Grab’s Trust, Identity and Safety team detects fraud by deploying data science, analytics, and engineering platform to search for anomalous and suspicious transactions, or by identifying high-risk individuals who are likely to commit fraud. The team builds tools for managing data feeds, creates SDK for engineering integration, and builds rules engines and consoles for fraud detection. An example of fraudulent behavior could be that of an individual who pretends to be both the driver and passenger, and makes cashless payments to get promotions. Recently, the team launched GrabDefence as a SaaS service to start helping external clients in Southeast Asia to combat fraud in their business. Billions of fraud and safety detections are performed daily as there are millions of transactions happening every day and thus storing and querying the data of a database in real-time is not feasible. So come listen to us how we use Apache Kafka to detect fraud successfully.