Tax dredger on social networks: new learning algorithms to track fraud

Drague fiscale sur les réseaux sociaux: de nouveaux algorithmes d’apprentissage pour traquer la fraude

Dominique Desbois ()

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Abstract: In France, estimates of tax evasion vary between 2 and 80 billion euros (€ bn) according to the parliamentary report of Bénédicte Peyrol. This would explain the injunction addressed by President Emmanuel Macron to the Court of Auditors on April 25 to shed light on this controversial issue in a context of tensions over public finances and a decline in tax compliance. In a letter sent on May 9 to Didier Migaud, president of this institution, Prime Minister Édouard Philippe indicates that "the time has come to take stock of the scale of tax fraud in the country and to assess the action state services and the tools that are put in place. " A recent interview with Gérald Darmanin, Minister of Action and Public Accounts, has just revealed the French government's plan to use machine learning algorithms to better target tax audits based on the information that taxpayers disclose to them. - even on social networks. Illegal trade and false tax domiciliations are particularly targeted by article 57 of the 2020 finance bill, which provides for the use of artificial intelligence in the service of the fight against tax fraud, adopted on November 13 by MEPs 3. Thus, this project plans to strengthen the IT resources to improve the targeting of tax audit operations thanks to an investment of 20 million euros by 2022. Artificial intelligence, often invoked to discuss technologies Numeric, is a misleading term, because it evokes the capacities of machines fantasized by the works of science fiction popularized by the seventh art. In tax matters, nothing like this: among the myriad of behaviors observed, the use of machine learning techniques aims to detect recurrent ones that are specific to certain types of fraud (VAT, bleaching, false domiciliation and illicit optimization). However, the tax administration concedes a weak point: "Today, nearly one audit in four results in only a small recovery. "

Date: 2019-12-12
New Economics Papers: this item is included in nep-acc, nep-big and nep-iue
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Published in 2019

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