{
  "id": "AIBD-0173",
  "title": "Treasury's machine-learning check-fraud detection recovers $1 billion in FY2024",
  "summary": "Treasury reported over $4 billion in fraud and improper payments prevented or recovered in FY2024, including $1 billion recovered through machine-learning check-fraud detection.",
  "date_observed": "2024-10-17",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "On 17 October 2024 the U.S. Department of the Treasury reported on fraud detection at the Bureau of the Fiscal Service's Office of Payment Integrity. The enhanced processes, including machine-learning AI, prevented and recovered over $4 billion in fraud and improper payments in FY2024 (October 2023 to September 2024). The FY2023 comparison figure was $652.7 million. Of the total, $1 billion was recovered through machine-learning identification of Treasury check fraud. $2.5 billion came from identifying and prioritizing high-risk transactions, $500 million from expanded risk-based screening and $180 million from payment-processing efficiencies. Nextgov reported that the office uses machine learning to examine large amounts of data and flag potential fraud schemes. NBC News reported that a Treasury official declined to give specific deployment examples for security reasons. No independent audit of the figures and no vendor or technique appears in the sources.",
  "category": "general benefit",
  "unexpected": false,
  "purpose": "Detect and prevent fraud and improper payments in federal disbursements, including Treasury check fraud.",
  "system": "Office of Payment Integrity enhanced fraud-detection processes including machine-learning AI (Bureau of the Fiscal Service)",
  "model_version": null,
  "developer": "U.S. Department of the Treasury, Bureau of the Fiscal Service, Office of Payment Integrity (no vendor is named in the sources)",
  "deployer": "U.S. Department of the Treasury, Bureau of the Fiscal Service",
  "location": null,
  "domain": "Public finance and payment integrity",
  "segment": "Federal government payments and check fraud",
  "benefit_type": "Reduced Risk",
  "taxonomy_note": null,
  "registry_ids": {},
  "ratings": [
    {
      "group": "societal",
      "depth": null,
      "reason": "The sources give only aggregate FY2024 totals for taxpayers' money recovered or prevented. No outcome is documented for an identifiable group."
    },
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      "group": "organizational",
      "depth": null,
      "reason": "Treasury reports aggregate prevention and recovery figures for the Office of Payment Integrity. No single deployment outcome is described."
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    "status": "assessed",
    "statement": "Treasury's release attributes $1 billion of FY2024 recoveries to machine-learning AI that expedited identification of Treasury check fraud. It credits $2.5 billion to prioritizing high-risk transactions. The technique is not described and no vendor is named. So developer and deployer appear to be the same public body (the Bureau of the Fiscal Service's Office of Payment Integrity). This is not stated. The figures are not independently verified in the sources."
  },
  "evidence": [
    {
      "kind": "press release",
      "citation": "U.S. Department of the Treasury, press release, 17 October 2024",
      "title": "Treasury Announces Enhanced Fraud Detection Processes, Including Machine Learning AI, Prevented and Recovered Over $4 Billion in Fiscal Year 2024",
      "url": "https://home.treasury.gov/news/press-releases/jy2650",
      "date": "2024-10-17",
      "written_by": "makers",
      "quote": "Treasury takes seriously our responsibility to serve as effective stewards of taxpayer money."
    },
    {
      "kind": "news report",
      "citation": "Natalie Alms, Nextgov/FCW, 18 October 2024",
      "title": "AI tools helped Treasury recover billions in fraud and improper payments",
      "url": "https://www.nextgov.com/artificial-intelligence/2024/10/ai-tools-helped-treasury-recover-billions-fraud-and-improper-payments/400368/",
      "date": "2024-10-18",
      "written_by": "independent",
      "quote": "We've made significant progress during the past year."
    },
    {
      "kind": "news report",
      "citation": "Rob Wile, NBC News, 17 October 2024",
      "title": "Treasury Department now using AI to save taxpayers billions of dollars",
      "url": "https://www.nbcnews.com/business/consumer/how-ai-artificial-intelligence-fights-taxpayer-fraud-treasury-dept-rcna175916",
      "date": "2024-10-17",
      "written_by": "independent",
      "quote": "Treasury Department now using AI to save taxpayers billions of dollars"
    },
    {
      "kind": "press release",
      "citation": "Bureau of the Fiscal Service (2026). Treasury's Bureau of the Fiscal Service Recognized for Payment Integrity Efforts. Fiscal Service news, 18 September 2026.",
      "title": "Treasury’s Bureau of the Fiscal Service Recognized for Payment Integrity Efforts",
      "url": "https://fiscal.treasury.gov/about-us/news/treasurys-bureau-fiscal-service-recognized-for-payment-integrity-efforts",
      "date": "2026-09-18",
      "written_by": "makers",
      "quote": null
    }
  ],
  "replication": {
    "produced_by": [
      "Centralised disbursement data at the Bureau of the Fiscal Service (Nextgov: over 1.4 billion payments and more than $6.9 trillion a year)",
      "Machine learning applied to large payment datasets to flag potential fraud schemes, combined with risk-based screening and prioritization of high-risk transactions"
    ],
    "must_hold": [
      "Access to payment and check data at scale",
      "Operational capacity to stop or claw back flagged payments and an office that measures the results",
      "Independent verification of the claimed figures, which the sources do not provide"
    ],
    "echoes": [
      {
        "date": "2023-09-30",
        "setting": "Treasury Office of Payment Integrity, FY2023",
        "model_version": null,
        "outcome": "recurred",
        "source": "Treasury press release gives $652.7 million as the FY2023 comparison figure; the machine-learning attribution for that year is not stated"
      }
    ]
  },
  "paired_incident": null,
  "headline": "Treasury's machine learning recovers $1 billion in FY2024",
  "metric": "$1 billion recovered through machine-learning check-fraud detection",
  "comparator": {
    "against": "Treasury's fraud and improper-payment prevention and recovery in FY2023, before the enhanced processes",
    "before": "$652.7 million in FY23",
    "after": "over $4 billion in fraud and improper payments this fiscal year (FY) (October 2023 – September 2024)",
    "basis": "measured",
    "quote": "Today, the U.S. Department of the Treasury announced that its latest efforts in taking a technology and data-driven approach to fraud and improper payment prevention enabled the prevention and recovery of over $4 billion in fraud and improper payments this fiscal year (FY) (October 2023 – September 2024), up from $652.7 million in FY23.",
    "url": "https://home.treasury.gov/news/press-releases/jy2650"
  },
  "later": {
    "status": "scaled",
    "date": "2026-09-18",
    "note": "The Fiscal Service reported that Treasury's payment integrity efforts prevented, detected or recovered more than $11.7 billion in FY2025, nearly three times the FY2024 total.",
    "quote": "In fiscal year 2025, Treasury’s payment integrity efforts helped prevent, detect, and recover more than $11.7 billion in improper payments.",
    "url": "https://fiscal.treasury.gov/about-us/news/treasurys-bureau-fiscal-service-recognized-for-payment-integrity-efforts"
  },
  "value": {
    "amount": "$1 billion",
    "what": "Treasury check fraud recovered in FY2024 through machine-learning identification",
    "who": "U.S. Treasury, on behalf of taxpayers",
    "estimate": false,
    "quote": "Expediting the identification of Treasury check fraud with machine learning AI resulting in $1 billion in recovery.",
    "url": "https://home.treasury.gov/news/press-releases/jy2650"
  },
  "developer_country": "United States",
  "deployer_country": "United States",
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      "date": "2026-10-21",
      "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
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      "change": "Added what the benefit is measured against, what happened since, the value as stated from the cited sources.",
      "source": "https://home.treasury.gov/news/press-releases/jy2650; https://fiscal.treasury.gov/about-us/news/treasurys-bureau-fiscal-service-recognized-for-payment-integrity-efforts; https://home.treasury.gov/news/press-releases/jy2650",
      "editor": "AIBD"
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      "change": "Country of the developer and the deployer added from the organization's own site or a registry.",
      "source": "https://en.wikipedia.org/wiki/United_States_Department_of_the_Treasury; https://en.wikipedia.org/wiki/United_States_Department_of_the_Treasury",
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  "confidence": "reported",
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