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PRAXORA LAB
WORKSHOP BRIEF

Half-day course · 05

AI-Driven AML & Financial Crime Detection

A 3.5-hour session for compliance, risk and MLRO teams evaluating AI-driven anomaly detection for AML and KYC workflows. Facilitated by Jason Lee, Designated MLRO and CAMS/CFCS certified.

Duration

3.5 hours, single session

Format

In-person or virtual

Cohort size

Max 20 participants

Requires

One real AML, sanctions or KYC workflow

Facilitator

Jason Lee

Credentials

Designated MLRO, CAMS, CFCS

CPD / CPE hours

4 CPD hours

Certificate

Certificate of Completion, Praxora Lab

What you leave able to do

  1. Evaluate a transaction-monitoring or KYC workflow for AI and machine-learning anomaly detection.
  2. Work through real RegTech integration patterns, Chainalysis, Elliptic and ComplyAdvantage among them.
  3. Map integration options directly onto the room's own workflow.
  4. Build an audit-readiness checklist for what a MAS inspection actually checks.
  5. Leave with a drafted implementation note a compliance function can act on.

Who should attend

  • MLROs and compliance officers at MAS-regulated banks, payment institutions and fintechs.
  • Risk and financial-crime teams evaluating a RegTech platform.
  • Teams preparing a workflow for a MAS inspection.

Four segments across 3.5 hours

  1. 20 min

    Framing

    Output: Workflow brief

  2. 55 min

    RegTech integration patterns

    Output: Integration options mapped to the workflow

  3. 1 hr

    MAS-facing audit readiness

    Output: Audit-readiness checklist

  4. 1 hr

    Close

    Output: Implementation note

Investment

Open cohort: on enquiry, per participant, max 20 participants.   Corporate in-house: on enquiry, fixed fee, group rates with AI Governance & Compliance for Regulated Industries.