If you're looking for a more complete solution to automate anti-money laundering (AML) and fraud detection, Nasdaq Verafin is a good option. It pools data from hundreds of institutions for better security and efficiency. The platform combines machine learning and consortium analytics to spot payment pattern anomalies and to monitor for AML and counter-terrorism financing (CFT). It also has high-risk customer management with automated segmentation, risk stratification and surveillance, and secure 314(b) information sharing for joint investigations.
Another strong option is ComplyAdvantage, an AI-based fraud and AML risk assessment platform. It automates time-consuming processes to reduce false positives and optimize compliance workloads. The platform spots fraud and suspicious transactions in real-time, monitoring hundreds of known typologies and trends in customer transactions. It offers real-time transaction monitoring and a calibrated risk approach, ensuring better compliance efficiency and better security that adheres to FATF guidelines.
SEON is another contender, with sophisticated digital footprinting, machine learning and customizable rules to stop fraud and money laundering. The platform offers real-time user activity monitoring, AI-powered insights for better fraud detection and streamlined compliance processes. SEON is designed for a range of industries and can be integrated through APIs or the AWS Marketplace, so it's a good choice for businesses of all sizes.
Last, Flagright is notable for its AI-native AML compliance and fraud prevention platform. It includes automated case management, AI-based risk scoring, real-time transaction monitoring and customer risk assessment. Flagright uses advanced AI algorithms to spot complex patterns, and it can help with AML compliance and fraud prevention. It can cut hours spent on manual tasks, false positives and productivity, making it a strong choice for fintechs and financial services companies.