Fraudsters are always evolving their tactics, such as using AI and LLMs, to bypass detection. 

To combat fraud, Signifyd, an e-commerce fraud detection platform, uses ML to make instantaneous decisions on whether transactions — such as returns, chargebacks, and customer account creation — are legitimate.

Nathan Ackerman, SVP of Engineering & CISO at Signifyd, joined Tecton CTO Kevin Stumpf in a recent discussion to dive into the details of Signifyd’s platform, including: 

• The challenges they face iterating on a system that needs to continuously adjust to new types of fraud, such as scammers using LLMs to bypass gibberish detection

• How having more historical data and transactions they can use as reference improves their fraud detection capabilities — for example, Signifyd uses data from 600+ million global wallets to inform whether a transaction happening at any moment is legitimate or fraudulent

• How feature freshness managed by their feature platform allows the Signifyd team to focus on understanding trends and disrupting fraud rings, as well as enable increasingly faster fraud response

REGISTER FOR WEBINAR