ThreatMetrix, a US provider of integrated cybercrime prevention solutions, has introduced a behavioral analysis in the ThreatMetrix Cybercrime Defender Platform via the ThreatMetrix Persona ID Rules, enabling linkage of a current transaction to related transactions through a matrix of attributes associated to the visitor, device and connection.

ThreatMetrix Persona ID Rules uncovers anomalous behavior through the association of related activity and connected entities such as email addresses, transactions, accounts, devices, IP addresses, geo-location, proxies and physical addresses. It also allows the use of custom fields such as credit cards for creating customer-specific user profile building. The Rules then score the divergence (anomalies) or convergence (similarities) between current and historical attributes.

Using the newly launched tool, customers will now be able to:
• Assess the risk associated with the person or device engaged in an online transaction;
• Examine related transactions and determine whether they have been flagged as high risk in the past;
• Identify a legitimate customer based on whether the device and identity associated has been flagged as low risk in previous transactions;
• Provide a view of a visitor’s identity based on historically related transactions linked to the same identity or device;
• Detect unusual velocities in identities. For example, if transactions coming from an identity are flagged low risk or without any associated historical incidence of fraud, a business can safely screen the transactions in real-time for a frictionless, positive customer experience;
• Determine if a device seen across multiple identities, time zones and geographies is flagged as suspicious, relative to the norm.

ThreatMetrix serves a global customer base across a variety of industries, including financial services, e-commerce, payments, social networks, government and healthcare.