A Data-Driven Exploration of Bias in Lending
This project explores the ongoing impact of redlining in Baltimore by analyzing mortgage lending data, neighborhood demographics, and AI-driven lending practices. Although redlining was outlawed decades ago, its legacy persists through biased data and discriminatory algorithms.
Baltimore has a long history of housing segregation. From HOLC maps in the 1930s to present-day zoning and lending practices, many Black and low-income communities have been systematically excluded from fair access to credit and housing. This project seeks to understand how modern data systems may unintentionally continue this legacy.