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- W4385215216 abstract "Abstract: Redlining is a term for race-based discriminatory acts in real estate. While this practice has been outlawed in modern America, the effects remain evident today’s society. The importance of this research is to determine if redlining is still prevalent in America and causing some racial groups to be more likely to be denied home loans over others. This paper analyzes the lasting impacts of housing discrimination in the United States by using data science applications and uses machine learning models to predict whether a loan request will be accepted or denied. We are analyzing loan approval and denial over the past decade by utilizing census data provided by the Home Mortgage Disclosure Act from the United States government. We are determining whether Black Americans and other ethnic minorities are disproportionately denied loans even with similar loan applications as other races. In other words, are they still being redlined and discriminated against based on their race. Our research revolves around the entire nation, from California to Alabama to Illinois to Michigan to determine if redlining is continuously occurring in such places and to predict loan acceptance. We determined that race was not a major factor in home loan decisions, and applicant income, along with loan amount, took precedence" @default.
- W4385215216 created "2023-07-25" @default.
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- W4385215216 date "2023-07-31" @default.
- W4385215216 modified "2023-09-24" @default.
- W4385215216 title "Application of Computational Analysis to Identify Housing Discrimination in 21st Century United States" @default.
- W4385215216 doi "https://doi.org/10.22214/ijraset.2023.54883" @default.
- W4385215216 hasPublicationYear "2023" @default.
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