This project aims to analyze loan portfolios and communication history for a financial institution. The project involves analyzing two datasets related to loans given to customers and their communication history. The first dataset, Portfolio_data.csv, contains information about loans given to customers, including their demographic information and the loan amount. The second dataset, CommunicationHistory.csv, contains details about the attempts made to contact these customers and the status of these calls.
The main objectives of this project are:
To analyze the distribution of loans across different states and loan amounts. To identify the distribution of customers by age and loans by due dates. To find the unique number of customers contacted every day, identifying the customers who have been contacted the most and least, and determining how many customers have never been reached out. To analyze the distribution of calls by states and campaign IDs and identify the unique number of customers by campaign ID.
This project is implemented using the following technologies:
Python 3.8 Pandas 1.3.3 Matplotlib 3.4.3
This project has analyzed loan portfolios and communication history for a financial institution. The analysis has provided insights into the distribution of loans across different states and loan amounts, the distribution of customers by age and loans by due dates, the unique number of customers contacted every day, the customers who have been contacted the most and least, and the customers who have never been reached out. The analysis has also revealed the distribution of calls by states and campaign IDs and the unique number of customers by campaign ID.