With the rapid evolution of regulatory environments, the pressure on financial institutions (FIs) to effectively detect and prevent money laundering while staying compliant with the changing pace of regulatory requirements is greater than ever.
However, with the right tools and strategies, this pressure can be effectively managed.
Regulatory scrutiny is intensifying, economic crimes are increasing in sophistication, and many traditional rule-based systems are struggling to keep up with the complexity and volume of financial crime. Combined with the added challenges of high false rates, fragmented data and ecosystems, and limitations in both staffing numbers and staffing knowledge, FIs are under harsh scrutiny to ensure compliance.
Three challenges stand out in particular:
1. Data silos: The first hurdle
One of the biggest challenges in transaction monitoring is the persistence of data silos. As long as traditional silos continue to persist across fraud and anti-money laundering functions, FIs will lack a holistic view of their customers. The interconnected nature of financial crime requires the dismantling of these silos. However, integrating disparate data sources, investigations, and platforms into a unified anti-money laundering (AML) solution is a significant challenge.
2. Evolving to keep pace with crime
Financial crime methods change daily. To keep pace, Fis must continually reassess and update their AML detection and monitoring strategies. As threats and technology evolve, so must AML programs.
3. Escalating regulatory environment
Driven by technological innovation, geopolitical shifts, cryptocurrencies, and decentralized finance (DeFi), among other factors, the regulatory landscape for AML compliance is undergoing significant change. These forces are driving legislative updates across multiple regulatory bodies, requiring FIs to stay current with ever-changing requirements. This comes at a substantial cost – both financially and in terms of resources.
Rethinking AML for the modern era
FIs need to rethink their AML approach. The answer lies in data-driven workflows and the integration of AI. Traditional rule-based systems are no longer sufficient to combat the complexity of financial crime. This is where AI comes into play.
At SureStep, we’ve witnessed the transformative power of AI in AML. By starting small and then scaling, FIs can begin their AI journey in AML.
Start with key paint points
The idea is simple but strategic. First, identify key pain points. Is your institution struggling with high false-positive rates? Are manual investigations bottlenecking your workflows? Do you experience inefficient KYC onboarding or struggle to detect complex money laundering patterns?
Once these pain points have been identified, you can begin embedding AI into the existing AML process. Rather than trying to overhaul your entire AML infrastructure overnight, start with a single, well-defined use case based on the previously identified pain points. This approach reduces risk, allowing you to fine-tune AI integration before expanding across the entire program. Once successful, this can serve as a proving ground to demonstrate value and build internal momentum.
Demonstrate value through AI in practice
For example, consider the challenge of manual investigation bottlenecks. By supporting investigations with AI-generated case summaries, intelligent alert triage, network analytics and SAR narrative generation, investigators can reduce manual documentation time, improve consistency and decision quality, and focus on high-value, high-risk cases.
One approach we use at SureStep is to start with a simple use case. We bring it into the platform, demonstrate success, and then expand it to handle an increasing number of use cases. Building a proper foundation from the beginning makes all the difference for long-term scaling.
Choose the right technology partner
As critical as it is to start small with AI, it’s arguably more important to choose the right vendor for your AML and analytics program. In today’s fast-paced financial services environment, institutions need more than just point solutions – they need platforms that can evolve with them.
SureStep has partnered with SAS to deliver SAS Anti-Money Laundering on SAS® Viya® to FIs of all sizes. With SAS Viya, tackling escalating financial crime threats, implementing AI, and scaling across the enterprise is not only possible but practical. Its practicality ensures seamless integration into existing systems, making the transition to AI-powered AML smoother and more efficient.
In the following video, I explain why SAS Viya stands out as a uniquely powerful platform for FIs.
The challenges facing FIs – including fragmented data, evolving financial crime, and increasing regulatory pressure – all require thoughtful and adaptable solutions. SAS AML on SAS Viya is designed to meet these challenges head-on. Its adaptability ensures that it can keep pace with the rapidly changing financial crime landscape, providing the tools you need to stay one step ahead of potential threats.
Coming full circle, here’s how SAS AML on SAS Viya addresses the three challenges I mentioned at the beginning of this blog post – plus an extra point that’s mission-critical for forward-thinking FIs.
Breaking down data silos
SAS AML on SAS Viya helps bring together data across fraud, AML, and customer due diligence systems into a unified view.
This integration supports more consistent investigations and enables teams to gain a better understanding of customer behavior across channels.
Adapting to shifts in financial crime
Because financial crime evolves rapidly, detection strategies must be adaptable and responsive to changing circumstances. SAS AML on SAS Viya includes built-in machine learning, anomaly detection, dynamic risk scoring, and network analytics.
These capabilities help uncover complex patterns that traditional rules might miss, allowing teams to respond more quickly and effectively – and to adjust their detection strategies as threats evolve.
Navigating regulatory complexity
With regulatory expectations evolving at an exponential rate, institutions need tools that support transparency and responsiveness. The platform offers capabilities for regulatory reporting, scenario testing, and explainable AI, featuring automated SAR narrative generation and case summaries that reduce manual effort and enhance consistency in documentation.
Supporting scalable innovation
The platform’s cloud-native design means institutions can start with a focused use case and expand over time. SAS AML makes it easier to test new approaches, demonstrate value, and build internal support without requiring the overhaul of existing infrastructure.
By aligning technology with real-world challenges, institutions can take practical steps toward more effective and efficient detection of financial crimes. Together, SAS Viya and SAS AML offer a flexible and scalable approach to combating financial crime – one that supports incremental innovation, enhances operational efficiency, and helps FIs stay compliant with regulatory expectations.
