Uncovering Hidden Fraud Networks in Real Time
FinTrust Bank is losing $10M annually to sophisticated fraud rings that exploit disconnected data silos. Traditional systems flag individual suspicious transactions but miss the bigger picture of coordinated activity.
Demo Overview
In this demonstration, you'll see how Graphora transforms unstructured financial data into a powerful graph that reveals hidden fraud networks in real-time. Traditional systems miss these connections because they analyze each transaction in isolation.
The Problem
Analysts at FinTrust Bank manually piece together relationships between accounts, beneficiaries, and external entities—a slow, error-prone process that lags behind fast-moving fraudsters.
Graphora's Solution
By extracting entities and relationships from unstructured data, Graphora creates a comprehensive graph that reveals multi-hop connections (e.g., Account → Person → Shell Company) that tabular data analysis would miss.
Demo Process
Step 1: Upload Unstructured Data
Upload transaction logs, customer emails, and regulatory watchlists into Graphora.
Upload Data Files
Drag and drop your files here, or
Accepted files: TXT, CSV, PDF, DOCX
Or use sample files:
| File Name | Type | Size |
|---|---|---|
| transaction_logs.txt | text/plain | 1.2 MB |
| customer_emails.txt | text/plain | 3.5 MB |
| regulatory_watchlist.csv | text/csv | 420 KB |
Upload files to visualize the fraud network graph