Delivery Hero’s GitHub-Vertex AI Voucher Fraud Detection
Fraud detection models must be redeployed often to combat human opponents that may reverse-engineer fraud engine logic and change their methods
At Delivery Hero, a prominent local delivery platform, the Incentive Fraud team builds ML-powered, rule-based services to identify and prevent incentive voucher fraud
These coupons can be given to those who have just registered to encourage users to use the delivery food platform, therefore it should be able to distinguish new clients from those making new profiles for each order
The team uses a REST API services with rule-based logic and integrated ML models to make choices. Since the API is utilized on each meal order, latency is tight
Vertex AI was chosen for its ML model creation environment due to its scalability and close connection with BigQuery, Delivery Hero’s primary data warehouse, as well as additional Google Cloud resources
The team’s Python library ml-utils enabled ML Operations processes for the Incentive Fraud use case utilizing the GCP Vertex AI Model Registry at the backend
After all Vertex AI pipelines succeed, the GitHub Actions task that initiated them queries the Vertex AI Model Registry to get evaluation metrics and prints them as markdown to the job Summary page