This project analyzes DBS Bank financial data to understand loan distribution, client activity, and transaction behavior.
The analysis transforms raw banking data into actionable business insights using SQL queries, Excel dashboards, Power BI reports, and Tableau visualizations.
The project includes two major analyses:
- Loan Data Analysis
- Credit & Debit Transaction Analysis
This project demonstrates a complete end-to-end data analysis workflow including:
- Data extraction
- Data cleaning
- Data visualization
- Business insight generation
The dataset used in this project was provided as part of a data analysis project during the ExcelR / AI Variant internship.
The dataset simulates real-world banking operations, including:
- Loan disbursement data
- Client activity information
- Credit and debit transactions across multiple branches and banks
This dataset was used to perform exploratory data analysis, SQL querying, and dashboard development using Excel, Power BI, and Tableau.
Note: The dataset is used strictly for educational and portfolio purposes and does not represent actual DBS Bank customer data.
The dataset used in this project contains banking financial data related to loan disbursements and customer transactions.
- Total Records: ~2000 clients
- Features include:
- Client ID
- Branch Name
- Loan Amount
- Funded Amount
- Loan Category
- Disbursement Date
- Repayment Status
- Risk Category
Dataset Size
Loan Dataset • ~2000 client records • 10+ features including branch, loan amount, risk category, disbursement date
Transaction Dataset • Multiple bank transaction records • Includes credit, debit, branch, bank, risk category
This analysis aims to answer key business questions related to banking operations and customer transactions.
- How many total clients does the bank have and how many are active?
- What is the total loan amount disbursed by the bank?
- Which branches contribute the highest loan disbursement?
- What is the average loan size given to customers?
- How has loan disbursement grown over the years?
- What percentage of loans are repaid on time?
- Which loan categories represent higher risk?
- What is the total transaction volume across banks?
- How do credit and debit transactions compare?
- Which banks generate the highest transaction amounts?
- Which branches show the highest transaction growth?
- What is the ratio of credit to debit transactions?
- What proportion of transactions fall under high-risk categories?
- SQL – Data extraction and analysis
- Excel – Data cleaning and dashboard creation
- Power BI – Interactive dashboards and KPI tracking
- Tableau – Data visualization and analytics dashboards
• Removed duplicate client records • Handled missing values • Converted date columns into proper format • Standardized loan amount units • Verified data accuracy using SQL queries
The objective of this analysis is to:
- Analyze loan disbursement trends
- Identify active clients
- Evaluate repayment behavior
- Compare branch performance
- Track loan growth over time
| Metric | Value |
|---|---|
| Total Clients | 2000 |
| Active Clients | 324 |
| Average Loan Size | ₹26,180 |
| Total Funded Amount | ₹5.23 Cr |
| Total Loan Disbursed | ₹5.23 Cr |
| Total Repayments Collected | ₹5.38 Cr |
| On-Time Repayment Rate | 71% |
Example SQL Query
SELECT branch_name, SUM(loan_amount) AS total_loan FROM loan_data GROUP BY branch_name ORDER BY total_loan DESC;
- Loan distribution varies across different branches.
- Some branches contribute significantly to total loan disbursement.
- Loan growth increased significantly in 2021.
- The 71% on-time repayment rate indicates strong repayment behavior.
- Majority of loans fall into medium and low risk categories.
This analysis focuses on understanding customer transaction behavior across banks and branches.
The main goals are:
- Compare credit vs debit transactions
- Identify high transaction branches
- Monitor transaction growth trends
- Detect high risk transactions
| Metric | Value |
|---|---|
| Total Transaction Amount | 254.89M |
| Total Credit Amount | 127.60M |
| Total Debit Amount | 127.29M |
| Credit to Debit Ratio | 1.0025 |
| Net Transaction Amount | 318.12K |
- Credit and debit transactions are almost equal, showing balanced financial activity.
- Some branches show higher transaction growth, indicating stronger banking engagement.
- Most transactions fall under normal risk, while a small portion are classified as high risk.
- Certain banks contribute significantly to the overall transaction volume.
- SQL Data Analysis
- Data Cleaning & Transformation
- Excel Dashboard Development
- Power BI Data Visualization
- Tableau Visualization
- KPI Analysis
- Business Insight Generation
This project demonstrates how banking data can help organizations:
- Monitor loan performance
- Analyze customer transaction behavior
- Identify branch performance
- Detect risk patterns
- Support data-driven financial decisions
Saba Attar
Aspiring Data Analyst skilled in:
- SQL
- Excel
- Power BI
- Tableau
- Data Visualization