Addressing Customer Needs? Off to the Data Mines

> Posted by Shaheen Hasan, Manager, FI2020 at CFI

The “customer centricity” mantra has become a common refrain among donors, policymakers, practitioners, and providers working on financial inclusion. Indeed we would be hard-pressed to find anyone working in the sector who wouldn’t identify him or herself as focused on customer needs. In the Addressing Customer Needs section of the Financial Inclusion 2020 Progress Report, however, we report that the number of financial service providers who are actually investing in and implementing these ideas at a scalable level are still few and far between. Although the truly customer-centric organizations are in the minority, we found a host of good examples, and we highlight some examples we like in the report.

A critical element of addressing customer needs is building the right consumer insights infrastructure to gather and translate data into better product offerings and the targeting of new market segments. Organizations use a multitude of methods to assemble insights. Some players, such as Equity Bank in Kenya and Tigo in multiple countries have built up in-house research capabilities. Banco Azteca in Mexico, for example, has one of the most sophisticated market research systems to amass and analyze information on customers. It has used that information to build up a clientele of millions of savers, borrowers, remittance receivers (and some senders), and insurance policy holders. Janalakshmi, an Indian microfinance institution, with the support of CGAP, developed a tool, Kaleido, which utilizes its front-line staff to get a “360 degree” view of a household, providing a rich source of data for developing new products as well as assessing the financial progress of a household.

With increasing availability of data on client behavior and new techniques to analyze that data, there is a rich wellspring to mine for insights relevant to market segmentation, product design, and delivery improvements.

Sophisticated data mining allows for analysis to draw from sources including mobile records, public data, online behaviors, spending transactions, and more to predict a consumer’s financial habits. Data analytics allow individualized responses to a given customer’s situation, whether for credit approval or for product offerings. One example is Tiaxa, which analyzes prepaid mobile airtime usage to offer short-term airtime credits. Cignifi (in Brazil, Ghana, Mexico, and Chile) and First Access (in Tanzania) analyze data to offer customer targeting and credit scoring services to financial service providers.

We also find a growing number of mobile money operators using transaction data to identify patterns of customer adoption and mobile money usage. This has allowed for better segmentation and refinements in product delivery and marketing to reduce churn, according to GSMA’s State of the Industry Report on Mobile Financial Services.

Many financial service providers already possess a treasure-trove of data. The challenge is to build or outsource the capability to analyze that data and to bring the insights back into operations.

For more details and examples, read the Financial Inclusion 2020 Progress Report.

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