Unified real-time fraud, risk & AML compliance

FRAML (Fraud Risk and Anti-Money Laundering) connects fraud detection, AML monitoring and investigation through shared intelligence. Instead of treating suspicious activity as separate fraud and AML alerts, Clari5 FRAML helps banks correlate signals across channels, customers, transactions and connected accounts in real time. This gives teams broader context to investigate potential financial crime and act on related risks.

Fraud proceeds can move through mule accounts and connected networks before being layered or transferred elsewhere. Clari5 FRAML combines cross-channel monitoring, customer risk profiles and graph-based link analysis to help identify relationships that individual fraud or AML systems may miss. Connecting these signals gives investigators a more complete view of suspicious activity across accounts and products.

Integration feasibility depends on your existing architecture, data availability, interfaces and processing requirements. Clari5 FRAML is designed to bring fraud and AML intelligence together on a shared platform, with SaaS and on-premise deployment options. A technical assessment should establish how existing systems will connect, which capabilities can be retained, and what changes may be required.

The objective is not simply to generate fewer alerts. It is to help investigators distinguish meaningful risk from activity that requires no further action. Clari5 FRAML combines transaction monitoring, behavioural analysis, machine learning and connected customer intelligence to support risk-based detection and investigation. Actual improvements in false positives, alert quality and investigation time should be validated against your bank's existing performance and control requirements.

No. Technology convergence does not automatically require organisational restructuring. Clari5 FRAML supports shared intelligence and investigation context while banks retain their chosen governance, reporting lines and approval responsibilities. The operating model should define how teams share relevant information, escalate cases, manage sensitive disclosures and maintain clear accountability for fraud decisions and AML obligations.

Clari5 FRAML supports consolidated STR, CTR and SAR reporting, goAML capabilities, unified case management and audit trails. The relevant reporting formats, workflows and controls must be assessed against the requirements of each jurisdiction and financial institution. During evaluation, banks should verify applicable regulatory coverage, evidence retention, access controls, reporting accuracy and the ability to reconstruct investigation decisions.

An in-house build offers control and customisation but requires sustained engineering and maintenance resources. Point solutions may provide specialist capabilities, although integration can leave gaps in shared intelligence and create additional operational overhead. A unified FRAML platform offers a common intelligence layer across fraud and AML. The right choice depends on your existing investments, integration complexity, control requirements, internal expertise and total cost of ownership.

Clari5 FRAML supports SaaS and on-premise deployment. The appropriate approach depends on your infrastructure, data residency obligations, security policies, transaction volumes and integration requirements. Discovery should establish the target architecture, migration approach, dependencies, testing requirements and implementation responsibilities before a delivery timeline is committed.

Implementation time depends on the bank's architecture, data readiness, integration scope, regulatory requirements and testing needs. Clari5's FRAML page describes a structured engagement covering discovery and assessment, a tailored demonstration, and business case development and scoping. Its stated typical deployment timeline is 16–20 weeks, but this should be validated for your institution. A detailed plan should cover parallel testing, performance validation, user acceptance, fallback arrangements and controlled transition to production.

Start by establishing a baseline for fraud losses, alert volumes, false-positive rates, investigation time, reporting effort, technology costs and operational duplication. Then assess the potential value of connected detection, shared investigations and platform consolidation against implementation, integration, licensing and ongoing operating costs. A structured evaluation with Clari5 should agree measurable success criteria, validate capabilities against representative scenarios, and produce a bank-specific roadmap and investment estimate before a purchasing decision.