Anti-money laundering

The beneficial owner does not stop at the border.

Who really controls a company, which group it belongs to, whether it appears on a list, how much risk it carries: these are the questions that anti-money laundering regulation asks you to put to yourself, even when the chain passes through three countries. We put the answers in writing. The platform gathers the data; artificial intelligence reads and explains the risk, and in customer due diligence also tries to anticipate it. Where a person's judgement is needed, there is an analyst.

Request a demo The beneficial owner from 2027

The customer due diligence cycle

Ten steps, from opening the relationship to record keeping.

It is the sequence in which a position is investigated under D.Lgs. 231/2007 and the Bank of Italy Provisions. For each step, the article that requires it and the page where we explain how it applies and where our products carry it out and document it.

01
Identification
Of the customer, the person acting on its behalf and the beneficial owner, with documents and reliable, independent sources.
Arts. 18, 19 · from 2027 AMLA RTS
02
Screening
Sanctions lists without filters, politically exposed persons, adverse media, across the whole world.
Art. 24 · art. 1 para. 2 letter dd
03
Beneficial owner
Ownership, control, residual today; in parallel and with the multiplier from 10 July 2027.
Art. 20 · AMLR arts. 51-54, 63
04
Purpose and nature of the relationship
Gathered in the interview, consistent with the customer's activity and size.
Art. 17 para. 1 letter c
05
Risk profile
High, medium or low, from the factors in article 17 and the annexes, with the reasoning in writing.
Art. 17 para. 3 · annexes 1 and 2
06
Enhanced or simplified verification
The form follows the level: origin of funds and of wealth where the risk is high, reduced and documented measures where it is low.
Arts. 23, 24
07
Approval
At the level of authorisation that the profile requires; for a politically exposed person, the director general or a delegate.
Art. 24 para. 5 · art. 42
08
Ongoing monitoring
For the whole duration of the relationship: changes on the subject every day, review at the frequency set by the risk.
Art. 17 para. 1 letter d · art. 19 para. 1 letter c
09
Reporting
To the UIF, without delay, with the reasoned suspicion and the file that supports it; nothing is said to the customer.
Arts. 35, 39
10
Record keeping
Ten years, so that customer, beneficial owner, transaction and checks made can be reconstructed.
Art. 31

01Titolarità effettiva worldwide

From the company to the natural person, in any country.

We reconstruct the ownership chain of a company, Italian or foreign, down to the natural persons who own or control it, using the criteria of article 20 of D.Lgs. 231/2007. Alongside the result the analysts write the path followed and the choices made along the chain, and artificial intelligence helps them summarise what the reconstructed chain says.

Three levels of depth: basic, extended and top.
The document is updated at the time of the request.
It is delivered on the platform, via API or by email, in other languages of the Union as well.

02Know Your Customer worldwide

When the relationship is opened, the risk is measured first, and artificial intelligence explains it.

We gather the information needed, from official sources and from those you provide, and calculate the indicators and the money laundering risk on three levels: high, medium, low. The rules set the level; on the platform artificial intelligence reads the whole picture, writes why and can only raise it, never lower it. For each outcome we propose how to mitigate it, from enhanced customer due diligence to a review further out in time. The weights of the calculation are agreed with you.

Protesti, pregiudizievoli and insolvency proceedings.
Sanctions lists, politically exposed persons and adverse media.
Age of the company, dissolution, liquidation or striking off.
Trusts and trust companies (fiduciarie) in the shareholding structure, foreign companies and beneficial owners.
Sectors at risk, shell company indicators, signing powers, which AI reads even where the Register records them in free text.
Coming soon: adverse media also from what the web writes about the company and its directors, read by AI.

Where artificial intelligence works →

03Groups worldwide

From any company in the group, up to the parent company and all the branches.

We start from any company in the group, go up to the parent company and reconstruct its branches, in any country. For an Italian company the codice fiscale is enough; for a foreign one, company name, address and country. The tree arrives as XLSX, CSV or JSON, or inside the beneficial ownership document.

04Customer due diligence

Ordinary, simplified and enhanced, in a single workflow.

ComplifyADV manages customer due diligence from opening the case through to monitoring: it gathers the information, calculates the risk, takes the case to approval and reopens it when something changes. Artificial intelligence analyses the cases, recognises the patterns of positions at high risk and flags them in advance.

How ComplifyADV is built →

The dates that matter

What applies today, and what applies from 2027.

2007
D.Lgs. 231/2007
The decree that transposes the European directives and, with its amendments, governs the whole Italian system: obliged entities, customer due diligence, beneficial owner, reporting, record keeping, sanctions.
2024
The European package
Regulation (EU) 2024/1624 on obligations, Directive (EU) 2024/1640 on authorities and registers, Regulation (EU) 2024/1620 establishing AMLA. On 30 September 2026 AMLA sent the Commission the technical standards on customer due diligence.
2027
10 July: the AMLR applies
The obligations become a regulation, the same across the Union. For the beneficial owner the criteria change: in parallel, a threshold of 25% or more, the multiplier method, the end of the residual criterion.
2028
AMLA's direct supervision
The European Authority directly supervises a small group of high-risk credit and financial institutions operating in several States; the first selection begins by 1 July 2027.

The full picture, with the sanctions, is on the page on regulation.

The words, in their place

KYC, CDD, AML, STR: four terms that are not synonyms.

They are used for one another, and in a review the confusion is costly. Below, what each one means and how they fit together.

AMLAnti-Money Laundering · AML: The objective and the framework: the set of obligations the law imposes to prevent the financial system from being used to launder illicit money. In Italy, D.Lgs. 231/2007; from 2027, Regulation (EU) 2024/1624.
CDDCustomer Due Diligence · CDD: The measure: identifying and verifying the customer, the person acting on its behalf and the beneficial owner, understanding the purpose and nature of the relationship, monitoring it over time (article 17). It is simplified where the risk is low and enhanced where it is high.
KYCKnow Your Customer · knowing the customer: The result: documented knowledge of the customer, who they are, who controls them, what they do and how much risk they carry, which customer due diligence produces and ongoing monitoring keeps up to date. This is what our KYC service delivers when the relationship is opened.
STRSuspicious transaction report: The outcome: the report to the UIF, without delay, of a transaction whose origin is suspected to be illicit (article 35). Elsewhere it is called an STR or SAR; the substance is the reasoned, documented suspicion.

Artificial intelligence

Where artificial intelligence works, and under what rules.

In anti-money laundering, artificial intelligence promises fewer false positives, faster profiles and patterns that the naked eye does not see. It also brings known problems: choices that are hard to explain, data of uncertain quality, models to be checked over time. We use it at three points, and for each there is a written rule.

Writes why the risk is what it is

The rules set the level and remain declared; artificial intelligence reads the whole file and writes the reasoning. It can make the assessment more severe, never more lenient.

Reads what is written in free text

The signing powers that the Register records in full text, and the summary of the chain of control reconstructed by the analysts: artificial intelligence helps to summarise the chain.

Recognises the patterns of high risk

In ComplifyADV it analyses the cases, recognises what positions at high risk have in common and flags in advance those heading the same way. It flags and prepares; the assessment and the decision remain with the bank.

The level comes from written rules and the reasoning is written in your organisation's language: it is what you take to a review. Coming soon: artificial intelligence reading of what the web says about the company and its directors.

Complify Yourself!

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