Dear RFILC members,

We would like to dedicate this edition of the newsletter to the topic of  FinTech (Financial Technology). FinTech companies combine technology with access to data to deliver new financial services and experiences to customers. Several of such innovations specifically focus on underserved, low-income, and remote customers. Yet for all the general excitement that FinTechs have generated in the global development community, there is still little information available about how specific FinTech innovations contribute to financial inclusion. A recent publication from the Consultative Group to Assist the Poor (CGAP) titled “Fintechs and Financial Inclusion: Looking past the hype and exploring their potential” provides a detailed overview of the linkages between Fintech and development, providing insights into whether these services: (i) work as stated; (ii) create value for underserved customers; and (iii) ease age-old pain points in delivering financial services to underserved customers. Based on the work carried out with 18 FinTech pilot experiences in Africa and South Asia, the paper also highlights the challenges faced by early-stage FinTech companies that inhibit their ability to impact financial inclusion in those regions.

The second highlight is a publication developed by the International Monetary Fund (IMF) titled “FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk”. Recent advances in digital technology and big data have allowed FinTech lending to emerge as a potentially promising solution to reduce the cost of providing financial products and services that can contribute to increasing financial inclusion. At the same time, there are associated technical complexities that many institutions need to understand, machine learning (ML) methods that lie at the heart of FinTech credit have remained largely a black box for the non-technical audience. This paper explains potential strengths and weaknesses of ML-based credit assessment; presents core ideas and the most common techniques in ML for the nontechnical audience; and discusses fundamental challenges related to ML-based credit risk analysis.

The third highlight of this month is the World Bank’s 16th Overview Course of Financial Sector Issues: Financial Systems in the Era of Data and Technology, which will take place in Washington, DC, United States at the Preston Auditorium of the World Bank Group Headquarters, from June 24 to June 28 of this year. This week-long course aims to provide a solid knowledge of the fundamentals of the financial sector and an opportunity to learn about the latest thinking in key areas. Throughout the training, participants will be able to hear the views of leading financial experts both on the more traditional applications of financial instruments, as well as on how big data and new financial technologies are reshaping finance all over the world.

Finally, we would like to remind you that the 5th Edition of the Boulder Rural and Agricultural Finance Program (RAFP) will take place this year in Turin, Italy, at the International Training Centre of the International Labour Organisation (ITC-ILO), from July 22 to August 2. Jointly developed by the Improving Capcity Building in Rural Finance (CABFIN) Partnership and the Boulder Institute of Microfinance, the program provides highly specialized training on rural and agricultural finance to experienced practitioners and institutions. The two week-immersion program offers a range of eight elective courses to choose from, for a total of 70 academic course hours. Please click here to register.

With best regards,
The RFILC editorial team