Configuration-as-Code (CaC) is the practice of managing system configurations through code rather than manual settings. Instead of relying on ad hoc changes in user interfaces, CaC stores configuration logic in files that can be version-controlled, tested, and audited.

For compliance and anti-money laundering (AML) contexts, CaC is valuable because it provides transparency, repeatability, and governance. When screening thresholds, alert workflows, or monitoring rules are stored in a structured, auditable format, firms can prove exactly how their systems were configured at any point in time, an expectation regulators increasingly emphasise.

Definition Of Configuration-as-Code

Configuration-as-Code refers to representing application or system settings in code-like formats that are maintained in repositories such as Git. This allows teams to apply software development practices like version control, peer review, and automated testing to system configurations.

For compliance, CaC means:

• Risk rules and workflows can be reviewed and updated transparently.

• Configuration histories are retained, supporting auditability.

• Deployments are standardised, reducing human error. 

CaC is related to Infrastructure-as-Code but focuses on business rules and system behaviour rather than servers or infrastructure.

Why CaC Matters In AML And Financial Crime Compliance

AML systems are complex, involving sanctions screening, customer due diligence, transaction monitoring, and alert adjudication. CaC principles support compliance by:

Transparency And Auditability

Configuration files provide a record of changes that can be retrieved and reviewed during regulatory audits.

Governance And Accountability

By treating configurations as code, firms can establish transparent and governed change processes that align with the FCA’s expectations for effective systems and controls, ensuring that configuration changes are traceable and subject to oversight.

Reducing Human Error

Manual configuration is error-prone. Code-based management reduces the chance of misapplied thresholds or misaligned workflows.

Faster Compliance Updates

When sanctions or regulations change, updates can be rolled out consistently across systems.

How CaC Principles Relate To Facctum

Configuration-as-Code is not a Facctum product in itself. However, Facctum solutions are built with configurable, transparent, and auditable controls that reflect the principles of CaC:

• FacctView, Customer Screening – configurable matching thresholds and screening logic, supported by governance workflows.

• FacctList, Watchlist Management – ensures data sources and lists are harmonised and managed consistently.

• FacctGuard, Transaction Monitoring – configurable detection rules and scenarios that can be adjusted as risks evolve.

• Alert Adjudication – audit trails for workflow changes and escalation paths, ensuring accountability.

These capabilities align with CaC principles by ensuring AML system configurations are traceable, reviewable, and consistent.

Challenges In Adopting CaC

While CaC provides benefits, financial institutions face adoption challenges:

Skill Requirements

Compliance teams may lack coding skills, requiring collaboration with IT or engineering.

Change Management

Transitioning from manual configuration to CaC requires cultural and operational shifts.

Integration Across Environments

Applying consistent configurations across hybrid systems (cloud and on-premise) can be complex.

Best Practices For CaC In Compliance

Organisations adopting CaC principles should:

• Use version control to store configurations securely.

• Require peer review and approval for configuration changes.

• Implement automated testing to validate that new rules behave as expected.

• Align CaC with governance frameworks so access and approval are role-based.

• Integrate configuration history into audit and reporting processes.

The Future Of Configuration-as-Code In AML

As compliance becomes increasingly data-driven, CaC principles are expected to move from an efficiency practice to a regulatory expectation.

• Regulatory Alignment: Supervisors will want evidence of how systems were configured at specific points in time.

• Explainable Configurations: Code-based rule management will improve explainability for regulators and auditors.

• Integration With AI: Combining CaC with AI models will make both rules and algorithms more transparent.

• Operational Resilience: CaC supports resilience by enabling fast, consistent system redeployments after disruption.

Firms that embed CaC principles in their AML frameworks will be better positioned to meet regulator demands for transparency and accountability.