Why do Data Initiatives for Financial Inclusion Fail?




Why do Data Initiatives for Financial Inclusion Fail?


Data has taken centre stage in debates about the future of development. An area where data has been heavily mooted as a key solution is financial inclusion. Here are three key reasons why data projects in that sector fail.


#1 Data isn’t an important Barrier in the first place


A well-designed data intervention doesn’t always lead to improved financial inclusion. Data is just one piece of a complex puzzle. Data Interventions can provide data to market actors BUT may not increase financial inclusion if other things are not working well.


There are many reasons why fintechs don’t access early-stage funding. Regulations on investments; Investor risk appetite; Fintechs’ readiness for investment; etc. These reasons mean that even with sufficient data, capital supply won’t increase.

There are many reasons why fintechs don’t develop solutions for financial inclusion; Weak digital infrastructure, weak business skills, lack of incentives to serve low-income population, etc. This means that, even with sufficient capital, financial inclusion won’t always increase, and improving data flows might not lead to improved financial inclusion.


#2 If data is an important barrier, the Initiative doesn’t properly identify all the behaviours that need to change in order to utilise that data


Improved quality or availability of data doesn’t guarantee a successful intervention. For data to generate change, a variety of actors - beyond the data provider - need to change their behaviours. Data availability requires several behaviours beyond just providing the data – including developing a terminology, collecting, validating, analysing, storing and presenting data. These different behaviours can be performed by a range of actors but all need to be performed by someone. Even when the data is available, other actors need to respond; either by seeking this data, to decide to pay for this data to be collected, validated, provided, etc., and ultimately to act upon the data. When interventions focus only the supply side it leads to unsustainable data sitting on a metaphorical shelf. For the right data to be provided and to lead to improved financial inclusion, the intervention needs to consider the behaviours of actors well beyond the data provider.


#3 The initiative doesn’t factor in actors’ incentives to change behaviours in the long run


Even if the intervention focuses on relevant data and identify what’s different actors need to do in order to benefit from it, all too often, interventions aren’t designed in a way that responds to the actors’ incentives to do so.

Interventions tend to assume, often erroneously, that actors will actively seek, share and use data. Public and private actors are driven by various types of incentives. Their incentives must be sufficiently strong to adopt new behaviours, but their incentives are not always aligned with the behaviours needed to seek, share and/or use data. For instance, why would Financial Service Providers use data on rural households if they do not consider them as worthy clients? Finally, for data interventions to be sustainable, these incentives need to remain over the long term, for actors to maintain the necessary behaviours after donor funding has ended.

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If this piece has whet your appetite for more in depth analysis on this topic, then check out this CGAP publication to which Agora contributed.