CYBERWATCH BY KODEKNIGHTS

UNIFIED GRAPH BETWEEN FINANCIAL TRANSACTION AND CYBER ATTACK

Inspiration

We were inspired to build CyberWatch as a proactive financial crime intelligence platform — one that doesn’t just detect fraud, but anticipates it. The goal was to create a system that simulates, analyzes, and predicts suspicious financial behavior in real time.

What it does

CyberWatch is a financial crime intelligence platform that: • Detects suspicious financial patterns in real time • Simulates multi-stage money laundering scenarios • Generates dynamic risk scores for users and transactions • Provides actionable alerts for compliance teams • Visualizes fraud progression across multiple phases

How we built it

We built CyberWatch using: • Frontend: HTML, CSS, JavaScript (clean, dashboard-style UI) • Backend: Python for logic and risk scoring • Data Simulation: Synthetic transaction data generation • Scoring Engine: Custom credit/risk scoring algorithm • Visualization: Interactive dashboard components

Challenges we ran into

• Designing an accurate and dynamic risk scoring model
• Simulating realistic multi-phase laundering flows
• Handling edge cases in transaction data
• Debugging incorrect credit score calculations
• Ensuring real-time responsiveness without slowing performance

Accomplishments that we're proud of

• Successfully built a 6-phase simulation engine
• Implemented dynamic risk scoring with anomaly detection
• Created a clean, professional intelligence dashboard
• Developed a working prototype within hackathon time constraints
• Designed a scalable architecture for future expansion

What we learned

• How complex financial fraud patterns actually evolve
• The importance of data normalization in risk scoring
• How to simulate real-world adversarial behavior
• Debugging large logic systems under time pressure
• The value of building modular and scalable code

What's next for CYBERWATCH

• How complex financial fraud patterns actually evolve
• The importance of data normalization in risk scoring
• How to simulate real-world adversarial behavior
• Debugging large logic systems under time pressure
• The value of building modular and scalable code