Programme

HDIP in Data Analytics for Business

Abstract

This project investigates customer churn within the banking sector, analysing a dataset of 10,000 customers to identify patterns and potential drivers of attrition. By leveraging data analytics and visualization techniques, we aim to understand the demographic and behavioural factors influencing customer decisions to leave for competing banks. The study applies the CRISP-DM framework to structure the analysis, enabling iterative refinement of objectives and hypotheses as insights emerge. Findings indicate that certain customer segments, such as those aged 40–60, are more prone to churn, highlighting opportunities for targeted retention strategies, including fee reductions and tailored loyalty programmes. By integrating academic research on customer satisfaction and retention, this project underscores the strategic importance of understanding and mitigating churn to support long-term business sustainability in the banking industry.

Date of Award

2025

Full Publication Date

2025

Access Rights

open access

Document Type

Capstone Project

Resource Type

thesis

Included in

Data Science Commons

Share

COinS