Simulation Training
Build analyst judgement before live risk
Our Simulation training gives analysts a safe environment to practise realistic financial crime decisions before they take ownership of live work. Analysts review simulated cases, investigate evidence, apply policy logic, choose an outcome, submit rationale, and receive feedback on their decision.
You can use our simulation training to:
Train analysts on realistic financial crime cases.
Build judgement before live exposure.
Test action, rationale, evidence, links, and case handling.
Track readiness by analyst, scenario, outcome, and handling time.
Target training where analysts need more support.
Simulation Training acr0ss Fincrime Work
SAR Writing
Case Simulation
EDD
Transaction Monitoring
Screening CCD
Financial crime training is too far from the real job
Most analyst training still depends on policy documents, classroom sessions, shadowing, and gradual exposure to live work. That creates a gap between knowing the process and applying it under pressure.
In real casework, analysts need to interpret incomplete facts, investigate supporting evidence, apply decision logic, select the right action, document the rationale, and do it quickly enough for an operational environment.
That gap is getting harder to close. True positives are rare, so analysts may not see enough genuine risk early in their development. At the same time, AI is taking on more repetitive junior work, reducing the live case volume that historically helped analysts build judgement.
Our simulation training gives teams a way to create that experience deliberately, safely, and repeatedly.
Realistic cases that analysts cannot simply memorise
Our training simulators are designed to feel like casework, not a quiz.
Analysts move through the practical steps they would follow in a live environment, from case ownership through to investigation, decision, rationale, and closure.
The training is built around scenario-based learning.
Each scenario reflects a type of decision analysts may face in financial crime operations, using combinations of data points such as payment details, party information, name match strength, jurisdictional indicators, sanctions exposure, prior records, company information, bank details, and supporting evidence.
Cases can be randomised so analysts see new combinations of facts each time.
This prevents answer memorisation and forces analysts to apply judgement.
The training uses synthetic data, so analysts can practise with data points such as realistic names, transactions, account details, company records, sanctions-style profiles, aliases, locations, bank details, and supporting research outputs without using real customer data or live production cases.
What this gives teams
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Fresh practice cases without repeated answers.
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Safe training without exposing real customer or production data.
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Realistic material for analysts to investigate.
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Domestic and international case variants.
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More exposure to rare but important true-positive cases.
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Scenario packs that can focus on known training gaps.
Validation, feedback, and measurable readiness
The final action is only part of a good financial crime decision. A defensible decision also depends on the rationale, supporting evidence, links, documentation, and completion steps.
Simulation training can validate the full decision. It can check whether the analyst selected the right action, chose the right rationale, included all required reasons, attached the right evidence, used the correct link or URL, avoided irrelevant evidence, and closed correctly.
When a decision is wrong, analysts receive immediate feedback showing what they selected, what the correct action should have been, what rationale was expected, and what evidence or links were missing. Completed decisions remain available so analysts and team leads can review what happened and turn mistakes into coaching.
Dashboards give managers a clear view of readiness, including completed work, pass and fail rates, scenario-level performance, analyst-level performance, average handling time, historical outcomes, repeated error patterns, and progress over time.
This helps teams understand
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Who is ready for live work.
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Who needs more support.
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Which scenarios are causing the most difficulty.
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Whether errors are individual or repeated across a cohort.
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Where training should be targeted next.
Build stronger analysts, faster
Simulation training helps financial crime teams move from passive training to practical readiness. It gives analysts realistic experience before live exposure, gives team leads better coaching data, and gives QA teams a clearer way to calibrate decision standards.
Expected outcomes
Faster analyst readiness
Clearer QA and calibration
More consistent decision-making
Safer learning before live exposure
Stronger rationale and evidence quality
A stronger pathway from junior analysts to senior judgement
Better coaching conversations
Financial crime work is becoming more complex, more AI-enabled, and more dependent on high-quality human judgement.
Simulation training helps teams build that judgement deliberately, rather than waiting for experience to appear naturally in production.
