Beyond the Registry: Illuminating Hidden Assets and Their Owners

Complex corporate structures can obscure the people behind assets, businesses, and financial activity. Artificial intelligence and open-source intelligence are creating new ways for investigators across missions and jurisdictions to follow the evidence.

The Essential Question: Where are the Assets and Who Controls Them?

Consider a high value, luxury property owned by a limited liability company. That company is owned by a holding company registered overseas, which is controlled by a trust in another jurisdiction. The official records may identify each legal entity in the chain without revealing the individual who ultimately owns, controls, or benefits from the asset. For investigators pursuing financial crime, that missing identity can change the direction of an investigation.

The individual behind the structure is known as the Ultimate Beneficial Owner (UBO) - the natural person who ultimately owns or controls an entity, directly or indirectly, even when legal title is held by someone else. Identifying that person can be critical to asset tracing, anti-money-laundering investigations, anti-corruption efforts, sanctions enforcement, fraud detection, and the pursuit of illicit financial networks. These ownership arrangements are not inherently unlawful. Holding companies, trusts, and cross-border structures serve many legitimate purposes. However, when combined with nominee arrangements, multiple jurisdictions, and limited disclosure requirements, they can create formidable barriers to government oversight.

The United States, once considered a leader in corporate disclosure, recently rolled back the U.S. Corporate Transparency Act (CTA).  The CTA, enacted in 2021, was designed to combat money laundering, tax evasion, and other financial crimes by requiring companies to disclose their ultimate beneficial owners to the Treasury Department's Financial Crimes Enforcement Network (FinCEN). However, following legal challenges and concerns about regulatory burdens on small businesses, the United States dramatically scaled back its implementation in March 2025. These rollbacks exempted all U.S.-formed entities and U.S. persons from reporting requirements, leaving reporting obligations primarily for certain foreign entities registered to do business in the U.S. The result is a significant transparency gap. According to a 2026 Government Accountability Office report, the exemptions eliminated reporting requirements for more than 99% of previously covered entities, leaving investigators without a comprehensive federal registry of domestic beneficial ownership information.

On August 11, 2026, FinCEN also announced that it would delete previously collected beneficial ownership information for U.S. companies and U.S. persons who are now exempt from reporting under CTA.

We are at a crossroads.  The United States is not merely ending most future reporting requirements. It is also planning to erase much of the ownership information previously collected. For law enforcement and regulatory agencies, these developments increase the importance of investigative methods that can reconstruct ownership and control relationships quickly from independent, publicly available evidence rather than depending exclusively on government-maintained registries.

A Public-Sector Use Case: Tracing Ownership Beyond the Registry

In 2026, a large U.S. tax enforcement agency asked IVIX to help solve a long-standing issue: identifying the anonymous sellers of high-value real estate.  The agency provided  a set of real estate entities to resolve and investigate, including some the agency had already resolved and others they’d never been able to resolve on their own. The exercise illustrates a broader investigative approach: begin with a known entity, collect relevant open-source evidence, trace possible relationships across jurisdictions, and assess whether the findings identify a person exercising ownership or control. 

In this evaluation, IVIX correctly identified the beneficial owners in all cases provided by the agency, including cases its investigators had previously been unable to resolve.

This project also highlighted the importance of evidence depth. In cases where the agency had already manually determined the owner, its team reported that IVIX surfaced additional supporting sources, making ownership assessments easier to determine and substantiate. 

This type of investigation can begin with a business name (legitimate or otherwise) or individual, as well as any other “clues” to help it disambiguate. AI-assisted OSINT research  collects relevant public information, discovers connected entities and people, and automatically constructs an interactive network graph that can be explored and re-run as new relationships emerge. AI-assisted OSINT tools like IVIX can search publicly available information across multiple languages and jurisdictions, presenting findings in the investigator's preferred language alongside citations, source links, and supporting evidence.

Instead of relying on a static report or spreadsheet, investigators can explore an interactive intelligence report and ownership network, review source evidence, and ask natural-language questions of the results to guide further research.

This AI-assisted, OSINT-driven investigative approach has been applied to many different investigations spanning financial crime including those involving both digital assets and fiat, corruption, sanctions enforcement, organized crime, fraud, asset tracing, public-integrity investigations, civil recovery, and tax compliance. These investigations have helped illuminate ownership and control relationships that agencies were unable to resolve.

For a financial-crime investigator, this may mean uncovering links amongst holding companies, registered agents, subjects, witnesses, confidential informants, and assets. For an anti-corruption team, it may mean exploring possible undisclosed interests or intermediary relationships. For a civil enforcement agency, it may mean identifying leads relevant to asset recovery, misuse of government funds or regulatory oversight.

Across these missions, the central task is to understand who sits behind a legal entity, how that entity connects to a much broader network, what parts of that network show signals of wrongdoing, and to further query (in natural language) all of the evidence that brought it to light.

Why Hidden Assets and Ownership Matter Across Investigative Missions

Asset and ownership opacity can obstruct investigations in very different fields. Consider a few illustrative scenarios:

• Money laundering and asset concealment: Funds or high-value assets move through companies, trusts and digital asset addresses and blockchains that mask the people directing or benefiting from them.
• Corruption and public integrity: A company competing for a public contract may have undisclosed links to an official or intermediary with influence over the award.
• Sanctions and illicit networks: A restricted individual may exercise influence through intermediaries or layered entities that do not prominently carry their name.
• Fraud and organized crime: Seemingly unrelated companies may share controllers, facilitators, or assets, obscuring a coordinated network.
• Civil and regulatory enforcement: Hidden control can complicate asset recovery, licensing reviews, procurement oversight, and tax compliance investigations.

These examples share a core problem: a transaction, asset, or entity may be visible, while the person exercising control remains concealed behind lawful-looking structures. That gap can frustrate intelligence development, case prioritization, evidence collection, and recovery efforts. Investigators need to reconcile corporate records, litigation filings, property documents, public statements, professional connections, and other independent evidence before a meaningful ownership picture emerges. The common obstacle is the separation of apparent legal ownership from the people who direct, control, or benefit from an entity.

Across investigative missions, that separation can mean missed connections, slower investigations, costly manual research, and difficulty identifying assets or responsible parties.

Why Beneficial Ownership Registries Are Only Part of the Answer

Governments and international standard-setting bodies have pushed for greater beneficial ownership transparency through corporate disclosures, ownership registers, and reporting frameworks. These measures are valuable investigative starting points, but their coverage, accessibility, and verification vary by jurisdiction.

These initiatives are essential. But even where beneficial ownership registries exist, several practical challenges remain.

1) Corporate registry disclosures may be incomplete or inaccurate. A registry that relies on self-reported information is only as reliable as the information submitted and the mechanisms used to verify it.

2) Ownership structures cross borders.  A registry in one country may identify another company as the shareholder, requiring investigators to continue tracing ownership through additional jurisdictions with different disclosure requirements.

3) Ownership is dynamic. Transfers, restructurings, nominee changes, and changes in control can occur between reporting periods, leaving official records incomplete or outdated.

4) Trusts (and other legal arrangements) may be subject to fewer disclosure rules. This creates additional challenges when ownership or control is exercised outside conventional corporate structures.

Finally, when a registry identifies an individual correctly, an investigator must still establish how that person connects to the specific activity, asset, transaction, or network under examination. A registry is a disclosure mechanism. It is not, by itself, a complete investigative solution.

Investigative visibility requires connecting registry information with other independent evidence of ownership, influence, control, and economic benefit.

The Digital Footprints That Traditional Investigations Miss

For years, investigators have pieced together ownership networks through painstaking manual work: reviewing corporate filings, tracing legal entities across borders, checking property and court records, and following leads through disconnected sources.

Much of this work remains necessary. But the information available to investigators has changed dramatically. Businesses and individuals now leave digital footprints across a vast and growing ecosystem of publicly accessible information. Property deeds, court filings, corporate disclosures, professional profiles, company websites, online business directories, media coverage, social networks, and other digital sources can reveal connections that are not apparent in official ownership records.

An individual who does not appear in a company’s registry filing might nevertheless be identified in litigation involving that company, a professional biography, an archived corporate website, or a public record connecting them to a related entity.

Individually, these pieces of information may seem insignificant. Together, they can reveal a much larger picture. This is the power of OSINT: discovering and analyzing information from publicly available sources to develop actionable investigative insights.

Yet OSINT has historically presented its own challenge. The relevant evidence may be scattered across hundreds of websites, multiple languages, and jurisdictions, making comprehensive manual investigation extremely time-consuming.

That is where artificial intelligence is changing the equation.

AI Is Transforming the Art of Connecting the Dots

The emergence of advanced AI-powered investigative tools represents a significant shift in how beneficial ownership investigations can be conducted.

Rather than limiting investigators to predefined databases or requiring them to manually search for every connection, AI can automate much of the discovery, collection, and analysis process.

Starting with a company, individual, or other known identifier, AI-powered tools can search across lawfully accessible public sources, identify potentially relevant relationships, reconcile fragmented information, and build networks connecting individuals, companies, and assets.

These capabilities are especially powerful when several technologies work together:

• Automated OSINT collection discovers relevant evidence across public sources, languages, and jurisdictions.
• AI-powered entity resolution helps determine when different names, addresses, identifiers, or references may relate to the same individual or organization.
• Relationship mapping connects people, businesses, assets, and other entities into an interactive network.
• Evidence-based analysis allows investigators to trace identified connections back to their underlying sources.
• Natural-language interaction enables investigators to ask questions and explore emerging leads without relying exclusively on technical queries or predefined reports.

The difference is profound.

Traditional investigative tools are generally designed to retrieve information already contained within known datasets. AI-powered OSINT can go further, actively discovering relevant evidence across the open internet and following connections that were not known when the investigation began.

It is the difference between searching a list of registered owners and investigating the broader network of relationships that may reveal the person exercising actual control.

Importantly, AI-generated relationships must still be evaluated against the underlying evidence. Shared addresses, professional associations, and other connections do not necessarily establish beneficial ownership. The technology accelerates discovery and analysis; investigators remain responsible for determining what the evidence proves.

AI and OSINT offer a powerful complementary approach.

For public-sector teams, the practical takeaway is to evaluate AI-assisted OSINT tools against representative investigative cases, examine the quality and provenance of their sources, and assess whether investigators can pursue emerging leads while maintaining a reviewable record of how findings were reached. Contact IVIX at sales@ivix.ai for more information.

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References:

1 - https://www.fincen.gov/news/news-releases/fincen-removes-beneficial-ownership-reporting-requirements-us-companies-and-us

2 - https://www.gao.gov/products/gao-26-107967

3 - https://home.treasury.gov/news/press-releases/sb0603