Leveraging Big Data for Financial Inclusion: Opportunities and Risks

Big data is a powerful new resource in international development with the potential to transform every industry, from education and health to agriculture and biotechnology. This month, Philippe is moderating a plenary on Big Data-driven microfinance at the European Microfinance Week. The Microfinance Gateway caught up with him ahead of the event to get a preview of some of the topics that will be discussed around Big Data and its effects on the microfinance sector.

Gateway: Can you talk about the concept of “Big Data” in the financial inclusion context? What is it and how is it collected and used by microfinance institutions?

Philippe: Traditionally, financial service providers have relied on small data, such as credit scoring, for decision-making. This type of data is easily accessed and interpreted by humans without the need for complex technology solutions and algorithms.

Due to the widespread use of smart mobile devices and the internet, the digital footprint of humans has increased dramatically in recent years, creating large amounts of electronic data referred to as Big Data. As the volume and the complexity of data increases, powerful computing tools and algorithms are needed to analyze and interpret it.

In recent years, new software platforms, such as Hadoop, have been developed, increasing the speed and efficiency with which big data is processed. Such platforms are built on the “distributed computing” model, which means that the processing work is distributed across a network of thousands of computers to provide more processing power.

The insights acquired through big data can and will transform every aspect of the industry, by:

• Leading to better strategic business decisions;
• Helping financial service providers design customized products and services for their clients;
• Triggering acquisition of new clients;
• Facilitating cross-selling activities; and
• Lowering operating costs.

Big data analysis can also enable businesses to identify issues in real time, allowing them to recalculate risk portfolios within a short time span, as well as identify fraudulent behavior. This will help to increase access to financial services for the poor.

Today, there are many sources of data that microfinance institutions can use. They collect some of the data directly from clients themselves, but there are a number of other sources being used, including Google search terms, social media, business transactions and machine-to-machine data that are stored and processed by new software. These data can be bought, but they can also be obtained through partnership agreements with companies such as mobile operators, social networks, and internet or software companies.

The insights acquired through big data can and will transform every aspect of the industry.

Philippe Breul

Question 2: How is big data changing the microfinance industry?

Big Data is opening doors for financial technology (fintech) firms and other non-microfinance organizations to enter the microfinance sector. The new competition can have a positive impact on MFIs as it pushes them to innovate around “alternative” credit scoring models and to develop mobile-based savings and loan products that can be easily accessed by clients. For example, First Access and Finca have joined to create the world’s largest collaboration of fintech and microfinance.

Retail banks such as Kenya Commercial Bank (KCB) and the Commercial Bank of Africa (CBA) in Kenya have also entered the microfinance sector, launching mobile savings and loans products such as CBA’s M-Shwari, MoKash and M-Pawa, that reach millions of clients. Similarly, Airtel Ghana has recently partnered with Tiaxa and Fidelity Bank to launch a “nano loan” scheme.

Fintech firms are using existing information to provide new services such as savings, loans, and insurance through existing channels (mobile, agents) with quite impressive success so far. The low-hanging fruits for MFIs are about to disappear, representing an important risk for fragile and non-adaptive institutions.

In some cases, fintech firms are even buying MFIs. My Bucks, a Luxembourg-based fintech firm, bought six African MFIs from Opportunity International. The two respective CEOs will be present at the European Microfinance Week (EMW) and will certainly be at the center of attention for those wanting to better understand the rapid changes impacting the MFI industry.

Question 3: Some are worried that the microfinance sector is shifting its focus from its original objective of increasing financial inclusion to increasing profit. What is your advice for MFIs?

MFIs need to leverage digital technology better. Big data plays an important role in helping financial service providers to develop services tailored to client needs, and also to acquire new clients, facilitate cross-selling activities, and lower their operating costs. All these elements can lead to better social performance. Concrete examples of such developments will be presented by the service providers MFI Insights Analytics, INBOX, OpenCBS and ADFinance at the upcoming European Microfinance Week.

Unfortunately, the innovation capacity of most MFIs is limited, and often depends on social investors and development agencies who are just starting to develop their digital finance strategies. At the same time, MFIs are facing increased competition from retail banks and fintechs, which means that their capacity to adapt and innovate is critical in order to sustain their operations.

Question 4: What are the benefits and risks of big data for consumers?

Big Data can offer big benefits to consumers, with more convenient and affordable financial services that better meet their needs. But there are also several risks that arise from the increased use of big data.

One of the main risks for consumers is privacy. Data on people’s personal information, interests, and activities may be collected and used for analysis without their knowledge. Sensitive personal data, such as health information, can be at risk of being revealed publicly. Consumers may be denied loans from other financial institutions if data on late payments is made public without further information on the circumstances that led to the late payments.

Discrimination is another risk of Big Data, as consumers with similar characteristics may be grouped together and excluded from accessing financial products and services. This type of profiling can lead to the wrong people being included or the right people being excluded.

Question 5: What can countries do to ensure a responsible use of Big Data by the financial industry?

Countries need to establish laws to protect the privacy of consumers and avoid discrimination. This can be done by addressing the three paradoxes of Big Data:

1. Transparency: As personal data is collected without the knowledge of consumers, the use of such data becomes unethical and may lead consumers to feel insecure about it. Data must be collected and analyzed with transparency.
2. Identity: Big data analyzes “how” consumers behave, without considering the circumstances explaining “why” they behaved that way. Real life situations should be analyzed in addition to Big Data analysis to avoid discrimination based on demographics.
3. Power: Big data provides great insight into the needs of consumers so that financial service providers can better meet them. However, such insights are usually kept secret so that businesses can use them for commercial purposes, thus increasing their power over consumers. Countries need to ensure that the clients also have access to the data and can dispute inaccuracies as needed.