AI-Assisted Complaints Analysis and Market Conduct Risk Scoring

Risk Assessment & Triage · Financial Services

What it collects that can identify you

About behaviour

Pseudonymous data

Consumer complaints data submitted to FCAC — records of what financial consumers experienced and reported regarding the conduct of financial institutions. May include details about specific transactions or interactions.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Run by: Financial Consumer Agency of Canada (FCAC)
Where: No fixed location
Kept: Not stated by the Helpful Places.
Shared with: Accountable organization
Your copy: You cannot see the data it holds about you. What you can do

What it is for

Risk Assessment & Triage

Financial Services

This system uses large language models to analyse consumer complaints data collected by the Financial Consumer Agency of Canada, and to build a risk model that helps supervisors identify which financial market participants warrant closer scrutiny. It is used exclusively by government employees as part of a risk-based supervision strategy. Members of the public whose complaints inform the model are not directly exposed to automated decisions; rather, the outputs guide internal supervisory priorities.

What it collects and what happens to it

Data taken in

About behaviour

Pseudonymous data

Consumer complaints data submitted to FCAC — records of what financial consumers experienced and reported regarding the conduct of financial institutions. May include details about specific transactions or interactions.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Processing

Language Models

Large language models (LLMs) hosted on AzureML are applied to consumer complaints text to identify themes, risks, and patterns relevant to market conduct supervision.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Classification & Prediction

The Market Conduct Risk Model classifies and scores financial market participants based on complaint-derived features, producing risk tiers that guide supervisory prioritisation.

Government of Canada AI Register — 2526-FCAC-ACFC-005

What it does

Deciding (Analytical AI)

Human decides

The Market Conduct Risk Model scores and ranks financial entities based on complaints patterns; government supervisors then decide which entities to scrutinise more closely.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Understanding (Semantic AI)

Human decides

Large language models are used to extract meaning, themes, and patterns from unstructured consumer complaints text, surfacing insights for human analysts.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Outputs

A recommendation or prediction

Anonymized data

Risk scores and rankings of financial market participants, produced by the Market Conduct Risk Model, used by government supervisors to prioritise their oversight activities. Outputs are advisory — human supervisors retain decision authority.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Run by

Financial Consumer Agency of Canada (FCAC)

Federal regulatory agency that deploys this system to analyse complaints data and support a risk-based supervision strategy for financial market conduct.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Built by

Microsoft Azure

Microsoft provides the AzureML platform on which the large language models are hosted and run. The system name directly references this cloud ML service.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization

Outputs and data are available to FCAC government employees only, as the system's primary users are identified as GC employees supporting internal supervision activities.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Not available to me

Members of the public whose complaint data feeds the model do not have access to the risk scores, model outputs, or internal supervisory assessments derived from their complaints.

Government of Canada AI Register — 2526-FCAC-ACFC-005

Stored

Stored on 3rd Party Cloud

Data and model outputs are processed and stored on Microsoft Azure cloud infrastructure (AzureML), which is a third-party cloud provider.
Duration: Not specified in source

Government of Canada AI Register — 2526-FCAC-ACFC-005

How to read the colours

Can it identify you?

Anonymized data: Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data: Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data: The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides: This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes: This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous: This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

Right to Algorithmic TransparencyThis system is listed on the Government of Canada's public AI Register, which provides general information about its purpose and use. Further details about the system's logic may be requested through Access to Information processes with the Financial Consumer Agency of Canada.
Right to Be Informed of AI UseConsumers who submit complaints to FCAC should be aware that complaint data may be used to train and inform AI systems supporting supervisory risk analysis. This disclosure is provided through the Government of Canada's public AI Register.

Risks and safeguards

Reputational harmFinancial institutions scored or ranked by the Market Conduct Risk Model may face reputational harm if risk scores are inaccurate, reflect biased complaint patterns, or are misapplied.Safeguard: The system supports human-led supervisory decisions — GC employees retain authority; outputs are advisory, not binding, reducing the likelihood of unchecked automated reputational damage.