{
  "id": "AIBD-0317",
  "title": "Vyntra's (formerly NetGuardians) AI risk models may have blocked fraudulent payments at unnamed banks, including a USD 500,000 ATM scheme",
  "summary": "Vendor “Fraud Cases” page lists blocked payments from CHF 19,990 to USD 850,000 and a USD 500,000 (KSh 58 million) ATM fraud ending in arrests; customers, banks and dates are not given.",
  "date_observed": "2022-04-04",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "Vyntra's “Fraud Cases” page was published 4 April 2022 per its page metadata; the cases themselves are undated. It states that “Our solutions stop the fraud before the money leaves the bank” and lists about two dozen short case studies at unnamed banks. One is an account takeover after pharming stopped before a CHF 19,990 payment. Another is an impersonation that led a bank employee to validate a CHF 1,000,000 transaction, blocked because the beneficiary was unusual at bank level. There are vishing, tech-support, CEO-fraud, business-email-compromise, romance and invoice-redirection cases. Their payments of EUR 22,114, EUR 33,170, USD 7,500, GBP 21,000, EUR 125,000, EUR 170,000, USD 100,000, USD 170,000 and USD 850,000 were stopped. Transaction or e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language) did not match the customer's or bank's usual profile. There are two internal-fraud cases. In one case “fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank's ATMs”. The models had flagged unusual timing and frequency of withdrawals. One entry still names “NetGuardians solution”, the Swiss company that merged with Belgium's Intix to form Vyntra in June 2025 (FinTech Global, 19 June 2025). No customer, bank, country, date, regulator or court record is given for any case, and none was found. The page is the vendor's own account.",
  "category": "harm prevented",
  "unexpected": false,
  "purpose": "The risk models are built to score payments and e-banking sessions against customer and bank profiles in real time and block fraudulent transfers. Each case is that intended use.",
  "system": "Vyntra (NetGuardians) AI risk models for real-time payment and e-banking fraud detection",
  "model_version": null,
  "developer": "Vyntra (NetGuardians SA, merged with Intix in June 2025)",
  "deployer": "Unnamed client banks",
  "location": "Not stated; amounts are given in Swiss francs, euros, pounds, US dollars and Kenyan shillings",
  "domain": "Banking fraud prevention",
  "segment": "Retail and corporate payment fraud at client banks",
  "benefit_type": "Reduced Risk",
  "taxonomy_note": "The blocked payments and the ATM fraud are described only on the vendor's page, with no named bank, customer or date.",
  "registry_ids": {},
  "ratings": [
    {
      "group": "personal",
      "depth": 3,
      "reason": "The vendor describes customers whose social-engineering transfers of EUR 125,000 and USD 170,000 were blocked, a loss averted for each. No customer is named or independently documented."
    },
    {
      "group": "organizational",
      "depth": 4,
      "reason": "The vendor states that a USD 500,000 (KSh 58 million) ATM fraud was stopped with arrests. It says payments up to USD 850,000 were blocked before funds left client banks. Serious losses averted if the account holds. Customers, banks and dates are not given."
    },
    {
      "group": "societal",
      "depth": null,
      "reason": "No aggregate verified by a regulator is given."
    }
  ],
  "ai_role": {
    "status": "unassessed",
    "statement": "The evidence is limited to the maker's account. Vyntra's page attributes each block to its AI risk models detecting variables outside the customer's or bank's usual profile. No customer, bank, date or official record is available to assess whether the models, rather than staff or other controls, produced the outcome. The AI's contribution is not established."
  },
  "evidence": [
    {
      "kind": "press release",
      "citation": "Vyntra (2022). Fraud Cases. vyntra.com (vendor case-study page; page metadata gives 4 April 2022; cases undated).",
      "title": "Fraud Cases - Vyntra",
      "url": "https://www.vyntra.com/fraud-cases/",
      "date": "2022-04-04",
      "written_by": "makers",
      "quote": "Vyntra's AI risk models prevented the fraud due to the unusual timing and frequency of ATM withdrawals."
    },
    {
      "kind": "press release",
      "citation": "Vyntra (2022). Fraud Cases, same page, ATM case.",
      "title": "Fraud Cases - Vyntra",
      "url": "https://www.vyntra.com/fraud-cases/",
      "date": "2022-04-04",
      "written_by": "makers",
      "quote": "fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank's ATMs."
    },
    {
      "kind": "news report",
      "citation": "FinTech Global (2025). Vyntra launched by NetGuardians and Intix to boost banking intelligence. 19 June 2025.",
      "title": "Vyntra launched by NetGuardians and Intix to boost banking intelligence",
      "url": "https://fintech.global/2025/06/19/vyntra-launched-by-netguardians-and-intix-to-boost-banking-intelligence/",
      "date": "2025-06-19",
      "written_by": "independent",
      "quote": "NetGuardians brings its advanced artificial intelligence tools to detect and prevent financial crime, while Intix contributes its expertise in transaction data analysis and visibility."
    }
  ],
  "replication": {
    "produced_by": [
      "Behavioral profiles of each customer's and the bank's usual transaction and e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language)",
      "Real-time scoring before a payment is released"
    ],
    "must_hold": [
      "The fraudulent transaction departs from the profile on several variables; the vendor notes cases with little customer history relied on bank-level anomalies",
      "The bank acts on the alert before the money leaves"
    ],
    "echoes": []
  },
  "paired_incident": null,
  "headline": "Vyntra's AI risk models may have stopped a USD 500,000 ATM fraud",
  "metric": "fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million)",
  "comparator": null,
  "later": {
    "status": "unknown",
    "date": null,
    "note": "No dated follow-up to any of the cases was found; the June 2025 merger of NetGuardians and Intix into Vyntra concerns the vendor, not the cases.",
    "quote": null,
    "url": null
  },
  "value": {
    "amount": "USD 500,000 (KSh 58 million)",
    "what": "fraudulent ATM withdrawal detected and stopped, with arrests",
    "who": "the second bank, an unnamed client bank (the page labels the case 'Kenya')",
    "estimate": false,
    "quote": "The fraud was detected in real time and the fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank’s ATMs. Vyntra's AI risk models prevented the fraud due to the unusual timing and frequency of ATM withdrawals.",
    "url": "https://www.vyntra.com/fraud-cases/"
  },
  "developer_country": "Switzerland",
  "deployer_country": null,
  "unrated_because": null,
  "brief_notes": null,
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    {
      "date": "2026-10-20",
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      "editor": "AIBD"
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      "date": "2026-10-21",
      "change": "Depth rated 3 for personal and 4 for organizational on the documented outcome, with the reason stated on each rating.",
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      "editor": "AIBD"
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      "change": "Added the value as stated from the cited sources.",
      "source": "https://www.vyntra.com/fraud-cases/",
      "editor": "AIBD"
    },
    {
      "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/",
      "editor": "AIBD"
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      "date": "2026-10-21",
      "change": "Country of the developer added from the organization's own site or a registry.",
      "source": "https://www.vyntra.com/contact",
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  "confidence": "reported",
  "shade": "medium",
  "claim_status": "Independently reported",
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          "editor_note": ""
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      },
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        "review_state": "not_assessed",
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      "evaluations[].setting_sample": {
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      "evaluations[].uncertainty_limitations": {
        "state": "not_assessed",
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      "external_references[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
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        "review_state": "not_assessed",
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        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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          "kind": "record_fields",
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          "kind": "record_fields",
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        "review_state": "not_assessed",
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              },
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                "group": "organizational",
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              },
              {
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            ]
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        "coverage": "partial"
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        "value": {
          "kind": "record_fields",
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            "location": "Not stated; amounts are given in Swiss francs, euros, pounds, US dollars and Kenyan shillings",
            "developer_country": "Switzerland"
          }
        },
        "provenance": {
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              },
              {
                "date": "2026-10-21",
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              },
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              },
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              },
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        "review_state": "record_mapped",
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      "replication.attempts[]": {
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                "The fraudulent transaction departs from the profile on several variables; the vendor notes cases with little customer history relied on bank-level anomalies",
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              "echoes": []
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              }
            ]
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        },
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            "summary": "Vendor “Fraud Cases” page lists blocked payments from CHF 19,990 to USD 850,000 and a USD 500,000 (KSh 58 million) ATM fraud ending in arrests; customers, banks and dates are not given.",
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        "review_state": "record_mapped",
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      "systems[].autonomy_permissions": {
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      "systems[].component_role": {
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        "review_state": "not_assessed",
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        "state": "not_assessed",
        "review_state": "not_assessed",
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        "state": "not_assessed",
        "review_state": "not_assessed",
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      "systems[].model_name": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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      "systems[].model_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
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        "value": {
          "kind": "record_fields",
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        },
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].provider": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "application_developer": "Vyntra (NetGuardians SA, merged with Intix in June 2025)"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Mapped from the existing case description without a new external source review.",
          "record_fields": [
            "developer"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "taxonomy_crosswalks[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "title": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "title": "Vyntra's (formerly NetGuardians) AI risk models may have blocked fraudulent payments at unnamed banks, including a USD 500,000 ATM scheme",
            "headline": "Vyntra's AI risk models may have stopped a USD 500,000 ATM fraud"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "title",
            "headline"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "version": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "0242cb63702bd620f893f6be7eb51974757fa5552e2abf436018f8573cdcbf56"
          ],
          "role": "SHA-256 of normalized original case data"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Deterministic content version assigned by the local migration.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "workflow": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "Vyntra's “Fraud Cases” page was published 4 April 2022 per its page metadata; the cases themselves are undated. It states that “Our solutions stop the fraud before the money leaves the bank” and lists about two dozen short case studies at unnamed banks. One is an account takeover after pharming stopped before a CHF 19,990 payment. Another is an impersonation that led a bank employee to validate a CHF 1,000,000 transaction, blocked because the beneficiary was unusual at bank level. There are vishing, tech-support, CEO-fraud, business-email-compromise, romance and invoice-redirection cases. Their payments of EUR 22,114, EUR 33,170, USD 7,500, GBP 21,000, EUR 125,000, EUR 170,000, USD 100,000, USD 170,000 and USD 850,000 were stopped. Transaction or e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language) did not match the customer's or bank's usual profile. There are two internal-fraud cases. In one case “fraudsters were arrested while attempting to withdraw USD 500,000 (KSh 58 million) from the second bank's ATMs”. The models had flagged unusual timing and frequency of withdrawals. One entry still names “NetGuardians solution”, the Swiss company that merged with Belgium's Intix to form Vyntra in June 2025 (FinTech Global, 19 June 2025). No customer, bank, country, date, regulator or court record is given for any case, and none was found. The page is the vendor's own account.",
            "replication": {
              "produced_by": [
                "Behavioral profiles of each customer's and the bank's usual transaction and e-banking session variables (beneficiary, country, amount, currency, browser, screen resolution, language)",
                "Real-time scoring before a payment is released"
              ],
              "must_hold": [
                "The fraudulent transaction departs from the profile on several variables; the vendor notes cases with little customer history relied on bank-level anomalies",
                "The bank acts on the alert before the money leaves"
              ],
              "echoes": []
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "account",
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 30,
      "reviewed": 0,
      "record_mapped": 30,
      "not_assessed": 61,
      "complete": false,
      "by_state": {
        "value_present": 30,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 61,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}