Today, many financial institutions find that their traditional anti-money laundering (AML) transaction monitoring systems are insufficient when relied on to detect risk in financial markets. In short, they fail to enrich, connect, or operationalize the various forms of data associated with such markets, often causing investigators to miss suspicious patterns of behavior that may exist within this data. Similarly, these legacy approaches overburden investigators with exceptionally high volumes of false positive alerts, making the process of detecting risks related to financial crime to be both inefficient and ineffective.
Now, industry expert Scott Nathan, Head of Innovation for AML and Risk at State Street, has been working with Quantexa on a new approach to AML in markets, one that harnesses contextual decision intelligence for more efficient and effective risk detection in financial markets.
Something Had to Be Done
Recent money laundering cases have resulted in fines approaching a billion dollars for numerous tier one banks. In these cases, the critical factor was the relationships between both sides of the trades. Using a rule-based approach, financial institutions may capture one or more of the trades associated with a scheme yet fail to act on them because the institution lacks context around those trades.
Conversely, using contextual monitoring that leverages entity resolution, network analytics, and advanced analytics offers a new approach to generating insights that empower decision making. Using this approach, financial institutions can resolve related entities into one and make connections between distinct entities through interactions and relationships to derive context, and this context gives investigators a far more unified and accurate picture of where true risk lies. Furthermore, advanced analytics at the transaction, entity, and network-level can support the generation of risk-scored alerts, allowing analysts to prioritize and focus their efforts.
Unlocking New Opportunities and Insights
When Scott Nathan joined State Street, he was excited to learn that the company was interested in trying something new, as the legacy approach to AML was falling short. “We process and persist data in ways that are unlike any traditional commercial bank, and that presents unique challenges but also really interesting opportunities to use new technology,” said Scott.
Scott acknowledges that up until recently, many financial institutions relied on linear models, which targeted many scenarios and specific behaviors, yet lacked the context to identify risk that may look different from that pre-defined set of typical typologies. This resulted in a lack of visibility into activity happening throughout the markets and across the financial services ecosystem.
Today, Scott reports that State Street uses AI and machine learning technology to detect, analyze, and visualize markets-related risk. The technology enables the bank to enrich data to create a single entity view and then build networks to understand customer activity, inherent risk, and how its products are potentially being abused. This approach leads to a more streamlined and optimized detection process.
A context-led approach empowers State Street to identify risk with fewer false positives, enabling investigators to focus on genuine risk and make more accurate decisions in their investigations. Most importantly, it helps Scott and his colleagues protect both the company and the financial system as a whole from the dynamic threats associated with financial crime.
To learn more about contextual monitoring and how State Street has implemented this approach to improve its markets AML processes, watch the full webinar here.
You may be interested in…

Solving the Shell Company Conundrum
New Decision Intelligence technology is allowing banks to identify illicit shell company networks at scale to crack down on money laundering and fraud.

3 Talented Quantexans Recognized in the 2023 Women of the Channel List
CRN’s 2023 Women of the Channel honors Tina Gravel, Donna Goodwin and Sheryl Wharff of Quantexa.

This Powerful New Solution Provides a Single View of Customers in Minutes
Quantexa is innovating quickly to test a faster, more streamlined way to deliver Entity Resolution at scale by bundling key capabilities of their Decision Intelligence Platform (DI) in a new product called ER Accelerate.

Quantexa Positioned as a Technology Leader in Quadrant’s 2023 AML SPARK Matrix
Quantexa has been named a 2023 Technology Leader in Quadrant Knowledge Solutions’ Anti-Money Laundering (AML) SPARK Matrix.

In Context: Enhancing KYC and AML Efforts With Innovative Technology
Today’s banking environment is rapidly evolving thanks to new technologies that are allowing organizations to get a full, 360-degree view of their customers. We caught up with Scott Nathan from Citi on the challenges the banking industry faces today and how savvy financial institutions are using technology to meet those challenges.

4 Areas of Focus for Financial Services Firms Following the FCA Review
The FCA’s review of firms’ Consumer Duty implementation plans highlights the positive progress made by some, but also the deficiencies in the approaches of others.
Related Solutions

Tax Authorities
Reduce the tax gap, identify fraud and non-compliance, and operate as efficiently as possible with limited resources.

Anti-money laundering
Reveal hidden risks and detect criminal activity faster. Reduce false positives to manage the cost of compliance. And improve investigations to make faster and more consistent decisions at scale.

Customs Agencies & Border Control
Contextual Decision Intelligence enables faster decisions, increased revenue collection and enhanced compliance. The Quantexa platform enables Customs and Border agency teams to analyze data successfully, automate and accelerate decision-making, and achieve improved results.

Fraud
Identify potentially fraudulent activity by looking at people or transactions in isolation. Understand the context surrounding the organizations you do business with to make fast, accurate decisions.

Fraud, Waste & Abuse
Empower your team with the best tools available for today’s challenges to identify and prevent fraud, waste and abuse with contextual decision intelligence software.

Credit Risk
Understand your customers, their business structures and supply chains. Make better lending decisions, faster. And support digital risk transformation.

Customer Intelligence
Generate a complete view of the context around your customers and prospects to build better relationships, reduce attrition and find hidden opportunities.

Revolutionize Your Financial Crime and Fraud Detection

Investigations
Enhance the efficiency, effectiveness and consistency of your operational and complex investigations to empower your teams to expose and understand risk faster.

Master Data Management
Connect all data—internal and third party—to create a joined-up, contextual view of all the relationships between your customers and every other domain.

Compliance
See how we help to reduce costs and improve coverage for financial crime compliance.

CDO
See how our platform uses contextual analysis to turn data into a high value asset.

CIO
See how our platform uses financial crime technology to enhance your existing IT ecosystem.

Healthcare
Reduce the tax gap, identify fraud and non-compliance, and operate as efficiently as possible with limited resources.

Contextual Monitoring
Reveal hidden risks and detect criminal activity faster. Reduce false positives to manage the cost of compliance. And improve investigations to make faster and more consistent decisions at scale.

Unified CRM Solution

Know Your Customer
Reduce significant manual effort across onboarding, refreshes and remediation. Automate checks, implement continuous monitoring, and focus on contextual decision making.

Growth and Retention

Contextual Engagement
Generate a complete view of the context around your customers and prospects to build better relationships, reduce attrition and find hidden opportunities.

Data Management
Connect all data—internal and third party—to create a joined-up, contextual view of all the relationships between your customers and every other domain.

Connected Customer View
Generate a complete view of the context around your customers and prospects to build better relationships, reduce attrition and find hidden opportunities.