{
  "id": "AIBD-0183",
  "title": "Nearly a third of French tax controls now come from mass-data risk analysis, with efficacy hard to measure",
  "summary": "The Cour des comptes (November 2023) found that nearly a third of DGFiP tax controls rest on mass-data risk analyzes (target 50% by 2027); a July 2026 parliamentary exchange put data mining at 44% ...",
  "date_observed": "2023-11-15",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "The Cour des comptes published its report “La détection de la fraude fiscale des particuliers” on 15 November 2023. It says nearly a third of tax controls now rest on risk analyses fed by mass data processing. The administration aims at 50% by 2027. Their efficacy remains difficult to measure. Mass data cross-matching may assist controls but can never automatically characterize fraud. The “foncier innovant” scheme illustrates the growing use of artificial intelligence. It gives 14.6 billion euro of droits et pénalités from controls in 2022, slightly more than a third on individuals. It attributes no share to data mining. It gives a 55% recovery rate that has barely improved since 2018. La Revue du Digital (22 July 2026) reported a divergence at the parliamentary finance commission on 21 July. LFI rapporteur Mathilde Feld said that data-mining controls were 44% of Direction générale des Finances publiques (DGFiP) controls in 2023. She said they produced less than 14% of droits et pénalités, less than a seventh of the total. DGFiP Director General Amélie Verdier defended data mining as an efficient and far less staff-intensive way to detect declarative inconsistencies.",
  "category": "general benefit",
  "unexpected": false,
  "purpose": "Target tax audits by cross-matching mass data to detect declarative inconsistencies.",
  "system": "DGFiP data-mining targeting of tax controls (program name not given in the sources)",
  "model_version": null,
  "developer": "Direction générale des Finances publiques (DGFiP)",
  "deployer": "Direction générale des Finances publiques (DGFiP)",
  "location": null,
  "domain": "Tax compliance",
  "segment": "Audit targeting and fraud detection",
  "benefit_type": "Improved Organizational Efficiency",
  "taxonomy_note": "The benefit is a share of control programming, and the Cour judged efficacy hard to measure.",
  "registry_ids": {},
  "ratings": [
    {
      "group": "organizational",
      "depth": null,
      "reason": "Sources give the share of controls programmed by data mining and a contested yield share, not an outcome attributable to the system."
    },
    {
      "group": "societal",
      "depth": null,
      "reason": "No recovered amount is attributed to data mining by the Cour. The 2026 figure is a yield share stated in debate."
    }
  ],
  "ai_role": {
    "status": "unassessed",
    "statement": "The Cour describes risk analyses fed by mass data processing. It reserves the term artificial intelligence for the separate foncier innovant scheme. Whether the targeting uses machine learning is thus not established. DGFiP builds and runs the targeting itself. The Cour des comptes, an independent audit court, wrote the report."
  },
  "evidence": [
    {
      "kind": "report",
      "citation": "Cour des comptes, 'La détection de la fraude fiscale des particuliers', 15 November 2023",
      "title": "La détection de la fraude fiscale des particuliers",
      "url": "https://www.ccomptes.fr/fr/publications/la-detection-de-la-fraude-fiscale-des-particuliers",
      "date": "2023-11-15",
      "written_by": "independent",
      "quote": "Près du tiers des contrôles fiscaux repose désormais sur des analyses de risque nourries par le traitement de données en masse"
    },
    {
      "kind": "news report",
      "citation": "La Revue du Digital, 22 July 2026",
      "title": "LFI- Finances Publiques : divergences sur l'efficacité du Data Mining dans le contrôle fiscal",
      "url": "https://www.larevuedudigital.com/divergences-sur-lusage-du-data-mining-dans-le-controle-fiscal/",
      "date": "2026-07-22",
      "written_by": "independent",
      "quote": "une manière efficace, beaucoup moins coûteuse en moyens humains"
    }
  ],
  "replication": {
    "produced_by": [
      "Mass cross-matching of declarative and third-party data to program a growing share of controls"
    ],
    "must_hold": [
      "The legal limit that cross-matching assists but never automatically characterizes fraud",
      "Audit staff capacity to convert targeting into droits et pénalités, which the 2026 debate questioned"
    ],
    "echoes": [
      {
        "date": null,
        "setting": "DGFiP activity for 2023 as cited at the finance commission (2023)",
        "model_version": null,
        "outcome": "recurred",
        "source": "La Revue du Digital: 44% of controls from data mining, under 14% of droits et pénalités"
      }
    ]
  },
  "paired_incident": null,
  "headline": "Nearly a third of DGFiP tax controls rest on mass-data analysis",
  "metric": "nearly a third of DGFiP tax controls rest on mass-data risk analyzes (target 50% by 2027)",
  "comparator": {
    "against": "tax controls initiated by DGFiP agents' own analysis",
    "before": "le rendement moyen à l’initiative des agents était près de cinq fois supérieur",
    "after": "celui des contrôles résultant du data mining",
    "basis": "measured",
    "quote": "En 2023, le rendement moyen à l’initiative des agents était près de cinq fois supérieur à celui des contrôles résultant du data mining",
    "url": "https://www.larevuedudigital.com/divergences-sur-lusage-du-data-mining-dans-le-controle-fiscal/"
  },
  "later": {
    "status": "scaled",
    "date": "2026-07-22",
    "note": "Citing the Cour des comptes, deputy Mathilde Feld told the finance committee on 21 July 2026 that data-mining-derived controls were 44% of DGFiP controls in 2023, up from nearly a third, while yielding under 14% of the sums recovered.",
    "quote": "Les contrôles issus du croisement des données représentaient 44% des contrôles réalisés par la DGFIP en 2023 pour moins de 14% des droits et pénalités mises en recouvrement, moins d’un septième du total",
    "url": "https://www.larevuedudigital.com/divergences-sur-lusage-du-data-mining-dans-le-controle-fiscal/"
  },
  "value": null,
  "developer_country": "France",
  "deployer_country": "France",
  "unrated_because": null,
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    {
      "date": "2026-10-20",
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      "date": "2026-10-21",
      "change": "Added what the benefit is measured against, what happened since from the cited sources.",
      "source": "https://www.larevuedudigital.com/divergences-sur-lusage-du-data-mining-dans-le-controle-fiscal/; https://www.larevuedudigital.com/divergences-sur-lusage-du-data-mining-dans-le-controle-fiscal/",
      "editor": "AIBD"
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      "source": "https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7; https://lannuaire.service-public.gouv.fr/gouvernement/80515340-0ad9-4293-9348-35d7eb005fc7",
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  "confidence": "studied",
  "shade": "high",
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              "url": "https://www.larevuedudigital.com/divergences-sur-lusage-du-data-mining-dans-le-controle-fiscal/"
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}