ComplyRadar is an end-to-end AML and financial crime compliance solution designed to help regulated entities detect, investigate, manage, and report suspicious financial activity.

It combines transaction monitoring, anomaly detection, automation, case management, goAML integration, and AI-powered virtual assistance into a unified compliance ecosystem.

The platform is designed for organisations operating in highly regulated or high-risk sectors, including:

• Banks
• Fintechs
• Payment service providers
• Electronic money institutions
• Crypto exchanges
• Insurance companies
• Gaming operators
• Corporate service providers
• Investment firms
• Wealth management companies
• Lending institutions
• Money remittance businesses

The platform helps organisations:

• Detect suspicious transactions
• Reduce false positives
• Automate repetitive compliance workflows
• Improve operational efficiency
• Meet AML/CFT regulatory obligations
• Streamline investigations
• Improve audit readiness
• Generate regulatory reports
• Strengthen risk management
• Enhance transaction visibility

Yes. The platform is highly configurable and supports:

• Custom risk rules
• Institution-specific thresholds
• Jurisdiction-specific requirements
• Dynamic risk scoring
• Multi-entity structures
• Workflow customisation
• Approval hierarchies
• Escalation paths
• Reporting templates
• User permissions

Yes. The platform is designed to support organisations operating across multiple jurisdictions and regulatory frameworks.

Configurations can be adapted to:

• FATF guidance
• EU AML directives
• FCA expectations
• MFSA requirements
• FinCEN requirements
• Local FIU obligations
• Internal compliance frameworks

ComplyRadar supports:

• Cloud deployment
• Private cloud
• Hybrid deployment
• On-premise infrastructure

Deployment options depend on operational, security, and regulatory requirements.

Implementation timelines depend on:

• Data complexity
• Integration scope
• Number of monitored systems
• Regulatory requirements
• Custom workflow requirements

Typical implementations range from several weeks to a few months.

Yes. The platform supports integration with:

• Core banking systems
• Payment processors
• CRM systems
• KYC providers
• Sanctions screening tools
• Fraud systems
• Data warehouses
• ERP platforms
• APIs
• Third-party compliance tools

The platform is designed for scalability and can support:

• High transaction volumes
• Multi-entity organisations
• Cross-border operations
• Real-time monitoring
• Large investigation teams

Yes. Industry-standard encryption and security controls are applied to data in transit and at rest.

Yes. Comprehensive audit logging tracks:

• User activity
• Alert handling
• Investigation decisions
• Rule changes
• Escalations
• Regulatory reporting actions

Yes. The platform is designed around risk-based compliance methodologies and supports:

• Customer risk segmentation
• Transaction risk scoring
• Geographic risk assessment
• Behavioural monitoring
• Dynamic thresholding

Language support depends on deployment requirements and may include multilingual user interfaces and reporting capabilities.

Transaction monitoring is the continuous analysis of financial activity to identify potentially suspicious behaviour, unusual transaction patterns, or AML/CFT risks.

The engine analyses transactional behaviour against predefined rules, thresholds, behavioural patterns, and risk indicators to identify potentially suspicious activity.

Yes. ComplyRadar can support real-time, near-real-time, and batch transaction monitoring depending on operational requirements.

The platform can monitor:

• Bank transfers
• Card transactions
• Crypto transactions
• Wallet activity
• Gaming transactions
• Remittances
• ACH payments
• SWIFT transfers
• Internal transfers
• Merchant payments
• Cross-border payments

Yes. Compliance teams can create and modify rules based on:

• Customer behaviour
• Transaction values
• Velocity thresholds
• Geographic risk
• Product usage
• Industry-specific risks

Yes. Scenario-based monitoring enables institutions to detect typologies such as:

• Structuring
• Smurfing
• Rapid movement of funds
• Layering
• Dormant account activity
• High-risk jurisdiction exposure

Yes. Alerts can be prioritised based on:

• Risk score
• Customer profile
• Jurisdiction
• Transaction value
• Historical activity
• Behavioural anomalies

Yes. Compliance teams can continuously refine monitoring scenarios and thresholds to improve effectiveness and operational efficiency.

Yes. Alerts can be reviewed, escalated, assigned, investigated, documented, and closed directly within the platform.

Yes. Integrated case management enables teams to manage investigations, evidence, escalations, and reporting workflows centrally.

Yes. The platform can support crypto-related monitoring requirements including wallet activity analysis, transaction tracing integrations, and behavioural monitoring.

Yes. Risk scoring can incorporate:

• Customer risk
• Geographic exposure
• Transaction behaviour
• Product usage
• Adverse media indicators
• Historical investigations

Yes. Investigators can review the logic, triggers, and risk indicators behind generated alerts.

Anomaly detection identifies unusual or abnormal transaction behaviour that deviates from expected patterns.

Rule-based monitoring relies on predefined thresholds and scenarios, while anomaly detection identifies unexpected behaviours that may not fit existing rules.

Yes. Advanced anomaly detection capabilities may use machine learning and behavioural analytics to identify hidden or evolving financial crime risks.

Examples include:

• Sudden transaction spikes
• Behavioural deviations
• Unusual account activity
• Geographic inconsistencies
• Rapid movement of funds
• New payment corridors
• Dormant account activation
• Abnormal transaction timing

Yes. Behavioural models can evolve as transaction patterns change.

No. Anomaly detection complements traditional rules-based monitoring to provide broader coverage and improved detection capabilities.

Alerts are routed into investigation workflows where compliance teams can assess context, supporting evidence, and customer risk.

Yes. Behavioural analytics can help identify suspicious patterns that may not yet be covered by static monitoring rules.

Yes. It helps focus investigator attention on genuinely unusual activity rather than relying solely on broad thresholds.

Yes. The platform can support crypto-related monitoring requirements including wallet activity analysis, transaction tracing integrations, and behavioural monitoring.

Yes. Risk scoring can incorporate:

• Customer risk
• Geographic exposure
• Transaction behaviour
• Product usage
• Adverse media indicators
• Historical investigations

Yes. Investigators can review the logic, triggers, and risk indicators behind generated alerts.