Discover "A Secret Worth Learning" About Data and Financial Inclusion >


In the recent New York Times article, "How Companies Learn your Secrets," Charles Duhigg discusses how companies can use demographics and data on personal consumption behavior to manipulate shopping habits and attract new customers. Target, for example, can predict if a customer is pregnant, what trimester she is in, and, with this information, target baby-related advertisements to her. For many consumers, this use of “big data” (very large and complex data sets and the analytics to mine them), seems like an unacceptable intrusion of privacy. For many of us working in microfinance and development, this concept produces a reflexive “Eewww,” probably because our goals are much less about directing consumption through marketing than they are about increasing the opportunity and capacity to consume.

Despite this initial reaction to the manipulation of customer data to drive profits, the use of big data can actually prove very effective for the fields of microfinance and financial inclusion. At Grameen Foundation, we strive to: 1) examine large datasets to find relevant patterns and leverage opportunities, and 2) build tools and systems that use data to enable the poor to improve their quality of life.
Here are three examples of how we use data in our work at Grameen Foundation:

  1. Understanding who our clients are: Our data is often analyzed in ways that can predict and identify households in different levels of poverty. Duhigg’s article describes a process where Target’s computers crawl through data to segment customers by the products they purchase. He was able to identify about 25 products that, when analyzed together, allowed him to assign each shopper a “pregnancy prediction score.” This is very similar to the process we use to build the Progress out of Poverty Index® (PPI®). We take income and consumption data from each country and boil it down to 10 of the most predictive indicators of poverty. With this information, a pro-poor organization can apply those indicators to a household to get a likelihood factor of that household being poor. This enables the organizations to design and test products and services explicitly for specific levels of poverty.
  2. Designing financial products using our client level insights: We can use big data to analyze how poor households access and utilize financial services, and then provide them with improved products to empower them to be more productive economic players. CARD Bank, a major microfinance provider in the Philippines, uses the PPI to know how well it is meeting its mission to reach poor households. Grameen Foundation has been actively working with CARD on designing and delivering savings services. Because we had segmented the clients by poverty levels, we were able to calculate that when we dropped the minimum opening balance from $25 to $2.50, we increased poverty outreach by six percentage points. We also know how much people at the $1.25/day and $2.50/day income lines are saving – and can use that as a starting point for strengthening products even further.
  3. Delivering information that helps clients make better choices: Big data also helped us to understand that a group of smallholder farmers we were working with are the poorest of the poor (or those living on less than $1.25/day PPP) and that their place in the value/supply chain was being undervalued. These farmers are not getting a fair share of the revenue that should accompany the service they provide. We believe the reason is that they are missing critical information – specifically, information about market prices, how to improve the quality of the crop and the yield, and how to aggregate crop yields from multiple smallholder farmers in order to open them to new, larger markets. We believe that providing this data to farmers will allow them to make informed decisions about their livelihood. So far it seems to be working. Farmers tell us the service is useful. More empirically, the data shows that the farmers are acting on the information they receive. Data analysis can also be utilized to understand how often and how deeply farmers are using information services so that we can continuously improve the process.

Though the use of big data by corporations (especially as described in the Duhigg article) may make us uncomfortable, there are important ways that the world of international development can harness its power to ensure that the products we deliver to poor households are effective and actually provide clients with the opportunities they need to improve their quality of life. And that’s a secret worth learning!

To learn more about how big data and the science of habit are being used to transform businesses and communities, check out Charles Duhigg’s recently published book, “The Power of Habit.”

To learn more about microfinance and financial inclusion, visit The Center for Financial Inclusion at ACCION International.

This posting written by Steve Wright, Director, Social Performance Management Center, Grameen Foundation, and Kate Griffin, Director, Solutions for the Poorest, Grameen Foundation.