Signifyd, an e-commerce fraud detection platform, uses machine learning and huge amounts of data to make instantaneous decisions on whether transactions-such as returns, chargebacks, and customer account creation-are fraudulent.
In this webinar, guest speaker, Nathan Ackerman, Senior VP of Engineering at Signifyd, and Kevin Stumpf, CTO and Co-founder of Tecton, dive into Signifyd’s fraud detection platform, including:
☑️ The challenges Signifyd faces iterating on a system that needs to continuously adjust to new types of fraud, such fraudsters using LLMs to bypass gibberish detection
☑️ How having more historical data and transactions Signifyd can use as reference improves their fraud detection capabilities-for instance, they use data from 600+ million global wallets to inform whether a transaction happening at any moment is legitimate or fraudulent
☑️ How feature freshness managed by Tecton allows the Signifyd team to focus on better understanding trends and disrupting fraud rings, and enable increasingly faster fraud response