Description
Fraud.net's AI and Machine Learning Models provide a wide array of solutions for fraud detection and prevention. Utilizing artificial intelligence and machine learning, including deep learning and neural networks, along with its unique data science methodology, the tool delivers valuable insights for combating fraud.
It provides various application options such as 'Application AI' and 'Transaction AI' for fraud related to applications and transactions. The solutions also cover identity services and monitoring of banks, payment methods, email breaches, dark web, and ISP intelligence for diverse industries.
Additionally, it offers solutions for case management, analytics, and reporting. Security is enhanced through multi-factor authentication, social media intelligence, and continuous risk monitoring.
Understanding different requirements, they provide different solutions for various types of fraud including account takeovers, application fraud, business email compromise, collusion, and insider threats, among others.
Essential banking functions such as KYC/AML, payment fraud, and synthetic identity fraud are also part of their solution offerings, ensuring a comprehensive asset protection platform.
Available resources include case studies, fact sheets, industry reports, product release notes, webinars, podcasts, and a dedicated 'fraud dictionary' for extended learning.
Pricing Plans
Releases
Reviews
Pros & Cons
Pros
Deep learning techniques
Neural network abilities
Comprehensive fraud detection services
Cons
Proprietary data science methodology implemented
Emphasis on numerous types of fraud
Unclear adherence to data privacy rules
