Linguistic Marginalization as a Weapon of Economic Oppression: An NLP Analysis of Financial Literacy Outcomes in India

India is currently facing a “linguistic genocide” of minority languages due to the implementation of nationwide hegemonic policies. This has severe repercussions for speakers, as it contributes to cycles of intergenerational poverty. Experts suggest that many of the declining languages are spoken by Scheduled Tribes, a factor that has played a role in their widespread impoverishment. To build on these claims, this study employed AI-based corpus analysis and statistical modeling to investigate the relationship between the availability of financial literacy terms and financial literacy outcomes across different language groups. Additional factors, including language vitality, script type, geographic region, and population density, were also assessed. The results revealed a significant correlation between the presence of financial literacy terms and financial literacy outcomes, with language vitality and script type serving as key explanatory variables. Languages with the lowest percentages of financial literacy terms and financial literacy scores typically belonged to historically marginalized tribal groups. These findings underscore the role of linguistic exclusion in perpetuating poverty and highlight the urgent need for financial literacy education in local languages.