Loan Approval Prediction

Inspiration

Loan Prediction is extremely useful for worker of banks similarly as for the customer additionally. The aim of this Project is to supply fast, immediate method for the eligible candidates. It will offer special advantage to the bank. The Loan Prediction System will calculate the load of every option participating in the loan process.

What it does

Loans area unit the core business of banks. The most profit comes directly from the loan’s interest. The loan corporations grant a loan with an associate degree of intensive method of verification and validation

How we built it

Data collection , Data cleaning and preprocessing, Feature engineering, Model selection, Model training, Model evaluation, Model deployment

Challenges we ran into

As the loan application analysis can be done using various algorithms and testing the model for higher accuracy providing algorithm.

Accomplishments that we're proud of

By using a logistic regression approach, the right customers to be targeted for granting loans can be easily detected by evaluating their likelihood of default on loans.

What we learned

We learned the logistic regression model concludes that a bank should not only target rich customers for granting loans but it should assess the other attributes of a customer as well which play a very important part in credit granting decisions and predicting the loan defaulters.

What's next for Loan Approval Prediction

Model is marginally better because it includes variables (personal attributes of customer like age, purpose, credit history, credit amount, credit duration, etc.)

Built With

• databases
• flask
• ml
• python