Credit Card Approval

Credit Card Approval Prediction

To identify important determinants, this study uses exploratory data analysis (EDA) to examine credit card approval data. We scrutinize your credit history, debt-to-income ratio, and income distribution to find trends and predictors of your likelihood of approval. Moving on to the presentation, we  use  Power BI to provide interactive data visualizations that allow for in-depth analysis. To support financial stakeholders, our data shows changes in approval rates and credit metrics. EDA gives us a complete understanding of the loan approval environment. We use Power BI to analyze trends and create interactive dashboards to help you make informed decisions. This research improves our understanding of credit risk assessment and decision-making processes. We empower financial industry stakeholders  by transforming complex data into actionable insights.

 

EXISTING CHALLENGES : 

Credit Karma is a popular platform that provides free credit score and credit monitoring services to its users. 

Differentiation: While Credit Karma provides users with information about their credit score and credit standing, our project  specifically aims to automate the credit card approval process.

SYSTEM ARCHITECTURE DIAGRAM :

MODULES USED:

 1. Exploratory Data Analysis (EDA)
 2. Data Preprocessing
 3. Model Selection
 4. Model Evaluation
 5. Deployment and Monitoring

ADVANTAGES : 

               

Reduction of manual labor 

Faster Processing

Risk limitation

INTERFACE