Announced details
Screening for invoice purchase factoring for freelancers, sole proprietors and SMBs, and fraud detection
Funding available in as little as 30 minutes (labol service overview)
Labol and the Tanaka Laboratory began joint research in March 2024. 株式会社アルバクロス, a shareholder of Labol, is supporting the project through its collaboration with Professor Tanaka. 株式会社 Delight Flow is supporting the project.
Professor Kenji Tanaka (田中謙司) is a professor at the University of Tokyo's Graduate School of Engineering and an adviser to 株式会社アルバクロス. 株式会社アルバクロス is a venture capital firm that invests in seed- and early-stage startups. 株式会社 Delight Flow is a startup led by a member of the Tanaka Laboratory that provides AI advisory services, systems development and AI training, with a focus on manufacturing and AI.
In this announcement the company addresses none of Contract Value / Offering price / Impact on Business Performance.
| Item | Details |
|---|---|
| Names of Products / Services Covered | labol, Fraud detection model |
| Counterparty | Tanaka Laboratory, Graduate School of Engineering, the University of Tokyo, Professor Kenji Tanaka (田中謙司), 株式会社アルバクロス, 株式会社 Delight Flow |
| Counterparty overview | Professor Kenji Tanaka (田中謙司) is a professor at the University of Tokyo's Graduate School of Engineering and an adviser to 株式会社アルバクロス. 株式会社アルバクロス is a venture capital firm that invests in seed- and early-stage startups. 株式会社 Delight Flow is a startup led by a member of the Tanaka Laboratory that provides AI advisory services, systems development and AI training, with a focus on manufacturing and AI. |
| Relationship with the Company | Labol and the Tanaka Laboratory began joint research in March 2024. 株式会社アルバクロス, a shareholder of Labol, is supporting the project through its collaboration with Professor Tanaka. 株式会社 Delight Flow is supporting the project. |
| Applicable area | Screening for invoice purchase factoring for freelancers, sole proprietors and SMBs, and fraud detection |
| Quantitative Effects | Funding available in as little as 30 minutes (labol service overview) |
Items this document does not state (12)
These are items the company does not state in this document. We do not leave them blank, nor fill them in from other sources or by inference.
The reasons the company gives
The company's own explanation, not something inferred from the numbers.The model is designed to train AI on the characteristics of forged invoices, detect suspicious data and automate verification procedures that were previously conducted through visual checks by staff. The company says preliminary validation demonstrated that the model could detect fraudulent samples with high accuracy, confirming its strong practical utility.