Credit Card Financial Dashboard
Developed an interactive Power BI dashboard analyzing credit card transactions and customer insights to visualize spending patterns and revenue trends.
Every transaction is a tiny story about behaviour, risk, and opportunity and when you bring thousands of those stories together, patterns emerge.
The Credit Card Transaction & Customer Dashboard converts granular transaction logs and customer profiles into strategic intelligence spending trends, top categories, customer segmentation, anomaly/fraud signals, and revenue drivers.
Built as an interactive Power BI experience, it helps product, finance, and risk teams monitor trends, detect outliers, target offers, and reduce exposure turning raw data into decisions that grow revenue and protect customers.
Project Objective:
To develop a comprehensive credit card weekly dashboard that provides real time insights into key performance matrics and trends, enabling stakeholders to monitor and analyse credit card operations effectively.
Chapter 1: Data Preprocessing
Before diving into the dashboards, meticulous data preprocessing was conducted. Redundant columns were removed, null values were addressed, and duplicates were eliminated. Additionally, columns were appropriately renamed in the Power Query Editor of Power BI, ensuring a clean and organized dataset for insightful visualizations.
Chapter 2: Transaction Dashboard
Unveiling the spending behaviour of customers across different backgrounds, this dashboard explores expenditure types, education levels, job roles, and card categories. It provides a clear picture of how various customer segments interact with credit products, offering valuable insights into lifestyle patterns, financial habits, and category-wise spending preferences.
Key Insights:
- Revenue from Bills accounts for ₹14M, indicating consistent spending on essential payments.
- Customers with a Graduate education contribute the highest revenue of ₹23M.
- Business professionals generate ₹18M in revenue, representing a key customer segment.
- The Blue card category dominates with ₹47M in revenue, showing strong customer preference.
- High-frequency card swipes drive ₹36M in revenue, highlighting active engagement as a revenue booster
Chapter 3: Customer Dashboard
Providing a deeper understanding of the customer base, this dashboard highlights the top five states by customer count, along with key demographics such as marital status, age group, education level, and salary range. It offers a comprehensive view of where customers come from and who they are, helping businesses identify high-value segments, regional trends, and potential target audiences for future marketing strategies. Utilized data groups to organize and visualize data.
Key Insights:
- Male customers are contributing more in revenue 30.9M, female 25.6M
- TX, NY, and CA contributing to 68%
- Age group 40-50 are primary attention
- High-salary customers generate the highest revenue, showing income drives card usage.
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