Demo Dashboard

Interactive Streamlit dashboard for testing and demonstrating the fraud detection system.

Starting the Dashboard

# Ensure the API is running first
uvicorn src.api.main:app --reload --port 8000

# Start the dashboard
streamlit run dashboard.py --server.port 8501

Open http://localhost:8501 in your browser.

Dashboard Layout

Sidebar: System Status

Real-time health indicators:

Indicator	Description
System Status	Overall health (Healthy/Degraded/Down)
Redis	Velocity counter store connection
PostgreSQL	Evidence storage connection
Policy	Policy engine status
Policy Version	Current active policy version

Main Area: Transaction Simulator

Attack Presets

One-click presets to demonstrate different fraud scenarios:

Preset	Description	Expected Result
Normal Transaction	Typical $50 purchase	ALLOW
Card Testing Attack	Small $1 amount from datacenter IP	REVIEW or BLOCK
Velocity Attack	$1500 from new account	FRICTION or REVIEW
Geographic Anomaly	US card transacting from Nigeria	REVIEW
Bot/Emulator Attack	Emulated device via Tor	BLOCK
Friendly Fraud Risk	High-value from dispute-prone user	FRICTION

Custom Transaction Fields

Fine-tune transaction parameters:

• Amount - Transaction value in USD
• Service ID - Telco service identifier
• Event Subtype - sim_activation, topup, device_upgrade, sim_swap, etc.
• Card Token - Tokenized card reference
• User ID - Customer identifier
• Device Emulator - Toggle emulated device flag
• Device Rooted - Toggle rooted/jailbroken flag
• IP Datacenter - Toggle datacenter IP flag
• IP Tor - Toggle Tor exit node flag
• IP VPN - Toggle VPN flag

Decision Display

Decision Badge

Large colored badge showing the decision:

Decision	Color	Meaning
ALLOW	Green	Transaction approved
FRICTION	Yellow	Request additional verification
REVIEW	Orange	Queue for manual review
BLOCK	Red	Transaction declined

Score Gauges

Four interactive gauge charts:

1. Overall Risk - Combined risk score (0-100%)
2. Criminal Score - Criminal fraud probability
3. Friendly Fraud - Friendly fraud probability
4. Bot Score - Automation detection score

Color thresholds:

• 0-30%: Green (low risk)
• 30-60%: Yellow (medium risk)
• 60-80%: Orange (elevated risk)
• 80-100%: Red (high risk)

Signal Details

Expandable section showing:

• Triggered detection signals
• Individual detector scores
• Feature values used in decision
• Policy rules that matched

Analytics Tab

Decision Distribution

Pie chart showing decision breakdown:

• Percentage of ALLOW vs FRICTION vs REVIEW vs BLOCK
• Updated in real-time as transactions are processed

Hourly Volume

Bar chart showing:

• Transaction volume per hour
• Decision distribution over time
• Useful for identifying attack patterns

Latency Metrics

Line chart displaying:

• P50 latency (median)
• P95 latency
• P99 latency
• Target threshold line (10ms)

Decision History Tab

Table showing recent decisions:

Column	Description
Timestamp	When decision was made
Transaction ID	Unique identifier
Amount	Transaction value
Decision	ALLOW/FRICTION/REVIEW/BLOCK
Overall Risk	Combined risk score
Signals	Triggered detectors
Latency	Processing time

Features:

• Sort by any column
• Filter by decision type
• Export to CSV
• Click row for full details

Policy Inspector Tab

Current Policy

Displays the active policy configuration:

version: "1.0"

thresholds:
  block: 80
  review: 60
  friction: 40

rules:
  - name: high_value_new_user
    condition: amount > 500 AND user_age_days < 7
    action: FRICTION

Policy Actions

• View Full YAML - See complete policy file
• Reload Policy - Hot-reload from disk
• Version History - See previous policy versions

Demo Scenarios

Scenario 1: Normal Operations

1. Select "Normal Transaction" preset
2. Click "Submit Transaction"
3. Observe ALLOW decision with low scores
4. View decision in history

Scenario 2: Card Testing Attack

1. Select "Card Testing Attack" preset
2. Submit multiple times rapidly
3. Watch scores increase with each submission
4. Eventually triggers REVIEW then BLOCK
5. Demonstrates velocity detection

Scenario 3: Bot Attack

1. Select "Bot/Emulator Attack" preset
2. Submit transaction
3. Immediate BLOCK decision
4. View signals: bot_detected, tor_exit_node

Scenario 4: Policy Change

1. Edit config/policy.yaml
2. Change friction threshold from 40 to 30
3. Click "Reload Policy" in dashboard
4. Submit borderline transaction
5. Observe changed decision behavior

Keyboard Shortcuts

Shortcut	Action
Enter	Submit transaction
R	Reload policy
C	Clear form
H	Toggle history panel

Tips for Demos

1. Start clean - Reset Redis counters before demos
2. Tell a story - Walk through attack → detection → block
3. Show the numbers - Explain what scores mean
4. Live reload - Demonstrate policy changes take effect instantly
5. Show evidence - Pull up stored evidence for a blocked transaction