Transaction monitoring with end-to-end traceable evidence

Every alert is linked to the customer’s already verified identity record, rather than being treated as an isolated data point. Investigations start from a profile backed by a validated document, verified biometrics, and an established history.

As a Facephi-managed SaaS solution, in a private cloud on dedicated infrastructure, or on-premises within your own perimeter. The choice depends on the data residency requirements established by your regulator.

Each alert records the timestamp, triggered rules, correlated signals, identity context, analyst decision, and analyst sign-off. Information can be exported for internal audits, external audits, and regulatory reporting in each market, aligned with SARLAFT compliance in Colombia and CNBV compliance in Mexico.

Transaction monitoring is the continuous analysis of a customer’s transactions to detect patterns that may indicate money laundering or fraud, such as unusual activity, transaction structuring, or signals that do not match the customer’s typical profile. It is an AML regulatory requirement in most countries, not just a best practice. You can read an in-depth analysis of how transaction monitoring works in our Observatory.

El monitoreo AML busca patrones de blanqueo o financiación del terrorismo a lo largo de toda la relación con el cliente, con obligación de reportar al regulador. El monitoreo antifraude busca operaciones fraudulentas, autorizadas o no por el titular, y actúa para bloquearlas antes de que se completen. Una misma transacción puede pasar por ambos controles, con lógicas y equipos distintos. Facephi los conecta bajo una misma capa de identidad, apoyándose en el screening de PEP y sanciones, la detección de cuentas mula y las soluciones antifraude.

AML monitoring focuses on identifying money laundering or terrorist financing patterns throughout the customer relationship and includes regulatory reporting obligations. Fraud monitoring focuses on detecting fraudulent transactions, whether authorized or unauthorized, and acts to stop them before completion. The same transaction may pass through both controls, each with different logic and teams. Facephi connects them through a single identity layer, supported by PEP and sanctions screening, mule account detection, and fraud prevention solutions.

We evaluate transactions as they occur, with latency appropriate to the transaction type and the payment engine being used. Specific latency metrics and immediate payment performance are shared during the demo based on your use case.

By combining configurable rules with the context provided by the customer’s already verified identity. Every alert includes the customer’s profile rather than being treated as an isolated transaction.

Through REST APIs and direct connectors to transaction systems and common payment engines. The exact data model and integration level are defined during the technical discovery session and adapted to each institution’s technology stack.

The platform is deployed in financial institutions of all sizes, including banks processing high daily transaction volumes and fintechs expanding across multiple markets. The exact capacity for your environment is defined after the technical discovery session based on the selected deployment model.

Yes. You can choose between Facephi-managed SaaS, a private cloud instance on dedicated infrastructure, or an on-premises deployment within your own data center to meet data sovereignty and regulated infrastructure requirements.

The timeline depends on the deployment model and the level of integration with the core banking system. SaaS and PaaS deployments are the fastest to bring into production, while on-premises projects require coordination with your infrastructure team. A definitive implementation plan is provided after the technical discovery session.

Pricing depends on transaction volume, the number of environments, and the selected deployment model. We provide a tailored commercial proposal after the demo, based on your specific requirements.