Detecting Fraud Across Sectors
How the Ministry of Justice Finds Patterns Without Sharing Personal Data
Pieter Den Dooven
CTO & Project Lead, mintBlue
Challenge
Online fraud costs the Netherlands an estimated EUR 2.4 billion annually. The signals to stop it exist, but they are locked inside separate organisations that cannot legally share them.
Solution
Fraud signals are converted into anonymous codes using advanced cryptography. The same person always generates the same code across all organisations, but the code cannot be traced back to a real identity.
Impact
- 12+Organisations in programme
- 0Personal data shared
- Cross-sectorPattern detection
Fraud Hides in the Gaps Between Organisations
Online fraud costs the Netherlands an estimated EUR 2.4 billion annually. The signals to stop it exist, but they are locked inside separate organisations that cannot legally share them.
- No mechanism to detect that multiple organisations are seeing the same fraud suspect
- Legal basis for cross-sector personal data sharing does not exist
- Data sovereignty concerns prevent simple data pooling
- Fraudsters exploit the gaps between sectors, operating undetected across jurisdictions
The Vision
“Enable cross-sector fraud detection without cross-sector data sharing. Every organisation keeps full sovereignty over their data while a cryptographic layer reveals convergence patterns that no single party could detect alone.”
Privacy-Preserving Convergence Detection
Anonymous Tokenisation
Fraud signals are converted into anonymous codes using advanced cryptography. The same person always generates the same code across all organisations, but the code cannot be traced back to a real identity.
Sector-Based Coordination
Market parties submit signals to sector coordinators, who aggregate within their sector. A mandated intermediary detects cross-sector patterns without seeing underlying data.
Convergence Detection
When multiple sectors flag the same anonymous token, the system detects convergence. Only then can authorised parties, with legal basis, request identity disclosure.
Immutable Audit Trail
Every action is logged on an immutable ledger. Full accountability for who accessed what, when, and why. GDPR Article 17 functional deletion built in.
Finding What No Single Party Can See
“The paradox of cross-sector fraud detection is that the data needed to catch criminals is exactly the data you cannot share. We built a system that resolves that paradox with mathematics instead of legislation.”
Pieter Den Dooven
CTO & Project Lead, mintBlue
Beyond Fraud Detection
The same architecture is designed to apply to any domain where multiple parties need to detect shared patterns without sharing data. From customs signals and organised crime indicators to AML reporting across jurisdictions. As more sectors connect, the network effect strengthens detection without increasing privacy impact.
Detect Patterns Without Sharing Data
See how convergence infrastructure enables cross-sector collaboration within existing legal frameworks.