A Dutch court stopped a secret system that scored poor neighbourhoods for fraud

The instrument that scored a neighbourhood

In Rotterdam's Afrikaander neighbourhood, a low-income district by the docks, the Dutch state ran a project against address fraud. Software drew records on the people who lived there, matched them against a risk model, and returned a list of residents deemed worth investigating for fraud. They were not told. The tool was called SyRI.

SyRI, short for Systeem Risico Indicatie, or System Risk Indication, was a legal instrument the government used to fight fraud in social security, income-dependent schemes, taxes, and labour law. It linked and analysed data in a secured environment so that "risk reports" could be generated.¹ A risk report meant that a person "is deemed worthy of investigating with regard to possible fraud."¹ The Minister of Social Affairs and Employment ran SyRI at the request of an alliance of designated bodies. They were the municipal authorities, the Employee Insurance Agency, the Social Insurance Bank, the Tax and Customs Administration, the Immigration and Naturalisation Service, and the Social Affairs and Employment Inspectorate.¹ Its legal basis was Section 65 of the SUWI Act and Chapter 5a of the SUWI Decree, in force from 1 January 2014.¹

The reach was wide by design. A deployment request had to name "which indicators and which risk model the request concerns," and could draw on seventeen categories of personal data, from tax and housing to education, pensions, and debts.² The court later said it was "hard to imagine any type of personal data that is not eligible."¹ Five projects ran from 2015 on, all in areas the state itself called problem districts: Rotterdam's Bloemhof and Hillesluis and the Afrikaander neighbourhood, Capelle aan den IJssel, and Haarlem's Schalkwijk.¹

A model kept from the people it scored

The heart of SyRI was hidden. The State never disclosed the risk model or the indicators it was built from, not to the public, not to the people whose data it processed, and not to the court.¹ A person had no right to be told that their data had been run through SyRI or that a risk report had been filed on them.¹

What the State would say about the method was limited. It told the court the model compared files against risk indicators and data links with a predetermined cut-off, and that a case below the threshold never became a hit.¹ It described the comparison as done "with the aid of a simple decision tree." The court accepted as a factual assumption that no deep learning or data mining was in use, though the legislation left room for both.¹ This was not, on the record, an artificial-intelligence model. It was a rule-based risk score whose rules were secret. Two scholars who reviewed the case, Marvin van Bekkum and Frederik Zuiderveen Borgesius, found three parts of SyRI kept strictly secret: the risk model, the algorithm that ran the comparison, and the ministry's method for connecting hits. What technology it actually used, they conclude, "is unknown."³

Struck down for what could not be verified

On 5 February 2020 The Hague District Court ruled that the SyRI legislation had no binding effect, because it was contrary to Article 8 of the European Convention on Human Rights, which protects private life.¹ The case was brought by a coalition of civil-society groups, led by the NJCM, the Dutch section of the International Commission of Jurists, and coordinated by the Public Interest Litigation Project. It was heard on 29 October 2019.⁴ Philip Alston, the UN Special Rapporteur on extreme poverty and human rights, filed an amicus brief in September 2019 for the claimants.⁵

Article 8 lets the state interfere with private life only where the interference is "in accordance with the law" and "necessary in a democratic society." The court read that as necessary, proportionate, and subsidiary, striking a fair balance between the aim and the intrusion.¹ It accepted that fighting fraud was a legitimate aim answering a pressing social need.¹ It struck the legislation down anyway: SyRI was insufficiently transparent and verifiable.

On discrimination the court was careful. It found "there is in fact a risk that SyRI inadvertently creates links based on bias, such as a lower socio-economic status or an immigration background." SyRI had so far been applied only to problem districts, as the State confirmed at the hearing.¹ It did not find that SyRI had actually discriminated against anyone, and it declined to order the State to disclose the models.¹ Only Section 65 and Chapter 5a fell; the general power to exchange data under Section 64 survived.¹ Alston called the outcome a landmark that set a strong legal precedent, and one of the first times a court anywhere had stopped a welfare authority from using digital technologies and pooled personal data on human-rights grounds.⁶ The State did not appeal. On 23 April 2020 it let the judgment stand, and SyRI was not used again.⁴

Why a secret score can't be proven wrong

Screening a whole population for a rare behaviour has a built-in problem. When the target is uncommon, the innocent so outnumber the guilty that even a fairly accurate test flags mostly innocent people. A screen like SyRI therefore stands or falls on its false-positive rate.

There is a second problem, and the court named it. When the data fed in and the neighbourhoods chosen both track poverty, the score tracks poverty too. Through poverty it can track traits the state may not target, such as an immigration background. That is the "risk" the court identified, and it followed from running SyRI only in poor districts.¹ The UN report Alston drew on names the danger: the way such systems reach a score is "often secret, thus making it difficult to hold Governments and private actors to account for potential rights violations."⁷

Both problems lead to where SyRI failed. To tell whether a screen catches fraud or the poor, someone has to open it and see the indicators, the weights, and how often the flags are wrong. With SyRI no one could. A flagged resident could not see the model, so could not show a flag was mistaken. The court could not see it either.¹ SyRI has no known false-positive rate, and by the design of the scheme it never will, because the model was never disclosed and its accuracy could never be tested.¹

What would have settled it was disclosure of the model, its indicators, and its error rate. It never came, and the court declined to compel it.¹ Van Bekkum and Zuiderveen Borgesius report SyRI "was never very successful in uncovering fraud," but even that is secondhand: the state kept its results secret too.³

The successor the Senate passed anyway

The Dutch government did not give up cross-agency data-linking. It wrote a broader law. The Wet gegevensverwerking door samenwerkingsverbanden, which critics call "Super SyRI," lets designated alliances share and jointly process personal data for enforcement across many domains, not only social security. The Senate adopted it on 18 June 2024.⁸ The Dutch data-protection authority had advised against it, and a civil-rights coalition of former SyRI claimants called it "a blueprint for more benefits scandals."⁹

That warning points at the other Dutch case SyRI is often mistaken for. The childcare-benefits scandal was a different system: the Tax and Customs Administration's dragnet for childcare-benefit fraud, which wrongly accused tens of thousands of families and brought down a cabinet, settled by a parliamentary inquiry rather than a court. SyRI is the cross-agency instrument a court struck down, with no finding that it wrongly flagged a single person. The two fail in different ways.

SyRI was never shown to be artificial intelligence. The State called it a simple decision tree, and the court accepted that no deep learning ran inside it.¹ What it shares with the AI systems now spreading through government is the shape of the failure, not the technology: an automated score built from pooled data, aimed at a group, closed to those it judges. AI only scores more people from more data and reveals less of how. The court in The Hague answered the question those systems raise before they scaled: a risk model aimed at the poor has to be transparent and verifiable enough to check, or it cannot stand.