Predictive Customer Segmentation in Risk Analysis
Degree
Master of Science in Computer Science
Department
Department of Computer Science
School
School of Mathematics and Computer Science (SMCS)
Date of Submission
Spring 2024
Supervisor
Dr. Tariq Mahmood, Professor and Program Coordinator MS(CS) and MS(DS) Programs, School of Mathematics and Computer Science (SMCS)
Keywords
Customer Segmentation, Risk Analysis, Machine Learning, K-means Clustering
Abstract
This project aims to create a customer segmentation framework for risk analysis in the banking sector. Utilizing machine learning techniques, such as K-means clustering and PCA, the project segments customers into distinct risk groups based on various factors. The goal is to enhance decision-making processes in lending, credit scoring, and risk management. The framework provides actionable insights through interactive visualizations, offering significant potential for improving financial services and risk management in the banking industry.
Document Type
Restricted Access
Submission Type
Research Project
Recommended Citation
Hashmi, Marium. "Predictive Customer Segmentation in Risk Analysis." Unpublished graduate research project. Institute of Business Administration. 2024. https://ir.iba.edu.pk/research-projects-mscs/40
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