Real-time Alerts
Monitor and respond to critical fraud events as they occur. Alerts are prioritized by severity and updated in real-time.
Real-time alert trend visualization would appear here
Connected to live data stream
Fraud Rules Engine
Configure, test, and deploy fraud detection rules. Monitor rule performance and impact on false positive rates.
Rule performance metrics and impact analysis
Hit rate, false positive rate, risk coverage
Rule Testing Sandbox
Test Results:
| Timestamp | Rule Name | Action | Deployed By | Status | Impact |
|---|---|---|---|---|---|
| 2026-02-16 14:22:18 | Nigeria High-Value Transaction | Activated | admin | Active | Blocked 3 fraudulent transactions |
| 2026-02-15 09:45:33 | Velocity Check Threshold | Modified | analyst_jane | Updated | Reduced false positives by 18% |
| 2026-02-14 16:30:05 | Suspicious Merchant Pattern | Deactivated | admin | Inactive | High false positive rate (42%) |
Audit Trail Logs
Immutable record of all system activities for compliance and forensic investigations. Meets FFIEC, PCI DSS, and GDPR requirements.
| Timestamp (UTC) | User | Action | Resource | IP Address | Details | Evidence Hash |
|---|
Regulatory Requirements Met:
- FFIEC Cybersecurity Assessment Tool (CAT) - Section III.D.3
- PCI DSS Requirement 10: Track and monitor all access to network resources and cardholder data
- GDPR Article 30: Records of processing activities
- SOX Section 404: Internal controls over financial reporting
- Local Central Bank Circular 1112 (Philippines)
Regulatory Compliance Reports
Pre-built templates and automated reporting for financial regulations. Generate evidence packages for auditors with one click.
PCI DSS Compliance Report
Requirement 11.5: Deploy a Change-Detection Mechanism
Requirement 8: Identify and Authenticate Access
Requirement 10: Track and Monitor Access
GDPR Article 32 Security Measures Report
Pseudonymization and Encryption
Confidentiality, Integrity, Availability
Data Subject Rights
Entity Network Analysis
Visualize relationships between users, devices, and transactions to uncover organized fraud rings and sophisticated attack patterns.
Detected Fraud Ring: "Operation Phoenix"
Entities Involved
- 6 User Accounts
- 4 IP Addresses
- 3 Device Fingerprints
- 2 Phone Numbers
Transaction Pattern
- Layering: Small transactions across multiple accounts
- Integration: Funds moved to "clean" accounts
- Geographic dispersion: Transactions across 5 countries
Risk Assessment
- Risk Score: 94/100 (Critical)
- Confidence: 92%
- Estimated Fraud Value: $187,500
- First Detected: 2026-02-10
Recent Entity Searches
- USER-78901 Critical
- 192.168.1.105 Warning
- DEVICE-ABC123 Info
- +639171234567 Low Risk
Fraud Ring Detection Alert
Our AI engine has detected a high-probability fraud ring involving 6 accounts with shared attributes. The network shows classic layering behavior with funds moving through multiple accounts before integration into seemingly legitimate transactions.
Key Indicators
- Shared Device Fingerprint: 4 accounts accessed from identical device configuration
- IP Rotation Pattern: Sequential transactions from different IPs in same geographic cluster
- Transaction Timing: Activity concentrated during non-business hours across timezones
- Merchant Diversity: Unusual variety of merchant categories for single user profile
Workflow Automation Studio
Design, test, and deploy automated investigation workflows. Reduce manual effort and ensure consistent handling of fraud cases.
High-Risk Transaction Workflow
Automatically routes high-risk transactions (>85 score) for senior analyst review
After-Hours Alert Workflow
Routes critical alerts during non-business hours to on-call analyst with SMS escalation
False Positive Learning Workflow
Automatically adjusts risk scores for merchants with high false positive rates
Workflow Configuration
Workflow efficiency metrics and SLA compliance
Cases processed, avg. handling time, escalation rate
| Timestamp | Workflow | Case ID | Status | Duration | Outcome |
|---|---|---|---|---|---|
| 2026-02-16 14:22:18 | High-Risk Transaction | CASE-9876 | Completed | 1h 24m | Blocked |
| 2026-02-16 13:45:09 | After-Hours Alert | CASE-9875 | Completed | 42m | Approved |
| 2026-02-16 12:30:55 | High-Risk Transaction | CASE-9874 | Escalated | 3h 15m | Pending Review |
| 2026-02-16 11:17:33 | False Positive Learning | CASE-9873 | Completed | 8m | Auto-Adjusted |
System Health Monitor
Real-time monitoring of system performance, availability, and security posture. Proactive alerts for potential issues.
Real-time system performance visualization
CPU, memory, database connections, API throughput
| Timestamp | Service | Severity | Description | Duration | Status |
|---|---|---|---|---|---|
| 2026-02-16 13:42:18 | API Gateway | Warning | Elevated response times (P95: 850ms) | 18 minutes | Resolved |
| 2026-02-15 09:17:33 | Database Cluster | Critical | Connection pool exhaustion | 42 minutes | Resolved |
| 2026-02-14 16:05:22 | Fraud Detection Engine | Info | Scheduled rule update deployment | 8 minutes | Completed |
| 2026-02-13 22:30:15 | Alert Notification Service | Warning | Temporary SMS gateway outage | 27 minutes | Resolved |
Active Cases
Manage ongoing fraud investigations. Assign cases, track progress, and collaborate with team members.
| Case ID | Priority | Transaction | Risk Score | Assigned To | Status | Created | Actions |
|---|---|---|---|---|---|---|---|
| CASE-9876 | Critical | TXN-A7B9C2 ($24,500) | 92 | Unassigned | New | 14:28:15 | |
| CASE-9875 | High | TXN-D4E6F8 ($4,850) | 68 | analyst_jane | In Progress | 14:15:33 | |
| CASE-9874 | Medium | TXN-G1H3J5 ($127.85) | 42 | analyst_john | Pending Review | 13:52:07 | |
| CASE-9873 | Medium | TXN-K7L9M2 ($349.99) | 38 | senior_analyst | Escalated | 13:41:22 | |
| CASE-9872 | Low | TXN-N4P6Q8 ($42.50) | 18 | analyst_jane | In Progress | 13:27:45 |
Analyst workload distribution and capacity
Cases assigned, avg. handling time, backlog
Case distribution by priority, status, and type
Visual breakdown of active caseload
Case History
Comprehensive archive of resolved fraud cases. Search, filter, and analyze historical investigations for pattern recognition and training.
| Case ID | Transaction | Risk Score | Analyst | Outcome | Resolution Time | Resolved Date | Actions |
|---|---|---|---|---|---|---|---|
| CASE-9800 | TXN-Z9Y8X7 ($18,750) | 89 | senior_analyst | Fraud Confirmed | 2h 17m | 2026-02-15 16:42:18 | |
| CASE-9799 | TXN-W6V5U4 ($320.50) | 62 | analyst_jane | False Positive | 48m | 2026-02-15 14:22:05 | |
| CASE-9798 | TXN-T3S2R1 ($1,250.00) | 71 | analyst_john | Legitimate | 1h 35m | 2026-02-15 11:17:33 | |
| CASE-9797 | TXN-Q0P9O8 ($4,200.00) | 94 | senior_analyst | Fraud Confirmed | 3h 42m | 2026-02-14 18:05:22 | |
| CASE-9796 | TXN-N7M6L5 ($87.25) | 38 | analyst_jane | Customer Dispute | 2h 08m | 2026-02-14 15:30:15 |
Historical case resolution metrics and trends
Resolution time, outcome distribution, analyst performance
Top Fraud Patterns Identified
- Nigeria High-Value Transactions: 27 confirmed fraud cases in last 30 days
- Card Testing from Bangkok: 18 confirmed fraud cases with velocity patterns
- Behavioral Shifts in Philippines: Jewelry purchases after 24 months of grocery transactions
- Merchant Category Mismatches: High-risk transactions at low-risk merchant types