Analyzing bank loan data involves collecting and cleaning applicant information, performing exploratory analysis to uncover trends, engineering features to enhance model performance, selecting and training predictive models like logistic regression or decision trees, assessing risk to determine loan approval, deploying the model into production, documenting findings, and ensuring compliance with regulatory and ethical standards throughout the process. This comprehensive approach ensures accurate decision-making based on data-driven insights.
Financial Data: This data source is primarly available in csv format , the that is used for the analaysis "financial_loan.csv" file, containing each deatils about the customer and the loan details.
- Excel Power Query - Data cleaning & Transformation
- Excel - Analysis Dashboard Preparation
In the initial phase i performed the following tasks:
- Data loading and inspection.
- Handling missing values and empty rows.
- Data cleaning and formating.
- Making the data into a table.
This method involved in solving the KPI's in bank loan analysis that is listed in the problem statement document. View Here - KPI's or Problem Statement
