Reaching the underbanked with products that lead to future growth and revenue for financial institutions is about more than developing innovative solutions and managing costs. It’s about having a deeper understanding of what financial products underbanked consumers and small businesses need and want. It’s about the data.

Promoting financial services for the world’s 3 billion financially underserved represents meaningful social progress, but it’s also good business. A recent study by Accenture found that financial institutions could add $380 billion in revenue by extending financial services to the world’s economically excluded. The end result of more effective financial inclusion efforts could be $4.2 trillion added to the global economy, according to McKinsey Global Institute and the Bill & Melinda Gates Foundation.

Financial providers are increasingly moving their financial inclusion work out of their corporate social responsibility portfolios and into core business areas. That is good news. But as they make this move, they should consider the value of data in making this strategic shift. Success requires more than just cost-cutting. It will be based on the ability to know the right product to offer the right client, at the right time.

Big data can expand financial institutions’ ability to reach underserved customers in ways that are profitable and cost-efficient, and therefore allow access for the financially excluded into the banking system.Adobe StockIn past and some current attempts to reach this market segment, companies had relied on high-touch, manual processes to evaluate prospective clients. But data democratizes access to underbanked customers.

In 2015, Omidyar reported that big data could help up to 580 million people gain access to formal credit for the first time. Transaction histories, behavioral patterns and a wealth of other information — which had previously gone unrecorded due to the informal, cash-based nature of business activities at the base of the pyramid — are now increasingly available to companies for analysis. Even microfinance institutions (MFIs) are making use of that information to better serve their clients and themselves — by cutting costs, improving operations and designing better products. Data can help commercial banks make a strategic shift downstream, compete for MFIs’ customer base, and serve more underbanked consumers and small businesses.

The most valuable asset a large, commercial bank can leverage for social good is likely the data it already has and additional data it can acquire with relative ease. We recently published research into the ways that nearly 60 financial services providers from around the world are using data to improve operations and extend financial services to the underserved; in many instances, these innovators are teaming up with commercial banks and using “alternative” data or new business models to enhance lenders’ assessments of current and prospective clients’ creditworthiness and risk profiles, and streamline customer acquisition.

While data itself is valuable, equally if not more important is the capacity to act on that data, by having the right people, systems and strategy in place. Commercial banks tend to have more capacity in these areas than MFIs or traditional financial inclusion players. Companies can use a “data readiness assessment” to measure their capacity to use data to drive innovation.

This can be a long process but companies often have data tools already at their disposal that they are not utilizing. As Paulo Marques of Capgemini put it, “Data is a journey where you’re heading towards the unknown. So, you have to start with the known.”

For instance, financial service providers could link insights gained from programs seemingly unrelated to business operations to help improve business performance. One Accion partner offered financial literacy classes with exams for loan applicants. Those exams scores were never intended as a part of assessments. But once the scores were digitized, the company discovered that exam results were highly predictive of loan default rates. Many commercial banks offer similar financial literacy programs as part of their community outreach, and could similarly use the insights gained from program participation to help target customer acquisition and improve product design to benefit banks and their clients.

Another way for lenders to use data to identify and reliably work with underserved market segments is to explore “micro, small, and medium enterprise” financing. MSMEs contribute significantly to job creation in both emerging and developed markets, yet more than 50% of these enterprises lack access to finance, hindering their growth and economic contribution. But apart from being a progressive mission, providing MSMEs with the financing they need is also a potentially lucrative one: In emerging markets alone, entrepreneurs face a $2.6 trillion financing gap. Meeting that need affordably and working with underserved businesses could unlock a significant new market.

New lenders are finding ways to use data to inform and improve customer acquisition, underwriting and funding, to identify and reliably work with more clients by overcoming information asymmetries to offer all entrepreneurs an equal opportunity to succeed.

Unlocking the promise of big data to promote financial inclusion will expedite the ability of businesses to provide high-quality financial services to billions of new customers.

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