Date of Submission

7-11-2025

Date of Award

7-22-2025

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Cryptology

Department

Cryptology and Security Research Unit (CSRU-Kolkata)

Supervisor

Mishra, Debasish

Co-Supervisor (if any)

Molla, Anisur Rahaman

Abstract (Summary of the Work)

This report presents the work I did during my internship at Hongkong and Shanghai Banking Corporation (HSBC), Kolkata. As a financial institution, the strength of the bank is fundamentally rooted in the behavior and reliability of its customers. Understanding this behavior is not only desirable; it is essential for the security, risk mitigation and future strategic planning of the bank. To do this, banks must invest in a thorough analysis of the financial behavior of their customers to detect early signs of risk and act accordingly. I worked in the Finance Support Team within the Data and Analytics division, where our focus was to build data-backed tools and insights to help identify what can cause financial vulnerability. My internship focused on feature engineering and dashboard making to support and strengthen financial decision-making frameworks. Key areas of my work included • Developing features like overdraft utilization, debt-to-income ratio, and essential spend indicators • Automating SQL pipelines to extract and aggregate large-scale banking data • Designing interactive dashboards in Looker to visualize customer behaviors (e.g., gambling, BNPL overuse) • Analyzing correlations, outlier patterns, and vulnerability signals in transac-tional datasets • Presenting a theoretical exploration of NLP embedding techniques including TF-IDF, CBOW, Skip-Gram, and LSTM The project blended technical depth with domain knowledge to build insights from financial data, aiming to identify early risk markers and guide responsible lending. The internship not only enhanced my analytical and engineering skills, but also offered a valuable experience in solving real-world problems collaboratively within a data science team.

Control Number

CrS2308

DOI

https://dspace.isical.ac.in/items/c19c0546-49f5-42d7-9f65-b02d92842041

DSpace Identifier

http://hdl.handle.net/10263/7636

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