Most compliance programmes can answer the question of who owns a given entity. Far fewer can reliably determine whether a corporate structure has been deliberately designed to prevent that answer from being found.
That distinction sits at the heart of Article 12(1)(d) of the Anti-Money Laundering Authority’s (AMLA) draft Regulatory Technical Standards (RTS) on Customer Due Diligence — and it represents a fundamental shift in what obliged entities must be able to demonstrate.
This sat at the center of a recent discussion from Cleverchain in a whitepaper, who discussed the topic of ‘Detecting Opacity by Design‘ and why the draft AMLA CDD Standards demand investigative judgment on complex structures, and what that means for every compliance programme built around verification and screening.
The provision requires firms to assess whether a corporate structure obfuscates or diminishes ownership transparency with no legitimate economic rationale. This is not a binary question. It cannot be resolved through a registry check, a screening match, or an automated score. It demands evidence-based investigative reasoning, documented in a form that can withstand supervisory scrutiny.
A qualitative standard, not a structural checklist
Conditions (a) to (c) of Art. 12(1) can be resolved through structural facts — legal form, jurisdiction, nominee status. Condition (d) cannot. For the first time, EU regulatory technical standards require obliged entities to perform a structured qualitative assessment of whether a corporate architecture is itself a risk indicator, rather than simply identifying and verifying the entities and individuals within it.
The compliance function must detect opacity, test for rationale, and document both sides of that determination. That is a materially different operating model from the one most institutions currently run.
Why legacy CDD architectures fall short
The vast majority of Customer Due Diligence (CDD) programmes are built around binary controls: verification (does this entity exist?), screening (does this name match a list?), and threshold-based Ultimate Beneficial Owner (UBO) identification (does any natural person hold 25% or more?). None of these controls produces the qualitative, evidence-weighted reasoning that condition (d) demands.
Corporate registries confirm that a legal entity exists — they do not assess whether an arrangement of entities serves a legitimate commercial purpose. A holding company with no employees, no commercial activity, and no function beyond interposing a layer between a customer and its beneficial owner can appear in a registry as a perfectly valid legal entity. Its filing status may be compliant and its directors identifiable, yet none of that information addresses condition (d).
Screening tools, meanwhile, operate on individual entities and persons — they test whether a name matches a list. A chain of four holding entities across three jurisdictions, each individually clean, may collectively represent a deliberate opacity arrangement. No screening engine will surface that finding, because the risk lies not in any individual entity but in the relationship between them and the absence of commercial rationale for how they are arranged.
Similarly, the standard 25% beneficial ownership threshold answers the question of who owns more than a quarter of an entity — not why the ownership chain is structured as it is. The gap is not a feature deficit in existing tools; it is an architectural mismatch between their design and the regulatory requirement.
The regulatory timeline and the harmonisation gap
The Anti-Money Laundering Regulation (EU) 2024/1624 (AMLR) harmonises CDD obligations as a directly applicable regulation across all Member States from 10 July 2027. On 9 February 2026, AMLA published its consultation paper on the draft RTS under Article 28(1), specifying how obliged entities must apply CDD requirements in practice. The consultation remains open until 8 May 2026.
AMLA must submit the final draft RTS to the European Commission by 10 July 2026. Following adoption and parliamentary scrutiny periods, the realistic entry into force is Q1–Q2 2027.
As CleverChain details, while the RTS harmonises what information must be collected and from which sources, it does not prescribe how the qualitative assessment under Art. 12(1)(d) is to be performed. There is no standardised methodology, scoring framework, or supervisory guidance specifying how obliged entities should detect opacity, test for rationale, or document the determination. This creates a first-mover advantage for institutions that establish a structured, documented, and defensible methodology now. Those that wait for supervisory guidance will be retrofitting under time pressure.
What a compliant Art. 12(1)(d) assessment must deliver
Best practice calls for a two-stage assessment. The first stage involves detecting opacity through a converging framework of indicator categories developed by international standard-setters including the Financial Action Task Force (FATF), the Wolfsberg Group, and the Joint Money Laundering Steering Group (JMLSG). These categories encompass financial anomalies (such as revenue disproportionate to employee count), operational substance gaps (virtual offices, mass-registration addresses), director and UBO behavioural patterns (mass directorships, rapid entity churn), offshore leak exposure, and activity code mismatches.
The second stage involves testing for legitimate rationale. Art. 12(1)(d) requires a positive finding that no legitimate economic rationale exists — meaning the obliged entity must actively consider whether recognised justifications apply, such as regulatory ring-fencing, asset protection, joint venture structuring, intellectual property holding, or political and security risk mitigation for beneficial owners in hostile jurisdictions.
Both stages must be documented as a structured, auditable record. A binary outcome without the supporting reasoning is not defensible under supervisory examination.
The back-book problem
The operational challenge extends well beyond new customer onboarding. Article 33 of the draft RTS provides a five-year risk-based transition period for the remediation of existing customers against the new CDD standard, with high-risk customers prioritised first.
For an institution with 50,000 corporate customers, even a conservative estimate that 15% have ownership structures exceeding three layers yields 7,500 Art. 12 assessments within the transition window. At an average of four to six hours per manual assessment, the effort required runs to between 30,000 and 45,000 analyst hours — the equivalent of roughly 15 to 22 full-time analysts deployed exclusively on Art. 12 remediation for a full year. Most compliance functions do not have that capacity available alongside their existing business-as-usual obligations.
How CleverChain’s VERA addresses the judgment problem
The structured, evidence-based qualitative assessment that Art. 12(1)(d) demands is the specific problem that agentic due diligence is designed to solve. CleverChain’s VERA is an autonomous AI due diligence agent that performs end-to-end CDD and Enhanced Due Diligence (EDD) on legal and natural persons, producing investigator-grade output within minutes per entity. The Art. 12 assessment is embedded in the standard product, not added as a separate module.
VERA automatically traverses the full ownership chain from the target entity to ultimate beneficial owners, counting layers and assessing each against the Art. 12(1) conditions. It identifies intermediate layers, flags extra-EU jurisdictions, detects legal arrangements such as trusts and foundations, and identifies nominee structures.
For condition (d), VERA runs a five-layer opacity analysis: operational substance verification, nature-of-business consistency testing, director and UBO pattern analysis, financial anomaly detection drawing on filed accounts, and cross-referencing against International Consortium of Investigative Journalists (ICIJ) Offshore Leaks databases including the Panama Papers, Paradise Papers, and Pandora Papers.
These layers collectively enable VERA to present evidence on both sides of the Art. 12(1)(d) assessment — opacity indicators found and potential legitimate explanations available from the documentary record — with the obliged entity making and documenting the final determination.
Every investigative step is explained, logged, and timestamped. Reports include a detailed entity resolution methodology and a complete evidence appendix with source URLs and retrieval dates. For Art. 33 back-book remediation, VERA’s speed means assessments can be processed in days rather than years, each documented to audit standard.
CleverChain’s capabilities in this area were recognised at the 2026 Financial Crime and Compliance 50 (FCC50) Awards, where the company received the Shell Company Detection award from Chartis Research.
Article 12(1)(d) is a category change in what CDD programmes must deliver. The international standard-setting framework has been building towards this expectation for years; the AMLA RTS codifies it. Verification, screening, and threshold-based UBO identification — the three pillars on which most CDD programmes rest — are structurally incapable of producing the qualitative assessment the provision demands.
The harmonisation gap, the back-book remediation obligation, and the realistic Q1–Q2 2027 implementation timeline cEU’s AMLA RTS demands a new qualitative approach to corporate due diligence. Discover how CleverChain’s VERA meets the standard. Read now. reate a clear imperative for obliged entities to act now. CleverChain’s VERA embeds the investigative, evidence-based assessment that Art. 12(1)(d) requires within the standard due diligence product, delivering the defensible, evidence-traced qualitative determination that supervisors will expect — not a score.
Read the full whitepaper by CleverChain here.
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