The “One Rupee trick” that recently caught the headlines in India provides an example of the unintended consequence of setting the wrong targets. With the best of intentions, the Indian government in 2014 launched an initiative to bring basic bank accounts to all. It mandated account-based targets for banks to deliver on this promise. This led to 240 million new bank accounts being opened since then.
However, it soon transpired that these accounts were not being used: the majority had zero balances, indicating that they were dormant. Just opening accounts was clearly not sufficient. So the focus shifted to measuring active accounts, defined as those with a non-zero balance. For a while it looked as if remarkable progress was being made: dormancy reduced dramatically. Here, finally, was a true financial inclusion success story.
But in reality, some bank managers had found a way to fool the system by simply depositing negligible amounts into accounts to make them appear active. It was discovered that more than 10 million accounts had only one Rupee in the balance. Though the targets were being met on paper, actual usage was non-existent and the account holders themselves were likely oblivious to what was happening in their accounts.
There are many lessons to be learned from this story. For us at the i2i facility, a resource centre based in South Africa that deepens understanding of financial inclusion through data, the story has demonstrated how critical the nuances of our measurement frameworks are. One of our objectives over the next few years is to work with governments and the broader financial inclusion community to develop measurement tools that better reflect our intentions.
To know what to measure, we must first own up to a common deception in financial inclusion: that financial services uptake is the objective. In fact, savings, credit, payments and insurance are roads, not destinations. We use them because we want to get somewhere, not because we want to travel. The real destination is the more fundamental needs that people must meet through financial services. These can include receiving income, buying groceries, paying for schooling or health care, buying stock for a business, or sending money to elderly parents, all of which, in turn, help you to live your daily economic life, be more resilient, or meet your financial goals.
A financial service such as a bank account may connect you to one or more of these destinations, but to do so it must be used. For example, in Indonesia, Findex data shows that seven out of ten bank accounts are dormant or used as a mailbox, whereby all income received into the account are cashed out in one single transaction. As with all those one-Rupee accounts, it is unlikely that the dormant bank accounts are meeting any of the financial needs noted above. And those used as a mailbox may only meet some of them. Where fees are incurred on such accounts, customer value may actually be eroded. Unused accounts are also not profitable for providers. So, if we set targets that incentivise the delivery of services to people who are not likely to need it – and will hence not use it – we are not achieving our end-goal, and, in some cases, may actually be making their financial lives worse.
Why are accounts not used? Does this mean that we have thus far been measuring the wrong things and, if so, what else should we prioritise?
To answer these questions we first need to know where we are and where we want to go.
For example, measuring the number of adults that use a formal financial service may indicate the breadth of the financial sector, but tells us little about how the financial sector is meeting the needs discussed above. If we broaden this to also include the depth of usage or the number and types of financial service these adults use, it tells us how responsive the financial sector is to needs. By considering both breadth and depth, we can more accurately identify where the development focus should be.
If the breadth of usage is low, providers should focus on improving the distribution infrastructure in a country, specifically payments to reach new consumers. If the breadth of usage is high, then providers should focus on targeting existing clients with a more comprehensive and tailored portfolio of financial services. We have found that this shift to depth typically happens when breadth reaches 50% in a country.
Whilst this is a very crude indicator, it already sharpens our measurement tools to allow a more targeted and sequenced policy response to help us get to where we want to go. Further, focusing on needs and unpacking people’s usage decisions can help to design discrete interventions for specific segments of the population. Just understanding that it is not useful to push full functionality bank accounts, or productive credit, to parts of the population that are unlikely to need – and hence use - it, already takes you a long way to knowing where to focus policy attention and resources.
Thinking about financial inclusion targets and measurement in this light opens up new possibilities. Our task now is posing and testing concrete hypotheses to unlock these possibilities, and to explore the potential of different data sources, including supply-side and transaction data, to answer these questions. Finding new metrics for financial inclusion is an ambitious agenda – but one which is within grasp if we work with the right partners.