Welcome to my repository showcasing the use of Kusto Query Language (KQL) as GQL for advanced financial data analysis. This project demonstrates how graph-driven queries can uncover hidden patterns and relationships in financial datasets.
A snapshot of a financial network graph showing asset ownerships
The graphical presentations in this repository address key financial intelligence use cases:
- 💸 Financial Fraud Detection
- 🕵️♂️ Anti-Money Laundering (AML) Analysis
- 🔁 Transaction Pattern Analysis
- 📊 Risk Assessment & Credit Scoring
- 🚨 Suspicious Activity Monitoring
- 🌐 Financial Network Analysis
The repository is organized into two main folders:
Contains KQL scripts for querying and analyzing transaction data:
-
🧮
account-ownerships.kql
Identifies account ownerships by individuals and companies. -
🔁
transactions.kql
Tracks transactions between individuals and companies. -
📈
timelined-transactions.kql
Generates a time-pivoted chart of individual-to-individual transactions.
Includes video walkthroughs of the scripts in action:
- 📽️
account-ownerships.mp4 - 📽️
timelined-transactions.mp4
To use the scripts, ensure you have access to a KQL-compatible environment (e.g., Azure Data Explorer). Simply open the desired .kql file and run the query.