Ready, Set, Comply with IPR – Part 2

The Instant Payments Blog Series

Part 2: AI-powered Defense in the Age of Instant Payments

In January 2025, the European Instant Payments Regulation (IPR) will make instant payments the new standard across Europe. With transactions settled within seconds, IPR promises unparalleled convenience and efficiency. The IPR’s primary goal is to create a fast, secure, and ubiquitous payment system that supports real-time transactions, whether domestic or cross-border. However, this speed introduces new risks for financial institutions, as threats like money laundering (ML) and terrorism financing (TF) often lag behind the rapid movement of money. 

As payment flows accelerate, the need for financial institutions to adapt their monitoring systems is more urgent than ever. Traditional transaction monitoring systems, designed for slower payments, will no longer suffice. Financial institutions need advanced tools that allow them to detect anomalies and risks much faster — ideally within the same day or even within hours. These systems play a crucial role in flagging suspicious activity for timely investigation, and help institutions remain compliant and vigilant in an era of instant payments.

What does IPR mean for transaction monitoring practices?

IPR redefines the standard for both domestic and cross-border payments, making transaction speed a key feature. This acceleration, however, puts significant pressure on financial institutions to detect potential risks sooner. Traditional batch-processed monitoring, which might analyze transactions days later, won’t suffice in an IPR world. 

Instant payments are not only a shift in how money moves — they’re also changing how financial institutions monitor transactions. This shift demands a reassessment of transaction monitoring, especially for cross-border payments, which inherently carry higher risks of money laundering, and will now need to be tracked almost in real time. Post-transaction detection systems allow for pattern analysis, generating alerts for investigators to review and ensure suspicious activity doesn’t slip through undetected. In the context of cross-border payments — where risks of money laundering and financing of terrorism are particularly high — this same-day detection is crucial to stay ahead of evolving threats. 

Monitoring thousands (or millions) of payments each day, requires an entirely different approach. Banks and fintechs must be able to scan payments quickly and accurately, flagging any suspicious activity without delay. 

Intra-day detection & response: The new normal

Real-time detection in the context of AML doesn’t mean stopping transactions before they’re completed. Instead, it refers to identifying suspicious patterns within hours — or even minutes — of a transaction occurring. This shift from reactive to proactive detection means institutions are driven by the requirements of the European IPR, which mandates that institutions handle payments in a much more timely manner while ensuring compliance with AML and CFT regulations. The faster the transaction speeds leave no room for traditional batch processing or delayed reviews. It requires institutions to implement advanced monitoring systems that quickly analyze data, detect anomalies, and generate actionable alerts. By meeting these new demands, financial institutions can spot risks sooner, empowering investigators to take timely action before risks escalate.  

For example, if a suspicious pattern emerges in funds moving to high-risk jurisdictions, a same-day alert ensures investigators are aware promptly. Although the transaction may have already been completed, early detection minimizes potential cascading risks, such as additional linked transactions or a larger laundering operation. 

With the surge in transaction volume and the expedited pace of payments, monitoring systems must filter through vast amounts of data in seconds, highlighting patterns that indicate potential illicit activity. This includes identifying anomalies, such as rapid fund transfers to high-risk jurisdictions, or identifying patterns of behavior consistent with money laundering or terrorism financing.

Beyond detection, institutions must also act quickly to mitigate risks. By moving from a reactive to proactive stance, financial institutions can ensure they stay one step ahead of criminals trying to exploit loopholes in systems.. 

AI & machine learning — The brainpower for smarter, faster insights

In a world of IPR, the sheer volume and velocity of transactions require advanced tools. This is where artificial intelligence (AI) and machine learning (ML) come into play. These technologies allow systems to detect patterns and anomalies in vast amounts of transaction data, automating the identification of potential risks.

Machine learning excels in uncovering patterns of anomalous activity, such as unusually structured transactions or funds moving through unexpected channels. For example, it can quickly identify suspicious behaviors, such as structuring transactions to avoid detection or funneling funds to high-risk regions. Over time, these AI systems continually learn, refining their ability to spot emerging threats and adjusting their models to stay ahead of new tactics used by criminals. 

One key advantage of AI is its ability to adapt. Traditional monitoring systems used by banks and financial institutions often rely on predefined rules and historical data, making them less effective at identifying novel threats or emerging patterns. For example, if a new method of terrorist financing appears, these legacy systems may miss it entirely until the rules are manually updated — a process that can take significant time. In contrast, AI-powered systems are dynamic. They can quickly adjust their algorithms to recognize new threats, offering a level of agility and real-time adaptability that traditional systems simply can’t match. This shift not only enhances detection but also provides greater confidence in compliance with evolving regulations, such as those governing European Instant Payments. 

Enhanced risk assessment for terrorism financing

AI doesn’t just help detect money laundering; it also plays a critical role in combating terrorism financing. One of the most important roles of AI in this context is dynamic risk assessment. By analyzing transaction data in real time, AI systems can assess the likelihood that funds are being used for terrorist activities. 

AI-powered systems track the flow of funds across borders, identify links to high-risk regions, and analyze customer behavior to build a comprehensive risk profile. For example, AI might flag transactions moving large sums of money into regions with known terrorist activity. It can also detect when funds are being funneled into increasingly complex financing structures designed to evade detection. 

By shifting the focus from merely detecting money laundering to also identifying terrorist financing networks, AI is transforming real-time compliance. It provides a level of sophistication and accuracy that traditional systems can’t match. 

Automating compliance to keep up with the speed of IPR

AI and automation offer substantial risk mitigation benefits for instant payments. Financial institutions need to ensure that each transaction is monitored for AML compliance without slowing down the system. Automated workflows powered by AI can guarantee that every transaction is screened instantly, and that suspicious activities are flagged for immediate review. 

But it doesn’t stop there. Automation also plays an important role in regulatory reporting. Under IPR, financial institutions will need to generate timely and accurate reports on suspicious activities. With automation, this becomes far less burdensome. Compliance teams no longer need to manually process each alert or generate reports — AI systems can take care of this efficiency, reducing human error and speeding up regulatory submission. 

In the fast-paced world of instant payments, automation isn’t just about efficiency — it’s about assuring compliance at the speed of transactions. 

Gaining Insights into customer behavior to improve trust & services

Beyond security and regulatory compliance, real-time monitoring powered by AI can also provide deeper insights into customer behavior. By understanding legitimate patterns of behavior, AI can help financial institutions better serve their customers with more personalized services and improved customer experiences.

Transparency is another key benefit. A robust, real-time AML strategy powered by AI can improve trust with customers, regulators and stakeholders. When institutions can demonstrate their commitment to safeguarding against financial crime, they create an environment of trust and transparency. Customers and regulators alike appreciate transparency and a strong approach to managing risks. 

The road ahead for instant payments & AML

As transaction speeds increase, financial institutions must evolve their transaction monitoring systems to keep pace. Real-time monitoring and AI-driven systems are no longer optional — they are essential tools for ensuring compliance with AML and combating terrorism financing. 

As instant payments gain momentum, the demand for sophisticated, proactive defense mechanisms will only increase. Institutions that stay ahead by upgrading their monitoring systems, partnering with advanced technology providers, and equipping their compliance teams with training on evolving regulatory requirements, will be well-positioned to tackle the challenges of the instant payments landscape — and those that lie ahead. By prioritizing safety, security, and compliance, these institutions can safeguard both their customers and the broader financial ecosystem. In the new era of IPR the future of payments is fast, and so must be the defenses that protect them.