Building Plaid's ML Fraud Detection Application, Signal

Watch this virtual fireside chat to explore best practices in designing and deploying ML fraud detection applications. 

Our guest speaker, Renault Young, a Software Engineer at Plaid, joined Kevin Stumpf, CTO and Co-founder of Tecton, to do a deep dive into Renault's experiences in designing and developing Plaid’s ML infrastructure for Signal, Plaid's payment fraud detection and prevention application.

In this chat, Renault and Kevin discussed:

• Overcoming the challenges faced during Plaid's quest for effective payment fraud detection, including how to solve for out-of-order transaction data
• Technical solutions they adopted, including a new ML platform that allows for generating training datasets and designed for feature freshness and seamless large-scale production
• The benefits derived from this new architecture—such as improved cost management, and better workspace and access controls—along with a look into future optimizations