Many individuals find the world of loans daunting. The criteria banks and financial institutions consider when granting loans remain opaque to many. We saw an opportunity to demystify this process, empowering individuals with the knowledge to make informed decisions about their financial futures.

Preprocessing:

• Obtained a Data set from Kaggle.com, had to clean the data and clear any NaN data
• Identify columns needed for training, clear any Irrelevant columns

Training:

• Split the data set between training and testing
• Use a RandomForestClassifier to train and fit the data

Testing:

• Used the sklearn accuracy_score library to check that our model is accurate and not likely to overfitting from the dataset
• Obtained an accuracy of 82% when back testing from the data set