DataVisor, an AI-powered fraud and risk platform, this week released its instant payments fraud prevention solution. Real-Time Payments Fraud Solution leverages account life-cycle signals, advanced machine learning techniques and prebuilt rules for real-time payments fraud scenarios. It allows financial institutions safely access instant payment technologies offered by The Clearing House and Zelle.
The U.S. real-time payments market is projected by some to grow at a compound annual rate of 10.12% from 2022-2027. That will bring an increased risk of payment fraud. Less time to complete payment means less time to detect fraud.
DataVisor said the Real-Time Payments Fraud Solution is developed on its existing fraud and risk platform, which leverages sophisticated machine learning techniques. It includes an open SaaS orchestration platform that supports easy consolidation and enrichment of data. Data Visor said it scales infinitely and enables FIs to react in real-time to fraud and money laundering activities. The product also incorporates unsupervised machine learning technology, advanced device and behavioral intelligence, powerful decision engine and graph-based investigation tools.
“DataVisor provides unparalleled security and peace of mind by protecting instant transactions, allowing financial institutions to confidently adopt real-time payments,” said Yinglian Xie, co-founder and CEO at DataVisor. “In today’s digitalized world, it is imperative to proactively tackle fraud in real time, as it evolves, and our solution is uniquely positioned to accomplish just that – all while boasting high approval rates and limited customer friction that help boost the customer experience and increase revenue growth.”
Real-Time Payments Fraud Solution includes turn-key, pre-built rulesets to protect against the most common real-time payments fraud scenarios. The company offers several pre-configured rulesets, hundreds of sophisticated rules and decision flows, including A2A, C2B, C2M, P2P, B2B, and B2C to cover various real-time payments fraud schemes, including account takeovers (ATO), business email compromise (BEC) scams, social engineering scams, and romance/elderly abuse.
“Proven and tested real-time payments fraud signals. DataVisor’s solution leverages a wide range of data and pre-configured fraud signals that have been extensively tested and proven in the real-time payments domain,” DataVisor said in a release. “These features are dynamically calculated in real-time during production, enabling the system to effectively identify suspicious behaviors such as abnormal velocity and out-of-pattern transactions.”
DataVisor’s Real-time Payments machine learning (ML) models include both supervised and unsupervised algorithms. The patented unsupervised solution scales to support more than 10,000 transactions per second and less than 200 milliseconds of latency.
Real-time intelligence offers stakeholders immediate alerts as fraud patterns change. Within minutes, staff can investigate fraud patterns, create new attributes, and deploy new rules on the platform, all without using any IT resources.
DataVisor orchestrates different data sources, such as call center activities, login activity and dark web data to provide the best decision based on a 360-degree view of each customer. When identifying a suspicious transaction, the platform may also request additional authentication methods, such as SMS in real-time, and even put the transaction on hold.
Real-time Payments Fraud Solution supports all existing real-time payments networks.