I am currently working on two primary projects. The first delves into the history of consumer credit scoring to understand present day policy efforts predicated on expanding data collection and the use of algorithmic scoring as a tool to foster racial and economic inclusion for those on the margins. In this work, I analyze historical documents, an original national survey, and semi-structured interviews to assess the reasons behind the push to expand the use of algorithms despite prevalent critiques of algorithms as increasing racial inequality, and ultimately unveil key limitations to racial inclusion in an algorithmic age. Second, as a part of a multi-university team of researchers, I am using administrative credit report data from one of the largest credit reporting agencies to study credit and debt outcomes in the United States. With granular information on millions of consumers across nearly a decade, this project has begun to understand the effects of federal social policy on the use of risky forms of unsecured credit and the role of residential segregation in the creation of markets for alternative credit products like payday loans.