Fraudulent booking detector: Identify suspicious travel transactions with Google Gemini

This automated n8n workflow detects and manages fraudulent booking transactions through comprehensive AI-powered analysis and multi-layered security checks. The system processes incoming travel booking data, performs IP geolocation verification, enriches transaction details with AI insights, calculates dynamic risk scores, and executes automated responses based on threat levels. All transactions are logged and appropriate notifications are sent to relevant stakeholders.

Good to Know

• The workflow combines multiple detection methods, including IP geolocation, AI analysis, and risk scoring algorithms
• Google Gemini Chat Model provides advanced natural language processing for transaction analysis
• Risk levels are dynamically calculated and categorized as CRITICAL, HIGH, or standard risk
• Automated blocking and flagging system protects against fraudulent transactions in real-time
• All transaction data is logged to Google Sheets for audit trails and pattern analysis
• The system respects API rate limits and includes proper error handling mechanisms

How It Works

1. Initial Data Ingestion & Extraction

• Monitors and captures incoming booking transaction data from various sources
• Extracts key booking details including user information, payment data, booking location, and transaction metadata
• Performs initial data validation and formatting for downstream processing

2. IP Geolocation and AI Analysis

• IP Geolocation Check: Validates booking IP addresses by checking geolocation details and comparing against expected user locations
• AI Agent Integration: Utilizes Google Gemini Chat Model to analyze booking patterns, user behavior, and transaction anomalies
• Enhanced Data Processing: Enriches transaction data with geographical context and AI-driven risk indicators

3. Risk Calculation and Decision Logic

• Enhanced Risk Calculator: Combines AI-generated risk scores with geolocation-based factors, payment method analysis, and historical patterns
• Critical Risk Check: Flags transactions with risk levels marked as CRITICAL for immediate action
• High Risk Check: Identifies HIGH risk transactions requiring additional verification steps
• Dynamic Scoring: Adjusts risk calculations based on real-time threat intelligence and pattern recognition

4. Action & Notification

• Block User Account: Automatically blocks user accounts for CRITICAL risk transactions to prevent immediate fraud
• Flag for Review: Marks HIGH risk transactions for manual review by fraud prevention teams
• Send Notifications: Dispatches real-time alerts via email and messaging systems to security teams
• Automated Responses: Sends appropriate messages to users based on transaction status and risk level

5. Logging & Response

• Log to Google Sheets: Records all transaction details, risk scores, and actions taken for comprehensive audit trails
• Flag for Review: Maintains detailed logs of flagged transactions for pattern analysis and machine learning improvements
• Response Tracking: Monitors and logs all automated responses and manual interventions

How to Use

• Import the workflow into your n8n instance
• Configure Google Gemini Chat Model API credentials for AI analysis
• Set up IP geolocation service API access for location verification
• Configure Google Sheets integration for transaction logging
• Establish Gmail/email credentials for notification delivery
• Define risk thresholds and scoring parameters based on your fraud tolerance levels
• Test the workflow with sample booking data to verify all components function correctly
• Monitor initial deployments closely to fine-tune risk scoring algorithms
• Establish manual review processes for flagged transactions
• Set up regular monitoring and maintenance schedules for optimal performance

Requirements

• Google Gemini Chat Model API access
• IP Geolocation service API credentials
• Google Sheets API integration
• Gmail API or SMTP email service for notifications
• n8n instance with appropriate node modules installed

Customizing This Workflow

• Risk Scoring Parameters: Adjust risk calculation algorithms and thresholds based on your specific fraud patterns and business requirements
• AI Model Configuration: Fine-tune Google Gemini prompts and analysis parameters for improved accuracy in your use case
• Notification Channels: Add or modify notification methods including Slack, SMS, or webhook integrations
• Data Sources: Extend input methods to accommodate additional booking platforms or payment processors
• Logging Destinations: Configure alternative or additional logging systems such as databases or external SIEM platforms
• Geographic Rules: Customize geolocation validation rules based on your service areas and customer base
• Automated Actions: Modify or expand automated response actions based on your fraud prevention policies
• Review Workflows: Integrate with existing fraud review systems or ticketing platforms for seamless manual review processes