The Role of Data Science in Financial Inclusion

Eric Schmidt, the former Google CEO revealed that every two days we generate as much information as we did from the dawn of civilization up until 2003 — that’s an estimated 5 exabyte of data every 48 hours. Most of the new data sources according to Eric Schmidt emanate from user-generated content in the form of instant messages, tweets, photos et cetera. As a result, global companies and organizations now have additional data on customers at their disposal — the challenge presented has been on utilizing the external data to generate actionable insights and discoveries that can drive growth.

Hence data science was born — this new discipline draws techniques from statistics, computer science and machine learning to provide superior analytic capabilities that allow for processing and manipulation of unstructured data. In East Africa, financial companies are utilizing data science to solve the problem of thin file clients. Two companies (Tala and Branch) are pioneering the use of Facebook profiles in scoring the creditworthiness of the unbanked population in Kenya and Tanzania.

Branch gathers an average of 10,000 data points for every user, understands who pays their bills on time, who uses capital wisely and where their sales come from. This has seen about $1.5 million disbursed to individuals and businesses with an 85 percent repayment rate in Kenya on 40,000 loans, and a 92 percent repeat rate. In addition, Branch has a simple SMS tool that allows individuals in the informal economy to perform daily money management and receive a formal financial identity.

Data science has significantly driven down the cost of providing financial services to low income earners by automating data capture processes and leveraging on algorithms to perform complex evaluation done by financial experts. In addition, these services are delivered through low cost avenues such as SMS, which is readily available. One such example is the use of gamification on SMS to deliver insurance to the least financially served people in the world. This works by setting up an interactive SMS based Q&A in which the cost of sending SMS contributes to a user’s insurance premium.

The rich SMS interaction data provides supplementary user information such as asset ownership, financial literacy, risk appetite, and propensity to take up financial products. Arifu, an ed-tech company based in Nairobi, Kenya is utilizing SMS conversations to provide financial training to their users. Data science provides endless possibilities in solving financial inclusion problems as computing becomes cheaper and data becomes abundant.