’s World Development Indicators dataset. Released late last month, along with the tool, the IMF published the results of running the index using the country information included in IMF’s dataset for 2009 to 2012.
The index is based on a definition of financial inclusion that incorporates the dimensions of outreach, usage, and quality of financial services. To capture outreach, the index employs the variables of number of ATMs and financial institutions per landmass or adult population. According to the World Bank Global Findex, out of the 2.5 billion people who are excluded from formal financial services, 20 percent cite physical distance from the point of service as the main reason for not having an account. For usage, the index incorporates the variables of percentage of adults with at least one type of regulated deposit account, and percentage of adults with at least one type of regulated loan account. Although the IMF recognizes services quality as cornerstone to inclusion, they indicate there is not yet ample data to enable its incorporation in the index. However, expanding the index in future iterations to include quality is indicated as a possibility.
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