Transaction Graph

Base Model

Transaction and Account Data Model Diagram

Key Features:

  • Complete customer identity modelling (documents, biometrics, contact information)

  • Transaction flows with movement decomposition for complex payment scenarios

  • Digital access patterns (devices, IP addresses, sessions)

  • Account relationships and counterparty management

  • Comprehensive constraint definitions ensuring data integrity

Supported Use Cases:

  • Transaction monitoring and AML compliance

  • Entity resolution across customer touchpoints

  • Synthetic identity fraud prevention

Extensions

Fraud Event Sequence Data Model

Extension of Transaction and Account Data Model

This model extends the base Transaction and Account Data Model above with event-specific nodes and relationships. You must implement the base model first before using this extension.
Fraud Event Sequence Data Model Diagram

Key Features:

  • Adds event nodes (Connection, ChangePhone, ChangeEmail, ChangeAddress, AddExternalAccount, Transfer)

  • Chronological event sequencing with :NEXT relationships

  • Tracks old and new values during account takeover scenarios

  • Links events to existing Session nodes from base model

  • Maintains full compatibility with base model queries

Supported Use Cases:

  • Real-time fraud pattern detection through event sequences

  • Account takeover investigation acceleration

  • Weak signal detection in rapid event sequences

  • Suspicious activity timeline reconstruction

  • Event-driven alert generation

Using These Models

Each data model includes:

  1. Node and relationship definitions with complete property specifications

  2. Constraint and index recommendations for performance and data quality

  3. Executable demonstration code for testing and validation

  4. Integration guidance for connecting to existing systems

  5. Query patterns for common business scenarios

These models can be implemented directly or adapted to fit your specific data sources and business requirements.