Quantexa

Retail AML

Empowering retail banks to fight financial crime with clarity and confidence.

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CHALLENGE

When AML Decisions Lack Context

As retail banking becomes more inter-connected, financial crime is increasingly dispersed across payments, cash activity, cross-border flows, and third-party facilitators. Legacy, rules-based AML systems lack the context advanced analytics and AI capabilities need to distinguish real risk from noise, allowing criminal networks to evade detection. Without a unified view of customers, counterparties, and networks, banks struggle to surface true risk with confidence.

6 trillion

Illicit financial flows are projected to hit $4.5 trillion to $6 trillion by 2030.

Source: Secretariat

75%

Generative AI is now the #1 external risk to financial crime functions. 

Source: ACAMS

HOW WE SOLVE IT

Decision Intelligence for Retail AML 

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Build a connected, context-rich data foundation

Unify fragmented internal and external data into enriched, trusted views of personal and SME customers, counterparties, and activity.

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See the full picture beyond a single transaction

A connected data foundation provides a holistic view that powers investigations beyond isolated alerts, bringing full behavioral and network context to retail AML risk detection.

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Expose hidden criminal networks across retail channels

Graph Generation uncovers suspicious activities, hidden facilitators, and coordinated behavior spanning across the broader retail banking ecosystem.

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Power trusted, explainable AI for better decisions

Connected, contextual data powers explainable AI and typologydriven scoring across Contextual Monitoring, detection, and investigations, accelerating action and strengthening Retail AML programs.

THE IMPACT

What we have achieved

80% reduction

in investigation time (at scale)

75% reduction

in false positives

73% of alerts

sent for further investigation

See it in action

Explore how connected data, typologydriven scoring, and network analytics surface true risk across retail customers and activity, cutting through alert noise to fight AML in retail banks.

Why Quantexa

We help you bring context to Retail AML compliance


Typology-based scorecards aggregate multiple indicators into meaningful risk events, reducing false positives and shifting teams from technical compliance to risk-led decision-making.

SOLUTION OVERVIEW

Get an overview of our Contextual Monitoring solution

category-leading technology

Our Decision Intelligence Platform

Build a single view of data and create a culture of confidence around critical decision-making that protects, optimizes, and grows your organization.

outcome-driven solutions

Decision Intelligence solutions built on our platform

FAQs

What is the difference between traditional Transaction Monitoring and Contextual Monitoring?

Rules-based transaction monitoring systems have several limitations and challenges, which have historically hindered their effectiveness in detecting and preventing financial crimes.  

For example, the rules and thresholds need to be manually created and updated, making the system less adaptable to evolving and emerging threats.  Similarly, rules-based systems also typically analyze individual transactions in isolation and may not provide a comprehensive view of customer and counterparty behavior or relationships. They may miss the connections between seemingly unrelated transactions or accounts, which can be crucial in identifying more complex fraud networks or money laundering schemes. 

In contrast, by combining multiple internal and external datasets all at once, Contextual Monitoring transforms the view of risk to a gain clearer understanding of customers, counterparties, their relationships, and behaviors in real time. Using advanced Entity Resolution and network generation techniques, Contextual Monitoring focuses on holistic relationships rather than transaction risk in isolation. 

This added context helps to identify hidden risk and generates fewer, more accurate alerts. Institutions can reduce rising compliance and operational costs and conduct more effective and efficient intelligence-driven risk processes without replacing existing systems. 

How can we accelerate the investigations process?

Turning data into intelligence is imperative for reducing manual processes, identifying critical connections and breaking down silos between teams. For AML investigations, shifting to an intelligence-led approach goes beyond a single event, relationship or activity enabling a more holistic understanding of customers, employees, counterparties and their related risk. With the broad capabilities of Quantexa’s platform, intelligence officers have a powerful tool that can run different analytical tasks, covering a risk-based approach and integrating third-party data and external sources for deeper investigation. Unlike traditional systems, Quantexa's AML software visualizes hidden connections through additional context.

How can banks navigate AML complexities?

Evolving AML intricacies and typologies driven by multiple channels, lines of business and products​ have driven major challenges in financial services. With Quantexa's Decision Intelligence platform, Quantexa's AML software can transform a banks approach to financial crime compliance. Improving risk coverage, identifying complex typologies, pinpointing real risk, reducing false positive and uplifting efficiencies.

DRIVE INDUSTRY TRANSFORMATION

Speak to an expert

Protect, optimize, and grow your organization with Decision Intelligence. More is possible with the right data in the right context.