Project AURIONAI Use-Cases Research & Innovation
tabular

Anti Money Laundering AI (AML AI)

Google Cloud AML transaction monitoring model co-developed with HSBC; HSBC reports 2 to 4x suspicious activity found and 60% fewer alerts.

GoogleGoogleUSAHSBCHSBCUK
Google
Levelmodel
Classtabular
Parametersnot in the notes
Contextnot in the notes
Releasednot in the notes
Opennessproprietary
Runs onnot in the notes
Statusnot in the notes

Industry Use Cases

Finance
AML transaction monitoring and suspicious account detection

R&D Topics

Fraud and outlier detection on transaction dataexemplar

Deployments

HSBC
HSBCproductionUK and Hong Kong30 Nov 2023

HSBC-reported: 2 to 4x suspicious activity found, 60% fewer alerts, detection 8 days after first alert (12 months post go-live vs prior 12 months); Celent Model Risk Manager of the Year 2023

AML transaction monitoring and suspicious account detectioncompany statementcloud.google.comservices.google.com
Where this comes from
From G13, the deployment rows of T08 to T10, and the Indonesian-language search of 11 October 2026. An outcome claim is the organisation's own unless the evidence type says independent report.

Identity

Developer
Google, HSBC
Family
not in the notes
Released
– sources
Weights published
–
Record checked
10 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
other Proprietary ML risk scoring
Total parameters
– sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
not in the notes
Output
not in the notes
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
proprietary
Licence
Proprietary sources
Access routes
API
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
not in the notes
Footprint
Managed cloud service
Runtimes
not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Benchmark Results

The notes record no benchmark result for this model.

Lineage

The notes record no lineage for this model.

Sources

  1. How HSBC fights money launderers with artificial intelligence | Google Cloud Blog cloud.google.com https://cloud.google.com/blog/topics/financial-services/how-hsbc-fights-money-launderers-with-artificial-intelligence
  2. services.google.com/fh/files/misc/hsbc_celent_model_risk_manager_... https://services.google.com/fh/files/misc/hsbc_celent_model_risk_manager_of_the_year_2023.pdf

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Anti Money Laundering AI (AML AI)", https://aurion.semai.id/models/google-aml-ai/, records of October 2026.