AML transaction monitoring
POLARIS
Anyone can raise an alert.
Polaris raises alerts you can defend.
Legacy monitoring is good at raising alerts and bad at everything after. It floods the queue with false positives, scores cases without saying why, and runs on data too fragmented to trust.
So when the supervisor, internal audit, or the MLRO asks the institution to account for a decision, it often cannot. Under direct AMLA supervision, that gap stops being a nuisance and becomes a finding.
Polaris closes it. Every alert it raises arrives with its own reasoning attached, and the full record is written down as it happens, on sovereign European infrastructure.
The problem
AML is an operation.
Legacy tools treat it as an alert.
In a professional AML operation, raising an alert is a small part of the job. The cost, the inconsistency, and the regulatory exposure sit in everything around it: the data underneath, the triage, the investigation, the decision, and the evidence that has to survive a review.
Legacy transaction monitoring optimises the alert and leaves the operation to absorb the rest. When someone reviews your programme, that is exactly where they look, and it is where three weaknesses compound.
01
It buries risk in noise
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02
It scores without reasoning
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03
It trusts data it should not
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What makes Polaris different
Anatomy of a defensible alert
Polaris does not just hand your analysts a score. Every alert it raises arrives with the reasoning already attached, answering the questions a supervisor or auditor will ask before they ask them.
How Polaris works
From raw data to a record you can defend
One pipeline. At each stage the data changes state, and the reasoning is captured, not reconstructed afterwards.
01
Ingest and harmonise
Polaris connects to your source systems and normalises inconsistent formats into a single canonical model, using machine learning to resolve duplicates and match records. Detection runs on clean data, not raw exports.
02
Detect with models and rules together
Machine-learning models surface patterns that fixed thresholds miss; a transparent rule engine enforces the typologies and expectations you are required to cover. Neither runs as a black box.
03
Retrieve context
For each alert, Polaris pulls matching typologies, comparable prior cases, and applicable guidance from your own knowledge base, held inside the platform rather than sent to a third party.
04
Explain in plain language
Polaris writes the reasoning for each alert: the behaviour observed, the rule or model that contributed, the typology matched, and the specific transactions to review. Written for a human, not buried in a score.
05
Customer Experience Enhancement
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06
Record immutably
Every alert, decision, and action is written to an immutable audit trail: what was detected, which rule and model applied, how it was explained, who acted, and on what basis. Built for internal control, financial-crime reporting, audit, and supervisory dialogue.
Built for AMLA supervision
Defensibility is not a feature. It is the point.
The Anti-Money Laundering Regulation, the recast Directive, and direct supervision by AMLA raise the standard for what monitoring must demonstrate: a consistent methodology, explainable decisions, and a complete record. Polaris is built for institutions that will meet that standard in practice, not on paper.
It runs on sovereign European infrastructure through our partnerships with T-Systems and Gefion. Your data, your models, and your audit trail stay under EU jurisdiction, independent of the legal instability around transatlantic transfers. For a financial institution, that is the difference between an AML strategy you can defend in front of your supervisor and one you cannot.
Why it matters
Polaris does not replace your AML programme, your risk assessments, or your reporting obligations. It operationalises them, so monitoring becomes a governed, documented function inside your financial-crime framework rather than a black box you take on trust.
First line
Financial Crime Operations
From clearing noise to resolving risk
Prioritised alerts, retained case context, and explanations written for the analyst raise both throughput and the quality of what leaves the team. Investigators spend their time on genuine exposure, not on false positives, and every disposition is captured as it is made.
Second line
Financial Crime Prevention
A programme you can evidence
Consistent methodology across the book, transparent model and rule behaviour, and a complete record of how decisions were reached. The inputs for effectiveness reviews, model governance, and dialogue with the supervisor and AMLA are produced as the work happens, not reconstructed afterwards.
Third line
Internal Audit
Assurance you can test
An immutable trail of what was detected, which controls fired, how each case was explained, and who acted on what basis. Audit can trace any alert end to end and verify the operation holds up, rather than relying on assurances that cannot be evidenced.
For leadership
CFO & COO
Defensibility has a financial receipt
Fewer false positives is not only a control improvement. It is analyst hours returned. When the queue reflects risk instead of thresholds, and each alert arrives already explained, the time spent handling a case falls, and so does the cost of running monitoring at all. The same change that makes the operation defensible makes it cheaper to run, and both land in cost-to-income. The walkthrough puts a number on each against your own alert volumes.
Get started
See Polaris against your own alerts
We run a one-hour walkthrough of Polaris against your own alert volumes and typologies. You leave with a clear picture of your current false-positive load and how much of it Polaris removes. Contact us to schedule.