Reframing Due Diligence in 2026: AML, KYC, and the Expanding Role of Public Data in Europe

By Liga Vinkele, CEO and co-founder at Fintelligence

In 2026, anti-money laundering (AML) and know your customer (KYC) frameworks across Europe are undergoing a structural transformation. What was once a compliance-driven, procedural function is now a strategic discipline shaped by geopolitical risk, technological advancement, and regulatory harmonization. Financial institutions are no longer assessed solely on whether they perform due diligence, but on how effectively they identify, interpret, and act on risk signals, including those from publicly available information.

At the center of this evolution is the European Union's push toward a unified AML regime. The establishment of the Anti-Money Laundering Authority (AMLA), which assumed its full mandate from the EBA in January 2026 and will begin direct supervision of selected high-risk financial institutions in 2028, marks a significant shift from fragmented national supervision to centralized oversight. AMLA is tasked with directly supervising selected financial institutions and coordinating enforcement across member states, thereby raising expectations for consistency, data quality, and risk-detection capabilities.

Alongside AMLA, the EU’s AML package (AMLR/AMLD6) introduces stricter and harmonised requirements for customer due diligence, beneficial ownership transparency, and ongoing monitoring. It reinforces a risk-based approach, requiring institutions to dynamically assess and update customer risk profiles based on risk, rather than relying solely on fixed periodic reviews.

Within this regulatory context, KYC is no longer a one-time onboarding exercise. Instead, it is an ongoing process embedded within broader AML obligations. Institutions must demonstrate a clear understanding of who their customers are, how they generate wealth, and whether their activities align with expected behavior over time. Any deviation - such as sudden changes in transaction patterns or emerging negative media - must trigger enhanced scrutiny. This is where public information screening becomes operationally critical. European regulators increasingly expect institutions to incorporate adverse media checks into both onboarding and ongoing monitoring processes. Negative news related to fraud, corruption, bribery, money laundering, terrorist financing, sanctions evasion, tax evasion, organized crime, human trafficking, cybercrime, proliferation financing, or ESG controversies can materially affect a customer’s risk classification. Failure to identify such information is often viewed as a gap in the institution’s AML controls.

However, the practical implementation of effective public data screening remains challenging. The volume of relevant information has grown exponentially. Moreover, Europe’s linguistic diversity adds complexity: risk-relevant content may appear in any EU language, as well as in third-country sources linked to cross-border clients. Manual screening approaches are increasingly misaligned with these realities. They are resource-intensive, difficult to standardize, and vulnerable to inconsistency. In particular, AMLA and national competent authorities are placing greater emphasis on auditability and evidence - institutions must be able to demonstrate not only that checks were performed, but that they were comprehensive and proportionate to the risk.

As a result, financial institutions are accelerating the adoption of AI-driven screening tools to support AML and KYC processes. These technologies enable automated analysis of large volumes of multilingual, unstructured data, significantly improving both coverage and efficiency. More importantly, they allow for continuous monitoring - an essential requirement under the EU’s evolving regulatory framework.

From a compliance perspective, the integration of AI technologies supports several key regulatory expectations. Risk-based due diligence is strengthened through automated screening, allowing institutions to apply differentiated levels of scrutiny based on customer risk profiles, which is a core principle of EU AML regulation. Ongoing monitoring is enhanced through continuous data analysis that enables the detection of emerging risks in near real time, rather than relying solely on periodic reviews. In addition, cross-border consistency is reinforced through multilingual processing, which helps reduce geographic and linguistic blind spots, particularly for institutions operating across multiple jurisdictions.

"The objective of modern due diligence is not merely to collect data but to generate actionable intelligence."

Importantly, these developments extend beyond the banking sector. Under the EU AML framework, a wide range of “obliged entities” - including investment firms, real estate professionals, and certain legal and corporate service providers - are subject to AML/KYC requirements. In 2026, many of these sectors are facing increased oversight, particularly in areas such as beneficial ownership transparency and sanctions compliance.

The objective of modern due diligence is not merely to collect data but to generate actionable intelligence. In the AML/KYC context, this means identifying meaningful risk signals early and integrating them into decision-making processes in a timely and consistent manner.

In conclusion, the European AML and KYC landscape in 2026 is defined by three converging forces: regulatory centralization, data, and technological innovation. Public information screening has become an important component of compliance frameworks. Institutions that can effectively integrate AI-driven insights into their AML/KYC processes will be better positioned to meet regulatory expectations, mitigate financial crime risk, and maintain operational resilience in an increasingly complex environment.

About Fintelligence

Fintelligence leverages AI to transform global, unstructured public data into real-time risk intelligence by automating due diligence across languages, jurisdictions, and complex risk domains. The tool focuses on gathering and analyzing publicly accessible information about potential clients or partners, including both individuals and companies. It identifies significant risks that could affect partnerships, including anti-money laundering (AML) concerns, involvement in war support, sanctions evasion, ESG risks, and other negative factors. Supporting searches in over 100 languages (and also preparing reports in these languages), the solution generates comprehensive reports to aid informed decision-making. In addition, Fintelligence incorporates sanctions screening and politically exposed persons (PEP) checks as part of its broader compliance framework.