Chapter-16: Agri-Fintech and Financial Inclusion: Evidence from Cross-Country, Agribusiness, and Indian Household Microdata, 2010–2024

This paper proposes a cross-country and in-country empirical research about Agri-FinTech and financial inclusion. The review is based on four unrelated microdata sets. The former is country-year data of the World Bank Global Findex Database with the six waves of surveys conducted 2011-2024. The second is microdata on agribusiness level of the Millennium Challenge Corporation Agribusiness Development Activity (ADA) impact evaluation in Georgia (201011). The third is household-level India-specific household-level files Periodic Labour Force Survey 202324 and National Sample Survey 70-Round, Land and Livestock Holdings Survey 2013. The fourth is three more Indian public-use files: rural finance outcomes of NAFIS 201617, monthly Public Distribution System food-grain distribution data (20172023) and the Agricultural Census of India (201011 and 201516). The cross-country file includes 162 economies that are observed in 6 up to 6 waves. The descriptive analysis supports that there is an increasing adult account ownership in the world where 50.6 per cent in 2011 has grown to 78.7 per cent in 2024 with significant increases in the low- and middle-income continents. The highest relative increase in formal inclusion is in Sub-Saharan Africa: the ownership of accounts changes by increasing its percentage by 23.3 to 58.2, and mobile-money accounts are expected to increase in 2024 by 40 percent of adults, compared to 11.4 percent in 2014. In 2024 the global country data on the mean rural-urban gap in account ownership is 6.7 percentage points, the global gender gap at 4.2 points and global income-tercile gap is at 10.6 points. An OLS regression of the latest wave across countries shows that the higher the mobile-money account ownership in the country, the higher the proportion of adults who received agricultural payments in digital form (slope = 0.120 percentage points per percentage point, SE = 0.014, n = 74, R 2 = 0.486). Based on the household-level Georgia ADA analysis (n = 528 agribusinesses, two waves), there were no statistically significant changes in the difference-in-differences between the banks-loan uptake gap between grant recipients and non-recipient applicants (difference-in-differences = -1.9 percentage points, SE = 8.6, p = 0.83). It is recorded in the India case study that, rural workforce is 52.0 percent agricultural, 42.8 percent female in the agricultural sector and landholding distribution 73.3 percent of operation holdings are less than one hectare. The Indian rural-finance analysis reveals a high cross-state correlation between microfinance penetration and household indebtedness (r = +0.720, p < 0.001), an almost complete digitisation of PDS food-grain distributions between January 2018 (39.9 percent automated) and September 2023 (100 percent automated), and a further merchantetisation of cropped the analyses are not causal but descriptive. Nonetheless, trends are unmistakable: headline indicators of digital financial inclusion are increasing at a rate higher than that of credit expansion which is relevant to welfare, and structural gaps exist as access is broadening.