💡 Inspiration
Millions of Americans file financial complaints every year, yet the data is overwhelming and difficult to understand. We wanted to turn this massive, unstructured information into a visual story that clearly shows who is affected, where issues are worst, and which companies need the most improvement. Our inspiration came from a simple idea: 👉 “What if financial complaints could be understood at a glance?”
📊 What it does
Consumer Pulse 2025 is an interactive Tableau dashboard that analyzes U.S. consumer financial complaints (Aug–Nov 2025). It provides:
📈 Trend analysis of complaint volume
🔍 Breakdown of most common issues
🗺️ Heatmap of complaint density across states
🏢 Top 10 companies with highest complaints
📚 Issue distribution for major companies
✨ Key insights for regulators, businesses, and consumers
It turns raw CFPB data into clean, visual insights that anyone can understand in seconds.
🛠️ How we built it
Downloaded a filtered subset of the Consumer Complaint Database (CFPB)
Cleaned the data using Excel / Sheets (removed nulls, formatted dates, created calculated fields)
Imported the cleaned dataset into Tableau Desktop
Built 5 major visualizations:
Monthly trend line chart
Issue frequency bar chart
State-wise complaint map
Top 10 companies bar chart
Stacked issue breakdown for top companies
Combined all visualizations into an interactive Story Dashboard
Added insights, captions, and storytelling elements to guide the user
⚠️ Challenges we ran into
The dataset originally contained millions of rows, which caused performance issues
Tableau struggled to load excessively large CSV files without preprocessing
Cleaning and filtering the dataset to a manageable size required careful handling
Maintaining consistency in color palettes, axis formatting, and labels across story points
Ensuring that the visualizations were both technically accurate and visually appealing
🏆 Accomplishments that we're proud of
Built a fully interactive dashboard from real government data
Identified meaningful trends from complex, high-volume datasets
Created a clean, professional Tableau story suitable for regulators or executives
Turned messy complaint data into powerful visuals that tell a clear story
Completed a fully polished project in under 48 hours
📚 What we learned
How to handle large datasets by filtering, cleaning, and optimizing
Advanced Tableau techniques:
Sets
Filters
Calculated fields
Color encoding
Story points
How to extract insights from unstructured complaint data
Importance of visual storytelling in analytics
How real-world financial complaint systems work
🚀 What's next for Consumer Pulse 2025
Build an automated pipeline to refresh complaint data daily using the CFPB API
Add ML-based anomaly detection to spot sudden spikes in fraud or reporting issues
Develop a predictive model for identifying companies likely to receive rising complaints
Expand dashboard to include complaint resolution outcomes and sentiment analysis
Launch a public-facing version for consumers to track real-time complaint trends
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