README.md

metadata

title: VynFi Fraud-GNN Demo
emoji: 🛡️
colorFrom: red
colorTo: indigo
sdk: gradio
sdk_version: 5.5.0
python_version: '3.11'
app_file: app.py
pinned: true
license: apache-2.0
short_description: GraphSAGE fraud + GAE anomaly on synthetic JE network
tags:
  - vynfi
  - graph-neural-network
  - fraud-detection
  - anomaly-detection
  - synthetic-data

🛡️ VynFi Fraud-GNN Demo

Interactive inference Space for the VynFi/je-fraud-gnn model bundle.

Three tabs

• Edge fraud predictor — pick a curated sample (clear fraud / clear normal / borderline) or build your own edge from any of the 499 GL accounts in the published COA. Returns fraud probability + anomaly MSE.
• Node anomaly explorer — top-K accounts ranked by GAE reconstruction error on a 5,000-edge sample; surfaces accounts whose attribute patterns don't fit the structural prior.
• Live evaluation — sample N edges from VynFi/vynfi-journal-entries-1m, run the classifier, render confusion matrix + ROC against ground truth.

Tech

• Gradio + torch-geometric + pandas + matplotlib
• Loads model bundle from VynFi/je-fraud-gnn at cold-start (cached after).
• Loads dataset slices from VynFi/vynfi-journal-entries-1m on demand.

Source

• Engine repo (spaces/fraud-gnn-demo/)
• Model card — full training details, metrics, and honest discussion of where GNN helps vs LR baseline.
• Companion paper (SSRN)

License

Apache-2.0.