Catalog record · Fraud Detection & AML
Stage as of Sep 10, 2020 · historical report, not live reconfirmation.
GAN-enhanced financial crime detection
Vendor workflow source. A reviewed supplier account names the customer and workflow. Supplier attribution and deployment claims are not independent outcome validation.
Last researched Oct 26, 2026. Source access and reported stage are recorded below; deployment evidence does not establish ROI.
What the research supports
Semi-supervised deep-learning models improve fraud detection despite imbalanced transaction labels.
- Reported stage
- Production
- Technology
- Machine Learning
- Business function
- Middle Office
- Impact (legacy label)
- Not labeled
- Catalog date · unconfirmed
- Not reported
- Imported
- Oct 29, 2026
- Last researched
- Oct 26, 2026
Measures & evidence
No quantified measure recorded. This is a gap in the evidence, not a finding of no value.
Documented vendor relationships
No vendor relationship has been linked to this specific workflow in the curated overlay. This does not mean it was built without vendors.
See the company’s documented relationshipsDeployment evidence & limits
Vendor article dated 2020-09-10 says Swedbank deployed Hopsworks' GAN technique for fraud detection; this establishes historical production use. Status as of 2020-09-10.
Stage is as reported in the cited evidence. Current operating status has not been independently reconfirmed; the research date is an editorial review date.
Source is dated 2020-09-10; continued operation or unchanged architecture through the 2026 review date is not independently established. Historical vendor account, not proof of unchanged current architecture.
Source register
- Logical Clocks Introduces new Machine Learning Technique to Detect Fraud and Prevent Money Launderinghopsworks.ai · opens in a new tab
Hopsworks / Logical Clocks · vendor-case · full-text · Published 2020-09-10
Research lanes: europe_banking · Batch global-discovery-2026-10-26. Coverage and remaining gaps