Account Protection
Watch for Threats.
Build Trust.
Detect and prevent account theft attempts preemptively. Monitor every user interaction to safeguard and retain customers.
Device Intelligence
via Digital Trust
Track changes in different devices, different locations, different IPs and many more. Data is processed in real-time and validated against many factors. Identify the counterparty in transactions and assure a safe and trustworthy process.
Behavioral Biometrics
via Digital Trust
Evaluate the behaviors that customers develop over time. Biometric approaches can help determine whether the user is logging into a legitimate account or if their behavior matches that of a fraudster.
Link Analysis
via Graph Intelligence
Visualize the relationships between financial actors like individuals, accounts, transactions, or devices. Reveal connections that appear anomalous which may indicate potential fraudulent activity. Focus on high-risk transaction patterns and save time.
Transaction Pattern Analysis
through Holistic Approach
Analyze transaction patterns to detect anomalous activities and prevent account theft attempts. Block the suspicious activities that drastically diverge from the patterns.
Frequently Asked Questions
Account protection refers to the set of security measures designed to prevent unauthorized access, account takeover attempts, and fraudulent activities. It continuously monitors user interactions, login behavior, and device signals to detect suspicious activity and ensure that only legitimate users can access their accounts.
Device intelligence analyzes signals such as device type, IP address, location changes, and browsing patterns to detect anomalies in real time. If a login attempt appears unusual compared to historical behavior, the system can trigger additional verification or block access to prevent potential account takeover attempts.
Behavioral biometrics focuses on how users interact with digital systems, including typing speed, mouse movement, and navigation patterns. These behavioral patterns create a unique user profile over time, making it possible to distinguish between legitimate users and fraudsters attempting unauthorized access.
Link analysis maps relationships between users, devices, accounts, and transactions to identify hidden fraud networks. By analyzing these connections, businesses can detect coordinated attacks, suspicious clusters of activity, and abnormal relationships that may indicate account takeover attempts or organized fraud schemes.
Businesses can use transaction pattern analysis to monitor deviations from normal user behavior. When activity significantly differs from historical patterns, such as unusual transaction amounts or login locations, the system can flag or block the session to prevent account theft.
Modern fraud prevention platforms like Formica AI combine device intelligence, behavioral biometrics, and graph-based link analysis to provide real-time account protection and reduce account takeover risk.