After two years of beta testing, Plaid’s machine learning tool Signal will be available to customers willing to upgrade their ACH transaction services with fraud detection
Plaid has announced that its machine learning (ML) risk assessment engine Signal is now widely available to all customers who wish to enhance the security of their ACH transactions. Previously, the tool has been in beta mode use by several Plaid customers for over a year. It currently protects nearly $1.5 billion in transactions every month.
Working on Plaid’s open banking platform, Signal operates similarly to risk and fraud detection tools on card networks and financial institutions. The engine offers real-time transaction analysis of ACH returns through data-insights pulled from Plaid’s network.
For each transaction, Signal analyses over 1,000 unique risk factors. After the analysis, it ranks transactions according to returns risk scores, tiers, and more than 60 other attributes for improved automation and faster, safer ACH.
Due to increased performance and precision, businesses can upgrade the user experience and boost conversion rates. More importantly, they can better predict and prevent risky and fraudulent transactions on their business platform.
Plaid’s new head of payments John Anderson stated that the tool helped an investment platform provide accelerated access to funds to 96% of their new users (the experience they previously didn’t have at all), with nearly no increase to its ACH return rate.