Question: I'm looking for a solution that uses AI algorithms to detect and prevent financial crime in real-time.

If you need a powerful system to spot and stop financial fraud in real-time, Nasdaq Verafin is a top contender. The all-purpose system collects data from hundreds of customers for better security and efficiency. It combines machine learning and consortium analytics to spot payment pattern anomalies, manage anti-money laundering (AML) and counter-terrorism financing (CFT), and oversee high-risk customers. By cutting down on false positives and speeding up investigations, Verafin helps financial services companies meet regulatory requirements.

Another contender is Flagright, an AI-native system for AML compliance and fraud prevention. It includes real-time transaction monitoring, AI-based risk scoring and automated case management. Flagright is designed to help fintechs and banks meet AML compliance and fraud prevention needs with a lot less manual work, with a big reduction in false positives and a boost to productivity.

If you want something a bit more specialized, Sardine is focused on fraud prevention and compliance with deep device intelligence and behavioral biometrics. It includes tools for identity fraud prevention, account takeover, payment fraud and anti-money laundering, along with customizable rule sets and data enrichment. Sardine's machine learning models predict fraud with high accuracy, and the system is designed to be easy to integrate and maintain.

Last, SEON has a fraud prevention and AML compliance system that uses digital footprinting and machine learning to stop fraud and money laundering. It's got features like real-time user activity monitoring and AI-powered insights, and it's designed to be a scalable system for companies large or small. That means it can automate fraud checks and keep up with regulatory requirements with less work.