Abstract: There is dense literature on the relationship between financial sector development (FSD) and income inequality. However, most of these studies employ a depth measure of FSD. This study argues that different components of FSD have a heterogenous impact on income inequality. This study first empirically tests the overall impact of FSD on income inequality. Thereafter, I investigate both the linear and nonlinear impact of financial sector development dimensions (depth and access) on income inequality. The study’s novelty lies in using financial access data such as ATM per adult and financial access index and comparing their impact on income inequality versus the impact of financial sector depth (growth in domestic credit) on inequality. Adding to this, fewer studies have investigated the overall impact of FSD. To solve the endogenous problem, the study uses the system General Method of Moments (GMM) on the panel data of 120 countries, from 2004 to 2019. The findings of the study are threefold. Firstly, the study finds that the overall FSD index, individual financial institutions, and market development index all narrow income inequality. Secondly, this study finds that different dimensions of FSD have heterogenous impacts on income inequality, where increased access to financial services reduces income inequality in both linear and nonlinear models. While financial sector depth narrows income inequality in the linear model, the nonlinear model reveals that the Too Much Finance hypothesis holds, as the results confirm a U-shaped relation with income inequality. These results are important for policy decisions concerning financial reforms and income distribution. These results imply that financial sector reforms can be shaped to reduce income inequality by increasing access to credit and through credit policy provisions.