banks (Aron 2018; Suri 2017).<sup>15</sup> In addition, evidence suggests that alternate credit scoring based on individuals’ digital presence can expand credit access to the unbanked who lack credit scores without adversely impacting default outcomes (Agarwal et al. 2019).

Several studies suggest that the use of digital technologies in financial services disproportionately benefits poor households. Asongu and Nwachukwu (2018) conclude that using mobile phones to send or receive money or to pay bills is associated with falling inequality in upper-middle-income countries. Asongu and Odhiambo (2018) also find that sending or receiving money by mobile phone is associated with falling inequality in a sample of more than 90 developing economies (except in countries where poverty is the lowest). Chinoda and Mashamba (2021) use a structural equation modeling approach to address the endogeneity concerns in the two previous studies. Using a sample of 25 African countries, they find that fintech has an indirect relationship, through financial inclusion, with income inequality. Demir et al. (2022) reach a similar conclusion in an analysis of 140 (mostly developing) countries, with the largest effects observed in the countries with the highest inequality. The importance of financial inclusion in the link between fintech and inequality is echoed by Hodula (2023).

A related strand of literature examines the ability of fintech to smooth consumption, which may help prevent households from slipping into poverty when experiencing adverse events. Evidence from Kenya, for instance, shows that receipt of digital loans and use of mobile money improves households’ resilience to negative shocks (Suri, Bharadwaj, and Jack 2021; Jack and Suri 2014). The frequency and amount of migrant remittances is also relevant here. For example, mobile money users in Kenya are more likely to receive and send remittances (Jack, Ray, and Suri 2013). In Uganda, Munyegera and Matsumoto (2016) show that mobile money subscribers are 20 percentage points more likely to receive remittances from family members compared to nonsubscribers, and that the annual value of remittances received by subscribers is one-third higher. However, evidence from China suggests that although digital financial inclusion can mitigate a large portion of transient income shocks, it is not effective in mitigating permanent income shocks (Lai et al. 2020).

There is also evidence that the use of mobile money is directly linked with better labor market outcomes for poor households. Lederman and Zouaidi (2020) show that digital payments are associated with lower unemployment rates for a large sample of developing economies, building on previous work which shows that digital payments improve the efficiency of labor allocation in Mexico and Kenya (Bachas et al. 2018; Suri and Jack 2016).

# **5. Digitalization and public finance**

Digitalization can boost inclusive growth by enhancing the provision of public goods and services and increasing access to social protection programs, which disproportionately benefit poorer households. These benefits can be attributable to the use of digital technologies that enables new delivery models, enhances the transparency and accountability of service providers, and supports

> 15 Studies on the economic effects of digital financial services build on a large literature on the economic effects of financial development (e.g., Beck, Demirgüç-Kunt, and Levine 2007; de Haan and Sturm 2017; Honohan 2008; Levine 2005). Khera et al. (2021) take up the little studied causal link between digital financial inclusion and growth.

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