Zeroing in on the True Bottleneck: What Is Holding Digital Financial Inclusion Back?

The Decision Tree framework, developed by the Center for Global Development (CDG) in 2019, provides a tool to help identify the constraints affecting usage of digital financial services in a given country. Due to growing interest in the tool, CGD is now launching an online course on how to apply the Decision Tree framework. FinDev Gateway sat down with Liliana Rojas-Suarez of CGD to learn more.

FinDev Gateway: How did the Decision Tree methodology come about?

Liliana Rojas-Suarez: The Decision Tree framework emerged from a practical challenge: while many countries are pursuing ambitious strategies to increase their populations’ use of digital financial services, the outcomes have been mixed. Some have made significant progress, while others continue to lag behind. Although numerous factors can constrain financial inclusion, a key challenge for policymakers is diagnosing the country-specific root causes of these shortcomings and determining which actions to prioritize. That’s the gap the Decision Tree fills. 

Developed by the Center for Global Development in 2019, the framework offers a step-by-step method to identify the most critical obstacle, or “binding constraint,” hindering digital financial inclusion. Instead of rushing into solutions, the Decision Tree helps users ask the right questions and follow a logical process to zero in on the true bottleneck. This structured approach is especially valuable in settings with multiple issues, as it helps direct focus and resources where they can have the greatest impact-- bringing clarity to complexity.

FinDev: Can you tell us how this tool works, and who the target audience is?

Liliana: The Decision Tree is primarily designed for policymakers working on national strategies to boost financial inclusion. But it’s also a valuable tool for anyone interested in understanding or expanding access to digital financial services—whether you're a private sector provider, a researcher, or just a curious student. What makes it especially useful is its flexibility: it’s not tied to a specific country, region or data set, so it can be applied in many different contexts.

Think of it like a diagnostic test. The Decision Tree helps users work through a series of possible explanations for low digital financial inclusion, both on the demand and supply sides. It follows a top-down approach: starting with broad potential causes (the upper branches of the tree), then drilling down into more specific explanations (the lower branches).

For example, on the supply side, a lack of competition among service providers might be the main issue. But that, in turn, could be due to regulatory barriers or a market dominated by just a few players. On the demand side, people may see little value in using digital financial services—which could be caused by limited digital or financial literacy, or by social norms that restrict women’s access to financial tools.

The goal is to move from a long list of possible issues to the one that’s truly holding progress back—the “binding constraint.” It’s a structured process that promotes clear thinking and helps decision-makers prioritize what matters most.

Instead of rushing into solutions, the Decision Tree helps users ask the right questions and follow a logical process to zero in on the true bottleneck. 

 

FinDev: When you launched, you had five initial case studies (in Ethiopia, India, Indonesia, Mexico, and Pakistan) that were shared to showcase the use of this framework. Were there common constraints across countries, or was there wide variation between countries?

Liliana: We selected these five countries because they all have low levels of digital financial inclusion compared to others at similar degrees of development. These five countries alone roughly account for one billion adults who do not use digital financial services. Each country had their country-specific binding constraints, but one can also identify commonalities.

To illustrate, consider India and Ethiopia. In both countries, institutional deficiencies limiting the authorities’ willingness to deal with competition problems were identified as the binding constraint. However, each country also identified constraints severely affecting specific sectors of the population. In India, social norms that restrict women’s participation in financial decision-making emerged as a key issue. In Ethiopia, low awareness about digital services was identified as a central cause impacting low inclusion in rural areas. These examples highlight how the Decision Tree can uncover both common and country-specific binding constraints to financial inclusion.

FinDev: Now you are developing an online course in which people can learn how to apply the Decision Tree framework. Why did you see the need for this online course?

Liliana: We created the online course in response to growing interest from people who wanted to apply the Decision Tree in their own contexts, but who lacked a clear and accessible way to learn how. While workshops and technical assistance are valuable, their reach is limited. The online course opens the door for anyone, anywhere, to learn the methodology at their own pace. It’s designed to be accessible to a wide range of learners-- from government officials to students.

The course goes beyond theory. Learners can reinforce their understanding through optional hands-on activities and data-based exercises. What sets it apart, though, is its practical application: it can serve as a decision-making tool for policymakers. Through guided assignments, participants can apply the framework to a specific country or area of interest, making the learning process both relevant and actionable. Ultimately, our goal is for this course to become a trusted resource for anyone serious about tackling digital financial inclusion challenges in a thoughtful, evidence-based way.

FinDev: How can people sign up for this course?  

Liliana: Signing up is simple--the course is available for free on the Center for Global Development’s website and learning platform. No special background is required and participants can progress through the material at their own pace, with full flexibility to navigate the content as they choose.

FinDev: What are upcoming plans for further dissemination and application of this framework?

Liliana: To broaden the course’s reach, we’re collaborating with a range of partners to promote it across policy, development, and academic communities. Current and upcoming partnerships include the Gates Foundation, CGAP’s FinDev Gateway, the Alliance for Financial Inclusion, Toronto Centre, the Fletcher Leadership Program for Financial Inclusion (FLPFI), and Cambridge University’s Regulators Knowledge Exchange (RKE). As global interest in the course continues to grow, we anticipate expanding our network of partners even further.