Sensitive Transactions and Segregation of Duties – Real-Time Practical Detection
The Challenge
One of the greatest weaknesses in ERP management and financial control is segregation of duties (SoD).
Most organizations rely on theoretical checks: if a user has conflicting authorizations, it is assumed they carry a potential risk.
The problem is that potential risk does not necessarily mean actual damage, and as a result many SoD controls remain broad and ineffective.
In addition, in many organizations achieving optimal segregation of duties is simply impossible due to the size of the team or the company structure.
The Detelix Solution
Detelix focuses on practical monitoring of sensitive transactions. Instead of stopping at the identification of risky authorizations,
our system verifies whether conflicting activities were actually performed, which user executed them, with which supplier,
and in what context and at what time.
The level of accuracy is micro-personal. For example, if a user created a new supplier, entered a bank account,
and also recorded an invoice for that same supplier, the system will immediately trigger a focused alert for investigation.
This approach perfectly complements our advanced supplier payments monitoring and bank reconciliation solution,
creating a full financial control framework that leaves no room for fraud or hidden errors.
What Makes Detelix Different
Detelix enables the detection of actual violations, not just potential risks. Monitoring is continuous and not a one-time review.
Alerts are highly focused rather than noisy reports of generic risky permissions. Each alert directly links user actions to specific suppliers.
Value to the Client
Fraud is prevented in real time—before money leaves the organization. Management gains full transparency into who does what in the system.
False positives are dramatically reduced, so only genuine violations reach review. Above all, it provides peace of mind for executives, boards,
and stakeholders, supported by Detelix’s proven expertise in financial fraud detection.
