nep-mfd New Economics Papers
on Microfinance
Issue of 2021‒01‒25
four papers chosen by
Olivier Dagnelie
Université de Caen

  1. Consumer Protection for Financial Inclusion in Low and Middle Income Countries: Bridging Regulator and Academic Perspectives By Seth Garz; Xavier Giné; Dean Karlan; Rafe Mazer; Caitlin Sanford; Jonathan Zinman
  2. The role of finance in inclusive human development in Africa revisited By Simplice A. Asongu; Rexon T. Nting
  3. Financial Inclusion: What Have We Learned So Far? What Do We Have to Learn? By Adolfo Barajas; Thorsten Beck; Mohammed Belhaj; Sami Ben Naceur
  4. Reducción de la brecha del crédito en México en un ambiente de incertidumbre generada por la pandemia COVID-19: Un enfoque de ciencia de datos (machine learning) By Rodríguez-García, Jair Hissarly; Venegas-Martínez, Francisco

  1. By: Seth Garz; Xavier Giné; Dean Karlan; Rafe Mazer; Caitlin Sanford; Jonathan Zinman
    Abstract: Markets for consumer financial services are growing rapidly in low and middle income countries and being transformed by digital technologies and platforms. With growth and change come concerns about protecting consumers from firm exploitation due to imperfect information and contracting as well as from their own decision-making limitations. We seek to bridge regulator and academic perspectives on these underlying sources of harm and five potential problems that can result: high and hidden prices, overindebtedness, post-contract exploitation, fraud, and discrimination. These potential problems span product markets old and new, and could impact micro- and macroeconomies alike. Yet there is little consensus on how to define, diagnose, or treat them. Evidence-based consumer financial protection will require substantial advances in theory and especially empirics, and we outline key areas for future research.
    JEL: D11 D12 D18 D81 D82 D83 D9 G21 K23 K31 K42 O12
    Date: 2020–12
  2. By: Simplice A. Asongu (Yaounde, Cameroon); Rexon T. Nting (University of Wales, London, UK)
    Abstract: This study investigates direct and indirect linkages between financial development and inclusive human development in data panels for African countries. It employs a battery of estimation techniques, notably: Two-Stage Least Squares, Fixed Effects, Generalized Method of Moments and Tobit regressions. The dependent variable is the inequality adjusted human development index. All dimensions of the Financial Development and Structure Database (FDSD) of the World Bank are considered. The main finding is that financial dynamics of depth, activity and size improve inclusive human development, whereas the inability of banks to transform mobilized deposits into credit for financial access negatively affects inclusive human development. Policies should be tailored to improve mechanisms by which credit facilities can be provided to both households and business operators. Surplus liquidity issues resulting from the inability of banks to transform mobilized deposits into credit can be resolved by enhancing the introduction of information sharing offices (like public credit registries and private credit bureaus) that would reduce information asymmetry between lenders and borrowers. This study complements the extant literature by assessing the nexus between financial development and inclusive human development in Africa.
    Keywords: Banking; human development; Africa
    JEL: E00 G20 I00 O10
    Date: 2021–01
  3. By: Adolfo Barajas; Thorsten Beck; Mohammed Belhaj; Sami Ben Naceur
    Abstract: The past two decades have seen a rapid increase in interest in financial inclusion, both from policymakers and researchers. This paper surveys the main findings from the literature, documenting the trends over time and gaps that have arisen across regions, income levels, and gender, among others. It points out that structural, as well as policy-related, factors, such as encouraging banking competition or channeling government payments through bank accounts, play an important role, and describes the potential macro and microeconomic benefits that can be derived from greater financial inclusion. It argues that policy should aim to identify and reduce frictions holding back financial inclusion, rather than targeting specific levels of inclusion. Finally, it suggests areas for future research.
    Keywords: Financial inclusion;Financial services;Credit;Banking;Mobile banking;WP,bank account,economic growth,incorporated firm,financial activity,household enterprise,loan officer
    Date: 2020–08–07
  4. By: Rodríguez-García, Jair Hissarly; Venegas-Martínez, Francisco
    Abstract: Resumen El otorgamiento de microcréditos de forma eficiente y transparente a través de plataformas digitales a individuos que desarrollan actividades económicas y que buscan mantener su empleo y el de sus trabajadores y que no tienen acceso al sistema financiero convencional es, sin duda, un problema urgente por resolver en la crisis sanitaria por la que atraviesa actualmente México. La presente investigación desarrolla varios modelos y estrategias de riesgo de crédito que permiten promover la inclusión crediticia en México de manera justa y sostenible en un ambiente de incertidumbre generada por los estragos presentes y esperados por la pandemia COVID-19. Para ello se utiliza el enfoque de ciencia de datos de machine learning, particularmente, se emplean las herramientas: regresión del árbol de decisión, bosques aleatorios, función de base radial, boosting, K-Nearest Neigbor (KNN) y Redes Neuronales. Abstract The efficient and transparent granting of microcredits through digital platforms to people who carry out economic activities and who seek to maintain their employment and that of their workers and who do not have access to the conventional financial system is, without a doubt, an urgent problem be solved in the health crisis that Mexico is going through. This research develops various credit risk models and strategies that allow promoting credit inclusion in Mexico in a fair and sustainable manner in an environment of uncertainty generated by the present and expected ravages of the COVID-19 pandemic. For this, the data science approach of machine learning is used, in particular, the used tools are: decision tree regression, random forests, radial basis function, boosting, K-Nearest Neigbor (KNN), and Neural Networks.
    Keywords: riesgo crédito, ciencia de datos, mercados de créditos, instituciones financieras, inclusión financiera. credit risk, data science, credit markets, financial institutions, financial inclusion.
    JEL: G23
    Date: 2021–01–04

This nep-mfd issue is ©2021 by Olivier Dagnelie. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.