Fraudulent Booking Detector: Identify Suspicious Travel Transactions with Google Gemini

Description

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