Integrating CDD controls into transaction monitoring with Quantexa

Enhancing correspondent banking compliance with Quantexa

Introduction

Correspondent banking compliance is facing unprecedented pressure. Rising transaction volumes, increasingly complex financial crime typologies, and heightened regulatory scrutiny are exposing the limitations of traditional compliance operating models. While banks have invested heavily in transaction monitoring (TM), customer due diligence (CDD) frequently remains manual, periodic, and operationally siloed.

Recent experience with a Tier 1 UK bank highlights a critical inflection point. Rather than treating CDD and transaction monitoring as separate control frameworks, banks now have an opportunity to integrate them into a unified, intelligence-driven compliance model. This shift enables more consistent risk assessment, broader coverage, and a more scalable approach to managing correspondent banking risk.

Why change is now a strategic imperative

Despite significant investment in transaction monitoring, many correspondent banking frameworks continue to face structural limitations that constrain effectiveness and scalability:

• Manual, sample-based reviews: Investigators often rely on Excel-based sampling to review payments, creating coverage gaps and delaying the detection of suspicious activity in high-volume environments.
• Operational silos: Limited alignment between TM and CDD functions leads to duplicated assessments and fragmented views of the same financial institutions, highlighting the need for a more integrated operating model.
• Rising regulatory expectations: Regulators increasingly expect event-driven, risk-based monitoring that enables continuous assessment and timely escalation. Traditional CDD review cycles struggle to meet these expectations, particularly for higher-risk correspondent relationships.
• Reactive risk management: Exposure to virtual asset service providers, offshore structures, trade sanctions, and embargoed jurisdictions is often managed manually, limiting consistency and scalability across rapidly evolving risk areas.

Taken together, these challenges highlight a clear opportunity. Modern transaction monitoring platforms already contain the intelligence needed to support continuous CDD. By repurposing these capabilities, banks can move from fragmented controls to a unified, near-real-time view of correspondent banking risk.

Quantexa solution for integrated CDD and TM

To address these challenges, our team designed a risk-scoring and monitoring framework that embeds a dedicated CDD control layer within the Quantexa transaction monitoring platform. The framework is built around four core principles:

Alignment with regulatory expectations
The framework aligns with current regulatory standards and Wolfsberg requirements for ongoing, risk-based CDD in correspondent banking. It enables a clear and consistent understanding of correspondent relationships and the effectiveness of counterparties’ AML controls. By consolidating these requirements into a single, integrated approach, the framework reduces manual evidence collection, improves regulatory defensibility, and supports continuous monitoring beyond traditional periodic reviews.

Reuse of existing infrastructure
The existing Quantexa transaction monitoring architecture was assessed to identify components that could be reused or enhanced as part of the design. Monitoring models, network graphs, and data pipelines were identified as candidates for repurposing to support both periodic and event-driven risk assessments. The design proposed a dedicated CDD layer within the platform, reusing the existing user interface for efficiency while maintaining clear functional separation through distinct Explorers. Potential overlaps between scores were identified to reduce duplication and improve long-term operational efficiency.

A dedicated CDD control layer
Automated risk scoring and intelligent alerts are tailored specifically to correspondent and respondent banking relationships, enabling more accurate and contextual monitoring. By shifting from manual oversight to automated detection, the framework provides continuous coverage of emerging high-risk areas, including:

• Jurisdictional risk: Identifying changes in regulatory strength and financial crime exposure across counterparties’ key regions.
• High-risk sectors: Using automated code mapping to highlight industry concentrations vulnerable to financial crime.
• Trade sanctions and embargoes: Detecting direct and indirect exposure to sanctioned entities and restricted jurisdictions within payment flows.
• Emerging entity risks: Flagging exposure to higher-risk structures such as virtual asset service providers (VASPs), offshore entities, and shell companies.

Support for risk-based reviews
The framework enables perpetual KYC (pKYC) and enhanced due diligence teams to focus on higher-risk relationships using data-driven insights. Automated monitoring tracks changes in customer risk profiles, reducing reliance on manual sampling and improving consistency. This targeted approach supports regulatory expectations, avoids blanket de-risking, and ensures attention is focused where risk is highest.

Conclusion

Integrating CDD controls into transaction monitoring marks a critical shift in correspondent banking compliance, moving banks from fragmented, manual processes to unified, intelligence-driven risk management. By combining TM and CDD, institutions can assess risk at both the transaction and customer levels while eliminating duplicate reviews and improving operational efficiency. This approach delivers stronger risk coverage, more consistent investigations, and supports true risk-based decision-making without unnecessary de-risking. With automated CDD controls embedded directly into TM platforms, manual oversight becomes the exception rather than the norm, enabling proactive, near-real-time management of high-risk correspondent relationships.