Transaction monitoring
Rules, thresholds and segmentation decide what the system sees. Where scenarios were inherited from a vendor and never tuned to the customer base, alert quality suffers and genuine risk hides inside the noise.
TECHNOLOGY, DATA & DIGITAL GOVERNANCE
Govern the Systems That Increasingly Govern the Business.
EGRC provides GRC technology advisory, RegTech advisory, data governance, cybersecurity governance and AI governance services.
01 / REGTECHSystems advisory
02 / DATAGovernance & privacy
03 / CYBERGovernance
04 / AIGovernance
THE SHIFT
The system is not the control.
Compliance increasingly runs inside software. That makes configuration, data quality and change control governance questions rather than IT questions.
Govern the systems that govern the business.
Rules, thresholds, workflows, access and data all encode policy decisions. EGRC reviews them the way an examiner would — by asking who decided, on what basis, and how it was tested.
SYSTEMS IN SCOPE
Four systems that carry most of the risk.
These platforms make or shape compliance decisions every day. Each needs documented configuration, owned data and evidence that it was tested.
Sanctions and PEP screening
List scope, matching logic, secondary identifiers and whitelisting all sit behind a screening decision. Each is a configuration choice that should be documented, tested and owned.
KYC and onboarding platforms
Automated verification, document capture and risk scoring encode policy in software. When policy changes and the platform does not, the control silently drifts away from the documented standard.
Reporting and case management
Investigation records, decision rationale and regulatory submissions are the evidence layer. If a case cannot be reconstructed later, the underlying control cannot be demonstrated either.
CONTROL EXPECTATIONS
What a reviewer expects to find.
The difference between a system that supports a defensible framework and one that undermines it is usually governance, not technology.
| Capability | Frequently found | Expected standard |
|---|---|---|
| Configuration | Vendor defaults, undocumented | Documented rationale for every rule and threshold |
| Change control | Ad hoc changes by administrators | Approval, testing and audit trail for each change |
| Data quality | Unvalidated feeds, silent failures | Completeness and accuracy checks with alerting |
| Model testing | Never tested after go-live | Periodic tuning and above/below-the-line testing |
| Access | Broad administrative rights | Least privilege with periodic recertification |
| AI use | Undocumented, no human oversight | Inventory, risk classification and human review points |
SCOPE OF SUPPORT
Where EGRC works.
From selection and implementation support through to independent review of systems already in production.
GRC Technology Advisory
RegTech Advisory
Compliance Technology Implementation
AML Systems Advisory
Transaction Monitoring Systems Advisory
Sanctions Screening Systems Advisory
Data Governance
Data Protection & Privacy
Cybersecurity Governance
AI Governance
Digital Transformation Advisory
COMMON QUESTIONS
Questions about technology and compliance.
The issues that come up most often when compliance technology meets regulatory expectations.
We bought a compliance system. Is that not the control?
The system is the mechanism; the control is the configuration, the data feeding it and the human judgement applied to its output. Regulators and auditors generally ask why a threshold is set where it is, who approved it, when it was last tested and what happened to the alerts it produced. A system cannot answer those questions on its own.
How do you review a transaction monitoring system?
EGRC looks at coverage first — whether the scenarios reflect the products, channels and customer types actually in the business — then at the data feeding the system, the segmentation and thresholds, alert handling and closure quality, and the governance around changes. The output is a set of specific tuning and control recommendations rather than a generic assessment.
What does data governance mean for a compliance function?
It means knowing where the data used for compliance decisions comes from, whether it is complete and accurate, who may change it, and what happens when a feed fails. Most system failures EGRC sees are not logic failures but data failures — a field that stopped populating, a feed that silently broke, or a reference table nobody owned.
How should we govern our use of AI?
Start with an inventory of where AI or automated decision-making is actually used, classify each use by the impact of an error, and define human oversight, testing and documentation proportionate to that risk. For compliance uses specifically, be able to explain how a model contributed to a decision, and retain enough record to reconstruct it. Governance should also cover vendor-supplied AI features enabled inside existing systems.
Do you implement systems or review them?
EGRC works from a governance, risk and control perspective rather than as a systems integrator. That means supporting selection and implementation with control requirements, reviewing configuration and data, and testing whether the technology delivers the compliance framework it was bought to support — independent of the vendor.
START WITH CLARITY
Discuss your digital governance requirements.
Speak with EGRC about RegTech, AML and screening systems, data governance and AI governance.