Digital Banking & Cybersecurity Event Data

• Tracks failed login attempts, device fingerprints, and suspicious cybersecurity events (e.g., flagged IPs, unauthorized login alerts).

• Supports the detection of compromised accounts by revealing repeated access attempts, new device usage, or known malicious IP indicators.

• Provides IP logs, device usage patterns, and connection details for each online banking session or transaction.
• Enables monitoring and flagging of repeated access attempts from known anonymizing networks (e.g., Tor exit nodes, VPN endpoints).
• Assists investigators in correlating suspicious IP usage or rapid geolocation changes to detect potential misuse of anonymity tools and mitigate laundering risks.

• Correlates high-frequency payments with session telemetry (IP switches, headless-browser flags, API keys) to prove that transfers originated from bots or scripted sessions rather than human UI use.

• Captures patch deployment history, vulnerability scans, and intrusion attempts, revealing gaps where core systems may be exploited.
• Logs cybersecurity events, such as suspicious network traffic or repeated failed authentication attempts, indicating potential compromise of bank infrastructure.
• Helps link unpatched software vulnerabilities to observed manipulations of AML or transaction monitoring systems.

• Monitors account creation and closure patterns, revealing rapid account turnover potentially linked to transient mining operations.
• Tracks anomalous login attempts or suspicious device usage associated with mining payment flows.
• Flags repeated or coordinated account activities that may facilitate the layering of illicit proceeds through multiple digital channels.

• Records anomalous device behavior, login patterns, malware infections, and endpoint security alerts.
• Correlates internal IT security events (malware detected, EDR logs, unauthorized cloud resource spikes) with downstream financial activity, supporting full-lifecycle tracing of cryptojacking—from compromise to laundering.

Collects device fingerprints, IP addresses, login timestamps, and other cybersecurity signals within digital banking channels. Correlating these with suspicious voice-based transactions helps uncover deepfake impersonation by spotting anomalous device or network usage.

Includes records of software usage, transaction anomalies, and unauthorized access attempts. Investigators identify unapproved plugins or scripts used to manipulate transaction data in real-time, bypassing standard logs.

• Includes IP logs, device usage patterns, and alerts on unauthorized access attempts within online banking portals.
• Assists in detecting compromised accounts, unusual login activity, or cybersecurity incidents correlating with the fraudulent redirection of educational institution payments.

• Monitors IP addresses, device fingerprints, and network activity for digital banking sessions.
• Identifies inconsistencies between a customer’s claimed location and the actual device or network attributes, revealing possible fake identities or impersonation.

• Track device fingerprints, IP addresses, and session metadata to identify repeated usage patterns across supposedly distinct accounts.
• Detect anomalies in remote onboarding or login behavior to indicate potential impersonation or account takeover.

Logs and analyzes account access patterns, device fingerprints, and profile modification events. Excessive or repeated alterations to personal details after account opening can indicate identity manipulation efforts or account takeovers.

Encompasses IP logs, device usage patterns, and login activity for online and mobile platforms. In lottery schemes, this data:

• Detects geographically dispersed IP addresses or multiple devices used for lottery ticket purchases.
• Flags unusual account access patterns linked to suspicious ticket-buying or prize-redemption activity.
• Supports investigation of compromised or third-party account usage.

Includes IP addresses, device identifiers, and geolocation data for mobile payment platforms. This data allows for the detection of device or geographic anomalies, such as multiple wallet registrations from the same device or IP address mismatches. It supports the investigation of layered account usage, cross-border activities, and rapid fund transfers.

Logs authentication events, device fingerprints, and IP addresses. This data helps detect multiple or unexpected devices accessing newly opened accounts, indicating possible external control or 'mule herding,' which is commonly seen in money mule recruitment.

The same device fingerprint or IP block repeatedly onboarding “distinct” spellings indicates systematic alias cycling—an artefact captured only in device-telemetry logs.

• Tracks IP addresses, device fingerprints, and account creation patterns to identify coordinated or high-risk activities in offshore gambling.
• Detects large volumes of new high-value accounts or potential fraudulent access attempts, indicating layering schemes.

These data points assist compliance teams in investigating suspicious digital behavior linked to under-monitored offshore gambling sites.

• Records login attempts, authentication failures, and suspicious device/browser fingerprints.
• Highlights anomalies in user session patterns (e.g., sudden IP address changes, usage of known anonymizing IPs).
• Assists in correlating frequent or failed logins through Tor/VPN networks with potential illicit activity masked by multi-layered encryption.

Captures IP addresses, device identifiers, and other technical details, enabling the detection of overlapping user fingerprints across supposedly unrelated P2P accounts.

• Tracks device attributes such as operating system, time zone, language settings, and user-agent details.
• Helps identify suspicious session anomalies or rapid changes in device fingerprints consistent with rotating proxy usage.
• Strengthens AML investigations by flagging inconsistent device characteristics originating from potentially anonymized connections.

• Provides IP logs, device usage patterns, and session metadata from online and mobile banking channels, revealing whether connections originate from public, potentially unsecured hotspots.
• Identifies VPN or proxy usage layered on public WiFi, helping detect deliberate obfuscation of user location and identity.
• Correlates multiple session logs to expose suspicious simultaneous or rapid-sequence logins from disparate public IP addresses, indicating potential coordinated misuse.

Captures IP addresses, device fingerprints, and session details for online banking, helping identify the repeated use of the same device or IP to deposit checks into multiple accounts under different names. This supports AML investigations of remote deposit capture abuse and potential collusive activity.

Captures IP addresses, device fingerprints, and usage patterns in online banking environments. It reveals multiple account creations from the same device or IP address and detects anonymizing tools such as VPNs and proxies. This data helps identify unusual remote onboarding behaviors consistent with online identity deception.

• Captures IP addresses, device usage patterns, and authentication attempts, enabling the detection of multiple remote account creations from the same device or IP range.
• Identifies the use of proxies, VPNs, or other anonymizing services during account registration or verification.
• Monitors aborted verification procedures followed by immediate re-attempts under new credentials or data, helping to reveal suspicious patterns indicative of remote verification bypass.

• Provides IP logs, device usage patterns, login timestamps, and alerts on suspicious behavior.
• Helps detect unusual login patterns, rapid address changes, or dispersed wallet usage indicative of potential money laundering through self-hosted wallets.

• Captures IP addresses, device identifiers, and login timestamps across online and mobile trading platforms.
• Enables detection of multiple trading accounts accessed from the same device or location, helping to uncover coordinated or collusive trading patterns.
• Highlights suspicious or unauthorized login attempts, supporting the identification of orchestrated manipulation using advanced electronic trading channels.

• Encompasses cybersecurity alerts, malware detections, unauthorized access attempts, and suspicious system events.
• Uncovers malicious code or anomalies specifically designed to alter or erase transaction records.

• Tracks user session information, IP logs, and transaction status changes, highlighting repeated initiation and quick cancellation of small transactions used to gauge thresholds.
• Supports investigation of abnormal login patterns and rapid reversals, suggesting deliberate testing of AML controls.

• Captures online banking events, including IP usage, device fingerprints, and account access details.
• Identifies consistent VPN usage in account opening or management activities.
• Supports AML investigations by correlating suspicious login methods with KYC records to detect potentially hidden user locations.