Although theory suggests that financial market imperfections-mainly information asymmetries, market segmentation and transaction costs-prevent poor people from escaping poverty by limiting their access to formal financial services, new financial technologies (FinTech) are seen as key enablers of financial inclusion. Indeed, the UN 2030 Agenda for Sustainable Development (UN-2030-ASD) and the G20 High-Level Principles for Digital Financial Inclusion (G20-HLP-DFI) highlight the importance of harnessing the potential of FinTech to reduce financial exclusion and income inequality. This paper investigates the interrelationship between FinTech, financial inclusion and income inequality for a panel of 140 countries using the Global Findex waves of survey data for 2011, 2014 and 2017. We posit that FinTech affects inequality directly and indirectly through financial inclusion. We invoke quantile regression analysis to investigate whether such effects differ across countries with different levels of income inequality. We uncover new evidence that financial inclusion is a key channel through which FinTech reduces income inequality. We also find that while financial inclusion significantly reduces inequality at all quantiles of the inequality distribution, these effects are primarily associated with higher-income countries. Overall, our results support the aspirations of the UN-2030-ASD and G20-HLP-DFI. Highlights • Harnessing the potential of FinTech to reduce financial exclusion and income inequality has been proposed by the UN and G20. • We posit that FinTech affects income inequality directly and indirectly through financial inclusion. • We invoke quantile regression analysis to investigate whether the effects of FinTech differ across countries with different levels of income inequality. • We find that financial inclusion is a key channel through which FinTech reduces income inequality, at all quantile levels, primarily among higher-income countries.

We develop a theory linking financial inclusion, defined as access to formal loans and financial assets, to income inequality. Initial inequality of households is modeled by a random variable determining initial endowments. These initial endowments can be used to invest instantaneously in human capital and financial assets. Human capital translates into income based on a strictly concave production function, suggesting optimal levels of investment. Financial assets earn yields which do not depend on the amount invested by individuals. Theoretical predictions are tested using the China Household Finance Survey (CHFS) for 2011 and 2013. Initial conditions modeled by a random variable are replaced by an actual distribution of income or assets to derive theoretical predictions regarding the proportion of the population that might benefit from financial inclusion. Financial inclusion does mitigate under-investment in education-but formal loans do not contribute. Income inequality worsens if households rely on formal or informal loans, whereas access to bank accounts improves households' prospects in the future income distribution. However, households below the 40th percentile of household income do benefit from informal loans.

This study re‐examines the construct of financial inclusion, through a literature review and confirmatory factor analysis (CFA). First, we conduct a systematic review of definitions, measures and data sources. Second, we apply CFA to test two prominent financial inclusion indices. The CFA analysis reveals a high correlation between the ‘access’ and ‘use’ dimensions; hence, indices fail to capture the multidimensionality of financial inclusion. Existing indices tend to be biased towards measuring the supply‐side and quantitative aspects of financial inclusion. The extent to which lower income individuals and smaller firms have been incorporated into the formal financial sector is not captured.

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