The world of compliance is changing rapidly. New sanctions packages, stricter anti-money laundering rules, and the arrival of the European supervisory authority AMLA are putting pressure on organizations to continuously improve their processes and data quality. During a recent compliance event organized by Altares Dun & Bradstreet, we examined how professionals are preparing for this future. The results show a clear trend: a shift from reactive compliance to proactive, data-driven risk management.
Reassessment based on events and triggers
Many organizations indicate that reassessments of customers or suppliers are mainly triggered by changes in public positions, negative publicity, or changes in ownership structure. A differentiation is made between events, i.e. actual changes in the customer structure, such as a new UBO or management change, and triggers, signals from monitoring or screening, such as a PEP hit, sanction notification, or negative media attention.
This approach demonstrates that companies are increasingly adopting a dynamic approach to risk assessment. Instead of fixed annual schedules, risk profiles are continuously assessed against current signals. The combination of sanctions data, PEP monitoring, and adverse media analysis forms the core of this approach, with an increasing emphasis on early risk recognition: the timely identification of changes that could affect the integrity or reputation of an organization.
Interesting read: What data do you need for an effective compliance process?
Technology as an accelerator, not as a goal
The results indicate that compliance teams no longer view technology as a standalone solution, but rather as a means of strengthening their integrated approach. Automation, workflow support, and data links are primarily used to reduce manual work and to make decisions faster and more informed.
At the same time, the human factor remains indispensable. Governance, process discipline, and knowledge of regulations still form the backbone of any effective compliance program. The future therefore lies not in more tools, but in smart collaboration between people, processes, and technology.
Where AI truly adds value
Artificial intelligence has now found its way into the compliance chain. Organizations are experimenting with automatic detection of suspicious patterns, document recognition during onboarding, and intelligent screening that reduces noise. For the time being, the priority lies with practical applications that deliver immediate efficiency gains, rather than predictive models.
AI is primarily used to reduce daily workloads and make decisions more consistent. This pragmatic approach is in line with the focus of regulators, who are increasingly emphasizing effectiveness over formality. The most important question is: does a system actually do what it promises? AI is primarily used to reduce daily workloads and make decisions more consistent. This pragmatic approach is in line with the focus of regulators, who are increasingly emphasizing effectiveness over formality. The most important question is: does a system actually do what it promises?
The European context: AMLA and dynamic sanctions
The creation of the Anti-Money Laundering Authority (AMLA) in Frankfurt marks a new era of European supervision. Whereas national supervisors previously focused primarily on processes, AMLA will explicitly examine the effectiveness of detection and prevention systems.
Organizations that have their data quality and monitoring processes in order will soon be in a significantly better position. At the same time, the sanctions landscape is constantly changing. The EU regularly expands its measures. Since 2022, several new sanctions packages have been added, with direct consequences for screening lists, transaction monitoring, and due diligence processes.
Flexibility in tooling and datasets is therefore essential. Not only to keep the number of false positives manageable, but above all to prevent false negatives and guarantee the integrity of decisions.
Interesting read: Compliance vs risk management: what is the difference and why do you need both?
From insights to action: five recommendations
- Make risk triggering dynamic. Have reassessments occur automatically when relevant events occur, such as PEP hits, negative media coverage, or changes in ownership.
- Reduce noise in screening. Enrich alerts with contextual data such as jurisdiction, relationship strength, and historical patterns to improve prioritization.
- Digitize document flows. Use OCR and NLP to automatically extract data from business documents, validate it, and link it to customer files.
- Strengthen model governance. Ensure that AI and rule-based models are traceable, explainable, and auditable.
- Prepare for European supervision. Measure the effectiveness of your processes, for example in terms of hit rates, turnaround times, and quality indicators, and carefully document your data flows.
How Altares Dun & Bradstreet can support
Altares Dun & Bradstreet helps organizations worldwide strengthen their compliance fundaments. Our solutions combine reliable company and UBO data with intelligent screening, continuous monitoring, and AI-driven data processing. This enables compliance teams to identify risks faster, automate processes, and demonstrate that their policies are truly effective. The future of compliance lies not in more rules, but in better insight. And that starts with reliable data.
Conclusion
The survey among our clients confirms what we see in practice every day: compliance is evolving from a control function to a strategic business partner. By intelligently combining technology, data, and governance, organizations are building a future in which integrity, transparency, and efficiency go hand in hand.
Curious about how your organization can apply these insights in practice? Discover how our compliance solutions can help you manage your risks more intelligently here.
