Beneficial ownership has long been one of the most challenging aspects of anti-money laundering, but the task is becoming significantly more complex. Multi-layered corporate structures, cross-border entities, trusts and nominee arrangements can obscure who ultimately owns or controls an organisation, making it increasingly difficult for financial institutions to distinguish legitimate complexity from deliberate concealment.
As criminals exploit these structures to disguise illicit wealth, AML frameworks are under growing pressure to evolve beyond static ownership checks. Can advances in data, analytics and AI provide firms with a clearer view of beneficial ownership, or are increasingly sophisticated ownership networks continuing to outpace the industry’s ability to detect financial crime?
How firms are managing CBO requirements
How are companies managing increasingly complex beneficial ownership requirements? In the view of Scott Nice, CRO at Label, companies are managing beneficial ownership requirements through documentation, customer outreach, registry checks, ownership charts, screening, enhanced due diligence and manual analyst review.
He added, “The challenge is that ownership complexity is increasing faster than many operating models are evolving. Layered entities, cross-border structures, trusts, nominee arrangements, private investment vehicles, family offices and fund structures can all make it difficult to identify who ultimately owns, controls or benefits from a customer relationship.”
For Nice, the challenge is not just collecting information – as companies can obtain documents and still struggle to understand what the structure means. “They need to know whether the ownership chain is complete, whether the information is consistent, whether the structure has a legitimate commercial rationale and whether there are control or influence factors that do not appear neatly in a shareholding percentage,” the Label CRO made clear.
A key issue is that many firms are still too dependent on static files and periodic refresh cycles. This, Nice believes, creates risk because ownership structures can change, and risk can change with them.
He added, “The firms that manage this best combine better data, stronger workflow and clearer escalation. They do not treat beneficial ownership as a box-ticking exercise. They build an evidence base that shows what was reviewed, what was understood, where uncertainty remains and why the final risk position was reached.”
Meanwhile, Zurab Kotaria, CEO and co-founder of Identomat, stressed that most firms are trying to manage beneficial ownership requirements through a combination of information collection, screening, registry data, document checks and manual revirew.
He believes the key challenge is that ownership structures are rarely static. “A company can have several legal entities, shareholders in different jurisdictions, nominee arrangements, or changes in ownership that are not immediately visible. This means firms need more than a one-time view of business.”
In the view of Kotaria, instead, they need a process that helps them understand who ultimately owns or controls the company, verifies the people involved and identify when something important has changed.
He added, “In practice, the strongest approach is usually risk based. Not every business requires the same level of investigation, but higher-risk structures need more scrutiny, stronger evidence, and more frequent review.”
Is ownership tougher to identify than risk?
A question being faced down currently in the industry is whether the identification of ownership has become harder than identifying risk.
Michael Thirer, CLO at Muinmos is of the view that identifying ownership is definitely one of the most complex, if not the most complex, area in AML. This, because corporate structures are increasingly layered across multiple jurisdictions, trusts, nominee shareholders, and holding companies.
Thirer sees two key ways that firms are dealing with this. “First of all, better tooling. This includes applying tools for visualisation of corporate structures, connected to global, reputable data-sources.
“These allow compliance teams to uncover all that is available online, before any additional investigation, if required,” he added.
Another area is making sure teams have ample time for this task. Compliance teams, Thirer stressed, are often tied in countless administrative tasks, back-and-forth with clients, moving files between systems. “Firms are realizing that these tasks take teams’ time from high-end tasks like UBO investigation, and they therefore adopt solutions that will give them the required breathing-room for this,” said Thirer.
Thirer summed this up simply. “Give them the best tools, both from data and visualisation perspectives, and give your teams more time to focus on high-level tasks by reducing the administrative workload.”
Kotaria said that identifying ownership and identifying risk are closely connected. “In many cases, you cannot properly assess the risk around a business until you understand who ultimately owns or controls it.
A company may appear low-risk on the surface, but the picture can change once you identify a beneficial owner with sanctions exposure, adverse media, PEP connections, or links to higher-risk jurisdictions.”
Therefore, ownership verification is not separate from risk assessment and is often one of the key parts of it. The challenge, he says, is that ownership information can be fragmented, outdated or difficult to verify across different jurisdictions.
“That makes it harder for firms to build a reliable view of both the company and the risks connected to it,” Kotaria added.
Nice is of the view that this is true in some cases. “Firms may be able to see that a structure feels high-risk before they can fully evidence who ultimately owns or controls it. AML teams may identify indicators of opacity, complexity or unusual structuring, but still need to work through incomplete information, inconsistent documentation or data spread across multiple jurisdictions before reaching a clear conclusion.”
However, he claims risk can sometimes be visible through patterns: unusual complexity for the customer type, connections to higher-risk jurisdictions, nominee indicators, unexplained intermediaries, adverse media, circular ownership or inconsistencies between the customer profile and the structures being presented.
“Ownership, by contrast, may require legal documents, registries, declarations, control analysis and a careful understanding of how the structure actually works,” said Nice.
This is why Nice is of the stance that beneficial ownership should not be treated as a purely mechanical threshold exercise. A percentage test may be useful, but it does not always capture control, influence or economic benefit. “In some cases, the most important risk may sit with someone who does not appear as a straightforward majority owner,” he finished.
The role of technology
What role can tech play in untangling opaque corporate structures? Kotaria believes that technology can make a major difference by helping compliance teams collect, organise, and review information more efficiently.
He said, “Solutions such as Identomat can support the verification of company representatives, help identify inconsistencies in submitted information, connect ownership data with AML screening results, and flag changes that may require further attention. They can also reduce the amount of repetitive manual work involved in reviewing straightforward cases.”
Max Worrall, EMEA Account Executive at Cascade, is of the view, meanwhile, that technology can help untangle opaque corporate structures by using AI, data analytics, and digital registries to identify beneficial owners, map complex ownership networks, and detect suspicious patterns across multiple jurisdictions.
He stated, “Developments in CLM technology allow clients to validate and supply supplemental validating complex structures both onboarding and at periodic review. This is an important evidential regulatory step which can now be completed with minimum to little client direct involvement therefore reducing outreach and enhancing the overall client experience.”
Technology is becoming an essential tool for helping firms make sense of increasingly complex ownership structures, according to Nice. Rather than simply mapping who owns what, modern platforms can reveal the relationships between entities, individuals, directors, shareholders, addresses and jurisdictions, bringing into focus risks that may not be apparent from reviewing a single company record in isolation.
As Nice explains, “The risk is not obvious from one document or one company record. It sits in the relationships between entities, individuals, directors, shareholders, addresses and jurisdictions.”
By connecting those relationships, technology can help analysts identify circular ownership, repeated addresses, shared directors, discrepancies between documents and changes in ownership over time, while consolidating internal records, external data, screening results and transaction information into a single view. AI is also proving valuable for reviewing large volumes of company documents and extracting relevant data, but Nice is clear that it should augment – not replace – human judgement.
“The firm still needs to decide whether the structure is reasonable, whether the explanation is credible, whether enhanced due diligence is needed and whether the relationship remains within risk appetite,” he says. “Technology will not remove ownership complexity, but it can make it easier to see, manage and assess consistently.”
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