AML/CFT compliance

Compliance risk assessment that keeps up with the law.

Move your firm-wide AML/CFT risk assessment off the spreadsheet and into a structured tool that stays current with the regulation — and can be produced to your supervisor at short notice.

One engine, four jurisdictions

Equal-weight frameworks — none privileged. Cited at statute and regulator level.

United Kingdom

MLR 2017 — FCA / HMRC

European Union

AMLR / AMLA

Canada

PCMLTFA / FINTRAC

Nigeria

MLPPA 2022 / SCUML & NFIU

Never silently stale

When the regulation moves, CleRisk flags the assessments that no longer match the current framework version, shows you what changed, and records the evidence that you responded.

See what changed

A plain-language summary of what moved in the framework and what to revisit.

Evidence you responded

Re-baselining re-stamps the assessment to the current version and writes an audit-trail entry.

AI that challenges your controls

AI analysis

RISK ASSESSED

Sanctions screening — false-negative drift after list updates

ORIGINAL MITIGATION

Ongoing monitoring of screening performance as per SOP.

SOP RESTATED AS MITIGATION

ISSUES IDENTIFIED

Business-as-usual monitoring presented as risk reduction
No false-negative target, so "performance" cannot fail
Match-rate drift after list updates is not measured at all

AI SUGGESTIONS

Set a false-negative ceiling (≤0.5%) validated against a reference sample set
Re-baseline the match-rate distribution after every list update
Alert when drift exceeds 10% — owner and escalation path named

Same challenge engine, MLR 2017 obligation set · assists, never certifies

The EU 2027 shift

The EU AML package — AMLR, AMLD6 and the Anti-Money-Laundering Authority (AMLA) — applies from 10 July 2027, with AMLA issuing technical standards through 2026. Spreadsheets will struggle to meet the new currency-and-production requirements. Get ahead of the shift with an assessment that stays current by design.

Built for scrutiny

SOC 2 (in progress), GDPR and secure data hosting, with data-minimisation applied before any AI processing — personal identifiers are stripped before analysis and never leave your trust boundary in the clear.

Turn your mandated assessment into something you can defend.