BANKING CUSTOMER ANALYSIS BY USING JUPYTER

Abstract

Banking Customer Analysis is an important process that helps banks understand customer behavior, preferences, and financial activities. The main objective of this project is to analyze banking customer data using Jupyter Notebook and identify useful insights that can help banks improve their services and customer satisfaction. In this project, customer data such as age, account balance, transaction history, and other related details are collected and analyzed using data analysis techniques. The analysis is performed using Python along with libraries like Pandas, NumPy, and Matplotlib to clean, process, and visualize the data. The project focuses on identifying customer patterns, segmenting customers based on their financial behavior, and understanding trends in banking activities. Visualization techniques such as charts and graphs are used to represent the analyzed data clearly and effectively. The results of this analysis help in predicting customer needs, improving decision-making, and providing personalized banking services. Overall, this project demonstrates how data analysis using Jupyter Notebook can support banks in understanding their customers better and enhancing their operational strategies.