Transaction screening vs transaction monitoring: How do they relate?

Transaction screening and transaction monitoring are both key elements of anti-money laundering and countering the financing of terrorism (AML/CFT) and fraud risk management. Although they differ, they’re complementary: screening is part of the risk process before a transaction is approved, while monitoring reviews existing transactions.

What is transaction screening?

Transaction screening is part of the customer due diligence (CDD) element of a firm’s AML/CFT and fraud risk management. It is an essential component of a company’s regulatory compliance. When referred to as payment screening, it is explicitly tasked with detecting risk in payments before they have been approved and processed. More generally, transaction screening verifies the information attached to a transaction to ensure it does not present red flags for financial crime, especially: 

• Fraud 
• Sanctions evasion 
• Money laundering 
• Terrorist financing
• Weapons proliferation

As highlighted by Deloitte, good transaction screening tools should incorporate internal and third-party risk insights. The process should be able to identify key red flags for risks identified in a firm’s enterprise-wide risk assessment (EWRA) and in alignment with regulatory requirements. It should be able to interface with the firm’s whole range of risk data, across compliance and fraud. Finally, it should represent this data clearly to analysts, enabling them to effectively evaluate alerts and investigate, escalate, and block suspicious activity.

Several elements are key to an effective transaction screening program, which should:

• Be conducted before a transaction is approved.
• Detect sanctioned entities, locations, and activities.
• Rely on sanctions lists refreshed soon after regulators update them.
• Be well-integrated into a firm’s holistic risk data.
• Provide clear risk insights to analysts to enable effective remediation.
• Incorporate both internal and third-party risk insights

What is transaction monitoring?

Transaction monitoring is the ongoing process of monitoring transactions for risks after they have been processed. Incoming and outgoing transactions are monitored for:

• Signs of fraud.
• Signs of money laundering or terrorist financing.
• Signs of sanctions violations.
• Other unusual activity in line with a firm’s risk profile.

Ensuring an accurate, transparent data set is essential for successful transaction monitoring. A high-quality transaction monitoring solution allows firms to view all transaction alerts holistically in light of other risk data. Analysts can remediate alerts more effectively when they can see them in context of the firm’s broader risk data (such as Know Your Business (KYB) data, onboarding investigations, and transaction screening data).

An effective transaction monitoring solution should:

• Review transactions that have already occurred, ideally in real-time.
• Detect financial crime risks using rules, artificial intelligence, or a combination.
• Access other risk data, including transaction screening and previous investigations.
• Provide clear data and context to analysts.

Transaction screening vs. transaction monitoring

Transaction screening reviews transactions before they are approved, while monitoring reviews those that have already occurred. Both processes are designed to spot suspicious and unusual factors needing additional investigation. In both cases, once transactions are flagged, analysts assess the alert and determine whether the transaction is legitimate or if further investigation, escalation, or reporting is needed. 

The best tools on the market allow companies to tailor their transaction monitoring solution to their unique risk profile, determined by a regularly-updated EWRA. Firms may set rule thresholds based on their own risk exposure and appetite. Artificial intelligence (AI) can also detect hidden risks, replacing a rule-based approach or augmenting it, depending on the solution. 

The importance of transaction screening and monitoring in AML/CFT and fraud

Together, transaction screening and monitoring can allow firms to uncover hidden threats, stop or report illicit activity, and protect customers from fraud. This can help firms stay ahead of criminal typologies and evolving regulatory requirements. To do this, transaction screening and monitoring should be integrated into reliable, up-to-date, and holistic data sets. The right tools can learn from past investigations, continuously adapting to the real-life context of a firm’s risk management.

By screening and monitoring transactions in a risk-based manner, firms can meet and even exceed regulatory expectations. Efficient transaction screening can also improve customer experience and positively affect customer loyalty. 

A Deloitte study identified multiple challenges impacting transaction screening, which can also impact monitoring. Firms may want to consider reviewing their current processes for the following issues:

• Inaccurate and insufficient data – Can transaction screening and monitoring interface with the wider risk management process and access all relevant data? Does it clearly provide this data to analysts?
• Overdependency on manual processes – Manual review and risk detection can result in missed risks. Are analysts having to manually compare an alert to a wider risk context, or does the system provide relevant context? Does the system ensure the riskiest alerts rise to the top, or do analysts have to sort and filter manually?
• Too many false positives – Unmitigated false positives can result in missed true positives. Digging through queues largely made up of low-risk activity can mean true alerts aren’t seen promptly or reviewed accurately. AI-enhanced alert prioritization can help with this.
• Regulations and sanctions lists not updated automatically – Does the system have rapid access to updated sanctions data?

Transaction monitoring and screening are both vital elements of AML/CFT and fraud prevention, so it’s essential they be supported with robust tools. The right monitoring and screening solution can free up resources, help firms meet their compliance obligations, and boost business performance.

Mitigate risks with AML transaction screening and monitoring solutions

When transaction screening and monitoring are integrated into a holistic risk management function, they are powerful tools against financial crime. In order to be most effective, these processes must be supported by well-trained personnel and robust technology. Analysts supported by the right tools are better able to target high-risk activity. This means key decisions are made faster and more accurately. 

The role of technology in freeing up human expertise is well documented. The Deloitte Leaders Survey 2022 found that with smarter analytics, firms can “look for opportunities to better use this existing talent and … work on cases that involve higher money laundering risks.” 

In ComplyAdvantage’s 2023 State of Financial Crime Report, 800 C-suite and senior compliance decision-makers around the world were asked which transaction monitoring use case AI could best help them with. They identitied three key areas:

• Alert Prioritization – 31 percent of respondents expected AI to help rank transaction alerts by risk. This enables transaction monitoring teams to catch more risky activity and do it faster.
• Flexible Tuning – 26 percent thought they’d use AI to improve their alert system – helping to adjust thresholds and fine-tune alerts responsively.
• Relationship Identification – 24 percent anticipated artificial intelligence would uncover new relationships between monitored entities and individuals.

Only one percent of the respondents didn’t expect AI to benefit their transaction monitoring.

Firms should consider whether their transaction monitoring and screening tools are tailored to their unique risks. Can monitoring provide alert prioritization, flexible rules, and intelligent detection of new alerts? Even a legacy system can benefit from a machine learning overlay, which can interface with an existing rules engine and prioritize the highest-risk alerts first.