Technology has helped cultivate an expectation of immediacy. With most things now available at the click of a button, people grow frustrated by any delay. While this is beneficial for most aspects of life, it is potentially damaging in the fight on financial crime.
One area where this is of most concern is payments. Payment speed has accelerated over the years, culminating in real-time capabilities. While this might seem beneficial to consumers, it reduces the time for financial institutions to monitor for illicit activity. Consequently, firms are looking towards new payment screening tools to resolve the challenge.
Chris Ostrowski, product management leader at Innovative Systems’ FinScan anti-money laundering (AML) compliance solution, explained, “Transaction screening has moved from a back-office control to a board-level concern because payments, geopolitics, and regulations have gone ‘real-time’ all at once.”
Consumer demands are not the sole driver towards a real-time payment’s future, with regulators also building frameworks around it. For instance, the US has launched the national real-time payment option FedNow, complimenting the already established RTP. Meanwhile in Europe, regulations like SEPA Instant and Instant Payments Regulation are also supporting the market’s move to instant settlements. This creates a landscape where increasing volumes of payments settle within seconds.
The ever-changing geopolitical and regulatory landscape is adding to the complexity compliance teams face with payment screening. It is an unprecedented time for new sanctions, tariffs, and conflict-related restrictions, with many changes coming at short notice. Furthermore, regulators are moving from a “best effort” mindset to an expectation for instant, risk-based controls that can support complex scenarios such as trade-based evasion, shadow fleets, and human-tracking flows.
“In that environment, weak or slow screening is more than an operational issue—it’s a direct route to missed risk, fines, growth caps, and reputational damage,” Ostrowski added.
The instant payment schemes that have been established require end-to-end processing in seconds, with most at 10 seconds. Within this short timeframe, systems must complete payee verification, sanctions screening, and fraud checks and they have to operate 24/7/365. Ostrowski noted, “Solutions that were built for overnight batches or ‘minutes, not milliseconds’ simply can’t keep up. Modern screening engines must parse ISO 20022 messages, multiple proprietary formats, and cross-border traffic at sub-second latency, with regulators increasingly explicit that sanctions controls must be as fast as the payment itself. That combination of volume, speed, and complexity raises the bar on both computational performance and match accuracy.”
Using technology to solve the problem
Adoption of instant payments will continue to rise. For instance, ACI Worldwide claimed there were 226.2 billion real-time payments in 2023, a year-on-year growth of 42.2%. It also estimates annual transactions will increase to over 575 billion by 2028. Similarly, a study by the Faster Payments Council claimed that between 70% and 80% of all financial institutions will enable instant payments by 2030.
As the world moves to this future, modern data-driven technology solutions will become essential for firms seeking to spot problematic payments at real-time speeds. These needs will drive organizations to enhance or replace systems they relied on for years that regulators had comfort and trust in. Now, as those institutions migrate, execution risk and concerns from those same regulators will be topics of conversation in both the successes and failures. These new systems will also create opportunities to streamline and help organizations take advantage of better data tools and improved analysis of their portfolios and payment activities.
Ostrowski explained, “Most institutions are trying to modernize payment screening while still running on legacy architectures and message standards like ISO 8583 and SWIFT, where data is fragmented, overloaded, or simply missing—creating inherent blind spots for AML and sanctions. That poor data quality fuels high false-positive rates, inconsistent matches across rails, and heavy manual rework.
“Operationally, firms struggle with fragile workflows, siloed fraud/AML teams, and case tools that were never designed for real-time alerts or multi-rail environments. Layer on procurement hurdles, budget constraints, and change fatigue, and it’s easy to see why many modernization projects stall or under-deliver.”
Firms hoping to keep pace with expanding sanctions and watchlists, as well as other geopolitical risks, will need screening platforms that can ingest layered internal and external lists in near real time, not quarterly, he added. Additionally, this system would require strong governance, including formal change management, regular risk assessments, and continuous optimization of rules and thresholds as market dynamics change. “That means tight collaboration between compliance, technology, and vendor partners, plus active horizon scanning on developments like PSD3, AI regulations, and instant payments rules so screening policies never lag the regulatory or industry rulebooks.”
Among the technologies transforming transaction monitoring and sanctions screening are AI and machine learning. They can both improve how firms prioritize alerts by learning from past decisions, identify subtle name and entity variations, and uncover anomalous behavior patterns that would be missed by humans or older rule-based solutions. On top of this, AI and machine learning boast capabilities such as dynamic risk scoring, alert triage and intelligent case summaries, freeing up time for investigators to focus on resolving flagged payments.
This doesn’t mean the technology is infallible. They are both prone to mistakes, whether it is hallucinations or data bias that create incorrect responses. Ostrowski said, “They only add value if they are transparent, trained on high-quality data, and subject to rigorous testing, governance, and model validation as regulators are increasingly clear that ‘blackbox’ models and AI-driven decisions regarding a payment or a customer must be the result of rigid model training and testing. The winners will be firms that use AI to augment human judgment, not replace it.”
The FinScan solution
FinScan is not new to the world of compliance. The solution launched in 2005, decades after Innovative Systems had already established itself as a respected enterprise-level, customer-centric data quality solution provider. Since then, FinScan has established itself as a major partner in helping financial institutions navigate the complex world of AML, focusing on eminent precision, speed, and global scale.
As firms face the challenges of real-time payments, the FinScan Payments screening solution provides them with valuable support. Ostrowski noted, “FinScan Payments is designed specifically for today’s multi-rail, instant-payment world, providing real-time, ISO 20022-ready screening across rails like SWIFT, SEPA, CIPS, FedNow, ACH, RTP, SEPA Instant, and Fedwire, with pre, mid, or post-process options.”
It combines the deep-data quality and matching heritage of FinScan parent company Innovative Systems with risk-based configuration, intelligent alert management, and sub-200-millisecond processing times for complex transactions. This enables institutions to block high-risk transactions without slowing payments. “Industry and client recognitions highlight its ability to handle complex watchlists at scale while materially reducing noise, rather than just adding another ‘fast but blunt’ filter,” he added.
False positives are a common challenge of using technology for payment screening. These are payments incorrectly flagged as problematic, requiring a human to assess the alert, critical time reviewing and causing unnecessary delays for customers. To reduce false positives, without weakening controls, firms need clean, enriched data, Ostrowski said. From there, they need to apply granular, risk-based configurations by product, corridor, and customer segment, as well as continuously tune thresholds with investigative feedback. Segmentation, intelligent suppression of benign patterns and the layering of internal risk indicators over external lists can also help reduce instances and save time for analysts.
“FinScan operationalizes this by combining a data-first approach, advanced matching, layered list support, and tailored workflows that can reduce irrelevant hits by up to eight-fold versus generic systems, while still meeting stringent sanctions and AML expectations,” said Ostrowski.
The team is always assessing market trends and customer demands to ensure it can provide clients with everything they need. As such, it offers real-time APIs, high-throughput processing, and greater support for formats, like ISO 20022. It has also invested in usability and workflow intelligence, to support clients from detection through to resolution and audit.
In the coming years, Ostrowski expects payments to transform significantly from how they look today. They will feature near, instantaneous settlement, and be more automated and specialized. Agentic systems will route payments across multiple rails including embedded finance, wallets, stablecoins and new cross-border corridors. In tandem, regulators will enforce stronger consumer protections and reimbursement for scams like authorized push payment fraud. As such, payment screening will need to move beyond simplistic name-list checks to context-aware, semantic, and data-rich risk decisions that span AML, fraud, and cybersecurity, with explainable AI embedded throughout.
Ostrowski concluded, “We’re positioning FinScan Payments and its broader AML platform to support that future through expanded rail and format coverage, more granular risk-based controls, deeper integration of data across individuals, entities, and virtual assets, and continued investment in performance and analyst experience—so clients can keep saying yes to new payment experiences without saying no to control.”
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