A common assumption in shareholding disclosure compliance is that once thresholds are known, compliance becomes a data exercise. Pull in reliable data, map thresholds to securities, monitor positions, and file when limits are breached.
This assumption overlooks key factors, which becomes clear as firms adopt this approach and recognise that disclosure obligations aren’t driven by thresholds alone. Instead, they’re a product of interpretation, jurisdictional nuance, instrument treatment, and operational execution. It’s in managing this difference between regulatory text and operations that creates failures resulting in fines, breaches, and reputational damage takes place.
The complexity in going from a regulatory memo to successful disclosure, or the avoidance of a disclosure, is underestimated. The issue is not simply data quality, but the oversimplification that data alone is enough to solve a regulatory problem. That reality is on display in several areas of shareholding disclosure monitoring.
Thresholds are just one component of disclosure regulation. And before numeric thresholds can be considered, teams need to apply jurisdiction-specific logic to rules. This includes aggregation rules, control structures, voting rights treatment, exemptions, look-through obligations, instrument classification, the netting of positions and the handling of cash or physically settled derivatives. It’s a tall task that requires both expertise and detailed execution.
Regions with harmonised frameworks frequently add stricter, local requirements, too. Compliance teams encounter market-specific rules and submission requirements, instead of consistent formats.
Operationally, teams must translate regulatory language into logic that fits their workflows for each jurisdiction they invest in. This is all before the ‘data-only’ approach begins.
Disclosure calculations rely on issuer-level information such as shares outstanding and voting rights totals. If those denominators are wrong or outdated, every threshold calculation becomes wrong and every disclosure unreliable. A data-only approach has no mechanism to validate whether the numbers it receives are correct. It assumes the data provider is always right.
Even the best data providers occasionally publish incorrect or outdated numbers. Relying solely on feeds means that, to ensure every denominator’s accuracy, teams would need to validate through issuers themselves.
Independent cross-checking of denominators provides a critical control layer. FundApps compares every client’s (anonymously and in a segregated environment) issuer-level data against the entire FundApps community and highlights outliers for shares outstanding, treasury shares and voting rights. Without doing so, these issues often remain hidden until regulators or internal reviews uncover inconsistencies. At that point it’s too late.
When a ‘data-only’ approach attaches a percentage limit to a security based on its country of incorporation or primary listing, it prioritises efficiency at the expense of risk. If the country code is incorrect, it creates a waterfall, where every security is associated with the wrong threshold, and every issuer in that market is misclassified. The risk is multiplied across the entire portfolio in an instant.
The problem is further complicated by the simple fact that global issuers do not sit or list neatly inside one country. Unfortunately, it’s not that simple. Instead, many issuers trigger obligations across several jurisdictions simultaneously. A ‘data-only’ approach won’t capture this.
HSBC is reportable in both the UK and Hong Kong, each under different regimes, deadlines and forms.
Any Swiss issuer may require disclosure in Switzerland, but if it has a section 12 listing in the United States, it also becomes reportable under the SEC regime. If that same Swiss issuer is listed in Frankfurt, it becomes subject to EU Transparency Directive requirements. Every jurisdiction has its own aggregation rules, attribution logic, exemptions and reporting templates.
Ultimately, this forces compliance teams into slow, reactive processes with time wasted. Data feeds limited to a single country can’t determine which regimes apply. They can’t handle exemptions. They cannot generate the appropriate forms.
Scalable compliance requires jurisdiction logic embedded into the workflows themselves, not simply country tags attached to securities.
Data remains essential, but it does not provide interpretation, workflow, or defensible decision-making. Firms evaluating solutions typically face three broad options:
Of the three, the last option scales successfully.
The core challenge is not data quality but misunderstanding the nature of disclosure compliance. It is an interpretation and operational execution problem supported by data, not solved by it.
Firms that recognise this early build scalable frameworks. Those that treat disclosure as a data tagging exercise often discover the limits only after obligations are missed or questioned, when fixing the problem becomes far more costly than getting the approach right from the start.
FundApps' Shareholding Disclosure is built to scale with firms as their needs develop, before risk compounds. A dedicated rules library supported by a team of regulatory experts, across more than 100 jurisdictions. Learn how the FundApps Shareholding Disclosure service helps managers make the most of their data.