Control testing
Scalable second-line control testing with AI agents
Agent Workforce executes defined control tests for second-line risk and compliance teams. The AI agents run each test and hand back a traceable result. Your people make the call.
Evidence-heavy control tests still run periodically, by hand
Whether a control sits in credit, operations or compliance, its evidence is spread across documents, records and systems. It rarely arrives in a consistent format. Each test takes days of skilled work, so the calendar decides what gets tested.
Conclusions often rest on periodic testing and limited samples. That leaves material gaps between testing cycles.
Coverage is set by capacity
Faster management decisions based on broader risk-based coverage
Tests run in hours
A defined control test runs in hours rather than days of manual effort. Many tests can run in parallel.
Issues surface sooner
Once results are validated, tests can run more often. Your risk function can investigate exceptions before the next scheduled cycle.
Repeatable in execution
The AI agents follow your approved method the same way on every run, whatever the day or hour. They record the evidence, steps, variations and exceptions for review and re-performance.
Half the deliverable is the test result. The other half is its audit trail
The AI agents read the agreed evidence package, apply your approved test design and propose a source-backed result.
They record missing evidence, contradictions and exceptions, and escalate them to your people.
Cora runs every test. Your methodology and risk tolerance set the confidence level at which it proposes a conclusion. Below that level, it hands the case to your experts.
- Evidence processing
- Data reconciliation
- Criteria evaluation
- Exception analysis
- Work paper production
Every completed test hands back
The evidence tested
Every document and record the conclusion rests on.
The test criteria
Your test script and thresholds, taken from your methodology.
The steps taken
In order, so a tester or auditor can re-perform the test.
The exceptions
What did not pass, raised for a human decision.
A confidence-scored result
Pass, fail or exception, with its confidence score and the evidence attached.
Collect the evidence, execute the control test end-to-end, hand out confidence-scored results
- Cora checks that the evidence is readable and sufficient to answer each question.
- It runs the full test and flags gaps as it goes. Unreadable or missing evidence goes back to its owner with a specific request.
- Cora performs all tests to all documents and categorizes them for passes, cases for a person, and failures
- Cora traces a failure and presents the reason.
The AI agents perform the test, and your people keep the accountability
The AI agents are onboarded like new testers and follow your methodology. Raw evidence can stay in your environment, and only minimised context reaches the AI agents. Your evidence is not used to train or fine-tune models, and every action the AI agents take is logged.
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Validated against your testers
Your testers compare the AI agents’ results with human results test by test before coverage expands.
Thresholds you set
Below your confidence threshold, the AI agents escalate to your experts.
Measured against a benchmark
We measure the AI agents’ results against a benchmark set your people have reviewed, so you know when a result needs re-checking.
Oversight follows the risk
During validation, your people review every result. At scale, exceptions and uncertain cases always get human review, and the rest are covered by sample re-performance and test-cycle approval.
Test the full population and show evidence behind every result
Financial crime
Customer risk classification
Periodic KYC reviews
Transaction monitoring
Handling alerts
Operational resilience
Incident reporting
Recovery testing
Access reviews
Change approvals
Third party risk
Provider register
Onboarding due diligence
Contract clauses
Exit plans
Customer risk
Risk classification
Customer due diligence
Beneficial ownership
Customer offboarding
Governance
Policy reviews
Risk appetite breaches
Delegated authority
Issue remediation
We own the execution of critical business processes
For ten years we have run business-critical automation for regulated organisations. The same governance, monitoring and operating discipline now runs our AI agents.
AI agents matched the human testers and caught what they missed
Agent Workforce executed a defined control test for a European asset-finance lender, using the lender’s existing evidence, criteria and output format. The lender tests controls across many regions and has a dedicated second-line risk function.
On the evaluated cases, the AI agents reproduced the agreed findings and identified additional exceptions for human review. Execution time fell from days to hours.
That gives the lender a validated basis for scaling to more controls and test variants, and from samples toward full-population testing.