Recording AI Suggestions and Human Compliance Decisions

Update note

Published as a new human-control guide for AI-assisted broker and compliance work.

Why this matters

ASIC places responsibility for compliant financial-services operations on licensees and their people; software does not inherit that authority. In evidence work, the critical distinction is between preparation and decision. AI may extract a date, propose a missing-information question or draft a case summary. A broker or compliance reviewer determines whether the source supports it and what should happen next. If the system collapses those stages, it becomes easy to assume that a polished draft was checked or that a low-confidence extraction informed the final client communication without challenge.

Key points to carry into the work

Use different data states for source fact, machine extraction, AI suggestion, human verification, decision and approval.
Keep the source excerpt or reference available so reviewers can inspect context rather than trusting an isolated generated statement.
Record accept, edit, reject and defer outcomes; silence or screen views are not approval events.
Require a separate authorisation step before any client communication, market instruction, compliance status or external action is released.

AI-to-human decision trail

01Set the task
02Preserve sources
03Record the suggestion
04Review the output
05Approve the decision
06Release the action

Build a reviewable AI decision trail

Define the permitted taskState whether AI may classify a document, extract candidate fields, identify possible gaps, summarise source material or draft text. Name prohibited outcomes such as certifying compliance, selecting a market, recommending cover or sending a message without approval. The boundary should be visible to the user performing the work.

Preserve the input contextReference the documents, records and relevant excerpts supplied to the model, including their versions and case permissions. Record the task instructions and material configuration where practical. Do not expose unrelated personal information merely to create a broader prompt.

Store the suggestion as provisionalRecord the generated output, time, service or model identity where available, confidence or uncertainty signal and any safety or quality warnings. Use language such as suggested, extracted or drafted. A generated answer should not overwrite the original source or a human-authored record.

Capture the reviewer responseName the person, role and review time. Record whether they accepted, edited, rejected or deferred the suggestion and preserve material changes. Where a reason is important—for example, the source was outdated or the question was not relevant—capture it so later reviewers can understand the judgement.

Separate decision from approvalA broker may make a case decision while a second person completes a required approval. Model those events separately with their evidence and status. Do not infer approval from workflow progression, a completed task or a user having permission to approve.

Gate the external actionBefore a proposal, disclosure, client response or market instruction leaves the workspace, verify that the required human decision and approval exist. Record the released version, authorised actor, destination and time. If the action fails, preserve the failure and reconciliation state rather than marking the case complete.

Where Insia fits

Insia Intelligence is positioned as an embedded copilot across Broker CRM, Quote Desk and Compliance Case Manager. It can assist with extraction, organisation, gap detection and drafting, while sources, uncertainty and status remain visible. Brokers and authorised reviewers verify facts, make decisions and approve outcomes. Intelligence is not a fourth standalone product, and availability follows the module using it. Compliance output remains a Draft Readiness Preview in private validation.

Keep the boundary clear. Insia Intelligence does not provide insurance or personal advice, certify compliance, decide suitability, select markets, make insurer decisions or take external action without approved human control. A record of AI use does not make the output correct. Brokerages must set permitted uses, access, review requirements, escalation, quality monitoring and retention rules appropriate to their responsibilities.

Checklist

Permitted AI task and prohibited outcomes defined
Source inputs and versions referenced
Suggestion stored as provisional
Named reviewer outcome and edits recorded
Decision and approval events separated
Released action tied to authorised version

Sources and scope

Sources support the external context in this guide. Current product capability and availability are explained on the linked Insia product page.

Common questions

Is clicking Accept enough evidence of human review?

Not necessarily. The workflow should identify what the person was expected to check and preserve the relevant source, reviewer, time and outcome. High-risk or regulated decisions may require a more explicit rationale or separate approval.

Should a rejected AI suggestion be deleted?

Usually it is useful to preserve a controlled record of the suggestion and rejection when they influenced the work, subject to the brokerage’s privacy and retention rules. The record can explain why the final output differs.

Can AI mark a compliance requirement complete?

It may propose that evidence appears relevant, but a responsible person should determine whether the requirement is satisfied. Insia does not claim that AI certifies compliance.

Put the context to work

Turn this evidence task into a visible case.

Discuss how the evidence, requirements and human decisions in this guide could become a reviewable Compliance Case Manager workflow. This starts a product conversation and does not guarantee pilot access.

Discuss Compliance Case Manager