For underrepresented communities, the practice of redlining has historically led to unjust denials of loans based on their race, ethnicity, or the neighborhood they live in. Even though redlining is illegal, its subtle effects can still persist, affecting communities' access to fair financial opportunities. Our project aims to develop a machine learning model that can detect instances where a loan should have been approved based on the applicant's qualifications but was unfairly denied, shedding light on potential redlining practices.

1. Unzip the contents of the table.zip file into the folder of the package
2. Run Main.py
3. Input your information and information about the loan into the interface
4. Wait for the model to predict whether or not your loan should be approved assuming the system is unbiased