Description: This project focuses on analyzing the creditworthiness of loan applicants for a small bank. Due to a recent financial scandal at a competitor bank, there has been a surge in loan applications, requiring a more efficient processing approach. The objective is to use classification modeling techniques to evaluate the creditworthiness of the new loan applicants and provide a list of creditworthy customers to the manager within two days.
Key Points:
- Objective: Evaluate the creditworthiness of loan applicants and process applications efficiently.
- Business Problem: Handle an increased number of loan applications within a week.
- Data Sources:
1. Data on past loan applications.
2. List of customers that need to be processed in the next few days.
- Steps:
1. Apply the Problem Solving Framework to analyze the business problem.
2. Utilize classification modeling techniques to evaluate creditworthiness.
3. Process loan applications efficiently based on the model's predictions.
4. Provide a list of creditworthy customers to the manager within two days.
- Note: The analysis will consider historical data on loan applications to train a classification model that can predict the creditworthiness of new applicants. Efficient processing methods will be employed to handle the increased workload.
Note: The project aims to leverage classification modeling to evaluate the creditworthiness of loan applicants and enable the efficient processing of applications. By using historical data and applying appropriate techniques, the project aims to provide the bank with a systematic approach to identify creditworthy customers and process loan applications effectively within a tight timeframe.