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Brisbane, Australia
February 2026
8 min readWorkflow Demo

LexAML: Client Onboarding, KYC & AUSTRAC Compliance

How GetPost Labs would build the AML/CTF compliance officer's workflow: new clients' identity documents, ownership and screening results read by AI agents, risk ratings and record keeping held by rules, and every higher-risk client decided by your compliance officer. The AUSTRAC record builds itself on the same trail.

Conceptual Prototype — Illustrating our approach
Lex-AML is a live GetPost Labs product for AML/CTF compliance. See how it was built →

Executive Summary

The Problem: Every new client has to be identified, screened for sanctions, politically exposed persons and adverse media, risk-rated and recorded before the work starts — and the Tranche 2 reforms bring more accounting and professional firms under the AML/CTF Act. The information arrives as scanned IDs, trust deeds and company extracts, so it is read, re-keyed and cross-checked by hand.

The Solution: LexAML gives the reading and screening summaries to AI agents, keeps the risk rating, record keeping and review dates as fixed rules in software, and leaves every higher-risk client and every reporting decision with the compliance officer. Onboarding, screening and the AUSTRAC record sit on one file.

The Outcome: The compliance officer reviews the clients that need judgement instead of re-keying every file, partners take on work knowing the checks are done, and each client keeps its own audit trail.

1

The Challenge

Understanding the problem space

"Conduct KYC, CDD and ECDD reviews, including beneficial ownership, PEP, sanctions and adverse media screening"

— A duty listed in a current Australian compliance officer job ad (SEEK, September 2026)

Onboarding and screening are the core of the role. Across 16 current AML compliance officer and client onboarding ads, the same duties come up again and again: onboard new clients, run KYC and customer due diligence, review higher-risk customers, maintain compliance records and registers, and assist with AUSTRAC reporting.

Most of that work is cross-checking information that already exists somewhere else — the ID documents, the company or trust structure, the screening results, the firm's own AML/CTF programme. When it lives across Xero Practice Manager, email and a spreadsheet, every file is assembled by hand, and one missed beneficial owner or out-of-date review becomes a gap an auditor will find.

11 of 16
ads mention AML/CTF
9 of 16
ads mention client onboarding
6 of 16
ads name AUSTRAC

Source: 16 AML compliance officer and client onboarding job ads in Australia on SEEK, September 2026. Employers not named.

2

The Solution

What GetPost Labs would build

Core Capabilities

Document Reading (AI agent)
Reads IDs, company extracts and trust deeds, and pulls out the directors, trustees and beneficial owners
Screening Summaries (AI agent)
Summarises sanctions, PEP and adverse-media results in plain language, separating likely matches from false positives
Risk & Record Rules
Risk rating from your AML/CTF programme, record keeping and review dates applied by fixed rules, not AI
Higher-Risk Clients Stay With People
The compliance officer decides every higher-risk client and every report to AUSTRAC; the agent prepares, never decides
Enhanced Due Diligence Drafts (AI agent)
Drafts the source-of-funds and source-of-wealth questions and the case summary for the officer to review
AUSTRAC-Ready Record
Identity, screening, risk rating, decisions and ongoing reviews kept together for audit
3

Where the Time Comes Back

Judgement, not data entry

The compliance officer stops assembling each client file by hand and starts reviewing what the agent has flagged:

Beneficial Ownership

Before

Open the company extract and the trust deed side by side, trace who ultimately owns or controls the client, type it into the file.

After

The agent has drawn the structure and listed the beneficial owners with the page each came from. The officer checks it, not builds it.

Sanctions, PEP & Adverse Media

Before

Run each name through screening, read every possible match, write up why each one is or is not your client.

After

The agent summarises each result and flags the ones that look real. The officer decides; the reasons are saved with the file.

Records & Ongoing Reviews

Before

Keep a spreadsheet of when each client was last checked and hope the next review is not missed.

After

A rule sets each client's review date from its risk rating, re-screens on schedule and keeps every record for the retention period.

4

BPMN Workflow

The business process modelled

New Client: Enquiry to Onboarded

ClientAI AgentRules in SoftwareCompliance OfficerNew clientProvide ID & DocsRead & ScreenRisk RatingDraft ECDD FileReview Higher RiskAccept or DeclineRecord & MonitorOnboarded
Client
AI Agent
Rules in Software
Compliance Officer
AI agent task
Rule in software
Person
5

User Journey

A New Client, Enquiry to Onboarded

Scenario: An accounting firm takes on a new client: a family trust with a corporate trustee, buying an investment property.

1
ClientProvide ID & Documents

Uploads the directors' IDs, the trust deed and the company extract through the onboarding portal

2
AI AgentRead & Screen

Reads the documents, lists the trustee directors and beneficiaries, and summarises the sanctions, PEP and adverse-media results. Flags one director as a possible PEP match

3
Rules in SoftwareRisk Rating

Applies the firm's AML/CTF programme: a possible PEP match and a trust structure rate the client as higher risk, so it cannot proceed without the compliance officer

4
AI AgentDraft ECDD File

Drafts the source-of-funds questions for the property purchase and a one-page case summary with every source linked

5
Compliance OfficerReview Higher Risk

Confirms the PEP match is a different person with the same name, and reviews the client's answers on the source of funds

6
Compliance OfficerAccept

Accepts the client with a note of the reasons. The partner is told the engagement can start

7
Rules in SoftwareRecord & Monitor

Identity, screening, rating and decision kept on one record, with the next review and re-screening dates set

Outcome: The client is onboarded with every check, flag and decision on one record. The agent prepared it; the compliance officer decided it.

6

Interactive Prototype

Functional dashboard demonstrating the concept

LexAML
LexAMLKYC Dashboard

KYC Client Dashboard

Real-time client verification status • AML/CTF Tranche-2 Compliant

100% Compliant
24
Verified Clients
3
Pending KYC
1
High Risk
8 min
Avg KYC Time
↓ was 2+ hours
Client Register
Search clients...
Client IDNameTypeRiskKYC StatusLast CheckAction
CLI-1247Acme Corporation Pty LtdCorporateLowVerifiedToday
CLI-1246Smith Family TrustTrustLowVerifiedToday
CLI-1245Johnson, Michael R.IndividualMediumIn ProgressPending
CLI-1244TechStart InnovationsCorporateLowVerifiedYesterday
CLI-1243Oceanview HoldingsCorporateHighReviewFlagged

© 2026 GETPOST Labs. Full Stack Engineering Solutions.

Functional prototype. Click on cells and entries to see interactions.

7

System Context

Where LexAML fits in the ecosystem

SYSTEM INTEGRATIONPractice Manager (XPM)Client recordsEngagementsDocumentsAPILexAML• AI document reading• Risk & record rules• Audit trailAPIID & ScreeningIdentity checksSanctions & PEPAdverse mediaAPIAUSTRACEnrolmentReportsRecord requests

Have a Similar Problem?

This is the kind of workflow automation GetPost Labs builds. If your organisation has similar challenges, we'd love to discuss how a custom solution might help.