{
  "id": "AIBD-0185",
  "title": "ChatGPT flags red flags on a fake pre-IPO adviser; 77-year-old in Bengaluru reports Rs 67.10 lakh fraud to police",
  "summary": "After withdrawals were refused, a 77-year-old Binnypet resident checked the firm's credentials with ChatGPT, which flagged complaints and inconsistencies; he reported the Rs 67.10 lakh fraud to Ben...",
  "date_observed": "2026-01-06",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed.",
  "category": "protective response",
  "unexpected": false,
  "purpose": "General-purpose conversational assistant that answers users' questions.",
  "system": "ChatGPT",
  "model_version": null,
  "developer": "OpenAI",
  "deployer": "The victim, using the consumer app himself",
  "location": "Bengaluru, India",
  "domain": "Investment fraud",
  "segment": "Pre-IPO share scam",
  "benefit_type": "Reduced Risk",
  "taxonomy_note": "The loss had occurred; the good is recognition and reporting of the fraud.",
  "registry_ids": {},
  "ratings": [
    {
      "group": "personal",
      "depth": 2,
      "reason": "The victim recognized the fraud and filed a police complaint after ChatGPT's response. Deccan Herald says that this stopped further payments. No money was recovered in the reports read."
    },
    {
      "group": "societal",
      "depth": null,
      "reason": "No outcome beyond the single complaint is documented."
    },
    {
      "group": "organizational",
      "depth": null,
      "reason": "The police registered a case. No organizational outcome is documented."
    }
  ],
  "ai_role": {
    "status": "assessed",
    "statement": "Both reports attribute the discovery to ChatGPT's response flagging complaints and credential inconsistencies when the victim queried the firm. That came after his own suspicion at refused withdrawals. The exact output is not reproduced. OpenAI had no role beyond providing the consumer product."
  },
  "evidence": [
    {
      "kind": "news report",
      "citation": "The New Indian Express, Bengaluru, 6 January 2026",
      "title": "ChatGPT alert helps Bengaluru senior citizen uncover Rs 67 lakh pre-IPO investment fraud",
      "url": "https://www.newindianexpress.com/cities/bengaluru/2026/Jan/06/chatgpt-alert-helps-bengaluru-senior-citizen-uncover-rs-67-lakh-pre-ipo-investment-fraud",
      "date": "2026-01-06",
      "written_by": "independent",
      "quote": "The fraud came to light after the victim checked the firm's credentials using ChatGPT, which flagged multiple warning signs."
    },
    {
      "kind": "news report",
      "citation": "Prajwal D'Souza, Deccan Herald, 6 January 2026",
      "title": "Bengaluru: ChatGPT response saves 77-year-old man from losing more money to cybercriminals",
      "url": "https://www.deccanherald.com/india/karnataka/bengaluru/bengaluru-chatgpt-response-saves-77-year-old-man-from-losing-more-money-to-cybercriminals-3853142",
      "date": "2026-01-06",
      "written_by": "independent",
      "quote": "The scammers had already cheated him of Rs 67.10 lakh through a fake investment scam."
    }
  ],
  "replication": {
    "produced_by": [
      "A victim querying a large language model about a company and its representatives after withdrawals were refused",
      "Public complaints and credential inconsistencies about the scheme that the model could surface"
    ],
    "must_hold": [
      "Suspicion arising before further payments",
      "Model output that points to specific red flags rather than generic caution",
      "Police registration for any tracing or recovery"
    ],
    "echoes": []
  },
  "paired_incident": null,
  "headline": "ChatGPT flags fake adviser; victim reports Rs 67.10 lakh fraud",
  "metric": null,
  "comparator": null,
  "later": {
    "status": "unknown",
    "date": null,
    "note": "Reports as of January 2026 say a case was registered and the money trail is being traced; no arrest or recovery was found.",
    "quote": null,
    "url": null
  },
  "value": null,
  "developer_country": "United States",
  "deployer_country": null,
  "unrated_because": null,
  "brief_notes": null,
  "brief": null,
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    {
      "date": "2026-10-20",
      "change": "Record drafted from the cited sources.",
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      "editor": "AIBD"
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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 Knowledge Discovery among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Country of the developer added from the organization's own site or a registry.",
      "source": "https://en.wikipedia.org/wiki/OpenAI",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
      "source": null,
      "editor": "AIBD"
    }
  ],
  "confidence": "reported",
  "shade": "medium",
  "claim_status": "Independently reported",
  "claim_basis": "Sources: two independent news reports. The cited evidence includes no independent study or report and no finding by a regulator or court.",
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            "account": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed.",
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      "outcomes[].distribution": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].duration": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].id": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].stakeholder_group": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "ratings": [
              {
                "group": "personal",
                "depth": 2,
                "reason": "The victim recognized the fraud and filed a police complaint after ChatGPT's response. Deccan Herald says that this stopped further payments. No money was recovered in the reports read."
              },
              {
                "group": "societal",
                "reason": "No outcome beyond the single complaint is documented."
              },
              {
                "group": "organizational",
                "reason": "The police registered a case. No organizational outcome is documented."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "ratings"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "outcomes[].status": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].tradeoffs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].unexpected": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "unexpected": false,
            "purpose": "General-purpose conversational assistant that answers users' questions."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "unexpected",
            "purpose"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "places[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "location": "Bengaluru, India",
            "developer_country": "United States"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "location",
            "developer_country"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "purpose": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "purpose": "General-purpose conversational assistant that answers users' questions."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "purpose"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "record_dates": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "date_observed": "2026-01-06",
            "revisions": [
              {
                "date": "2026-10-20",
                "change": "Record drafted from the cited sources.",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
                "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/OpenAI",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "date_observed",
            "revisions"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "replication.attempts[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "replication.conditions": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "replication": {
              "produced_by": [
                "A victim querying a large language model about a company and its representatives after withdrawals were refused",
                "Public complaints and credential inconsistencies about the scheme that the model could surface"
              ],
              "must_hold": [
                "Suspicion arising before further payments",
                "Model output that points to specific red flags rather than generic caution",
                "Police registration for any tracing or recovery"
              ],
              "echoes": []
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "revision_history[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "revisions": [
              {
                "date": "2026-10-20",
                "change": "Record drafted from the cited sources.",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Benefit type set to Reduced Risk under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
                "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/OpenAI",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "revisions"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sector": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "domain": "Investment fraud",
            "segment": "Pre-IPO share scam"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "domain",
            "segment"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].access_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "sources[].citation_locator": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "evidence": [
              {
                "kind": "news report",
                "citation": "The New Indian Express, Bengaluru, 6 January 2026",
                "title": "ChatGPT alert helps Bengaluru senior citizen uncover Rs 67 lakh pre-IPO investment fraud",
                "url": "https://www.newindianexpress.com/cities/bengaluru/2026/Jan/06/chatgpt-alert-helps-bengaluru-senior-citizen-uncover-rs-67-lakh-pre-ipo-investment-fraud",
                "date": "2026-01-06",
                "written_by": "independent",
                "quote": "The fraud came to light after the victim checked the firm's credentials using ChatGPT, which flagged multiple warning signs."
              },
              {
                "kind": "news report",
                "citation": "Prajwal D'Souza, Deccan Herald, 6 January 2026",
                "title": "Bengaluru: ChatGPT response saves 77-year-old man from losing more money to cybercriminals",
                "url": "https://www.deccanherald.com/india/karnataka/bengaluru/bengaluru-chatgpt-response-saves-77-year-old-man-from-losing-more-money-to-cybercriminals-3853142",
                "date": "2026-01-06",
                "written_by": "independent",
                "quote": "The scammers had already cheated him of Rs 67.10 lakh through a fake investment scam."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "evidence"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].id": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
            "AIBD-0185-source-0001",
            "AIBD-0185-source-0002"
          ],
          "role": "Existing evidence items, in their original order"
        },
        "provenance": {
          "kind": "curatorial",
          "basis": "Stable within the fingerprinted record version; no source content or source review has been added.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "sources[].language": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "sources[].relationship": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "evidence": [
              {
                "kind": "news report",
                "citation": "The New Indian Express, Bengaluru, 6 January 2026",
                "title": "ChatGPT alert helps Bengaluru senior citizen uncover Rs 67 lakh pre-IPO investment fraud",
                "url": "https://www.newindianexpress.com/cities/bengaluru/2026/Jan/06/chatgpt-alert-helps-bengaluru-senior-citizen-uncover-rs-67-lakh-pre-ipo-investment-fraud",
                "date": "2026-01-06",
                "written_by": "independent",
                "quote": "The fraud came to light after the victim checked the firm's credentials using ChatGPT, which flagged multiple warning signs."
              },
              {
                "kind": "news report",
                "citation": "Prajwal D'Souza, Deccan Herald, 6 January 2026",
                "title": "Bengaluru: ChatGPT response saves 77-year-old man from losing more money to cybercriminals",
                "url": "https://www.deccanherald.com/india/karnataka/bengaluru/bengaluru-chatgpt-response-saves-77-year-old-man-from-losing-more-money-to-cybercriminals-3853142",
                "date": "2026-01-06",
                "written_by": "independent",
                "quote": "The scammers had already cheated him of Rs 67.10 lakh through a fake investment scam."
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "evidence"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].upstream_sources": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "strategic_assessments[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "strategic assessments"
      },
      "summary": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "summary": "After withdrawals were refused, a 77-year-old Binnypet resident checked the firm's credentials with ChatGPT, which flagged complaints and inconsistencies; he reported the Rs 67.10 lakh fraud to Ben...",
            "account": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "summary",
            "account"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].autonomy_permissions": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].component_role": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].deployment_configuration": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].inputs_outputs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_name": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].product_name": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "system": "ChatGPT"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "system"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].provider": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "application_developer": "OpenAI"
          }
        },
        "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": "ChatGPT flags red flags on a fake pre-IPO adviser; 77-year-old in Bengaluru reports Rs 67.10 lakh fraud to police",
            "headline": "ChatGPT flags fake adviser; victim reports Rs 67.10 lakh 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": [
            "f6c0a087d5b24db8a8b779d822e10293d456ab2962ad17de12e5fcfedd1835c7"
          ],
          "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": "The New Indian Express (6 January 2026) reported on a 77-year-old resident of Binnypet, Bengaluru. In November 2025 a man calling himself Yatin Shah contacted him. He claimed to be an adviser with IIFL Wealth Management and promised assured allotment of pre-IPO shares. The victim first transferred Rs 5 lakh for a supposed ICICI Prudential AMC pre-IPO and was shown profits in a digital wallet. Over the following weeks he made multiple RTGS transfers totaling Rs 67.10 lakh. When requests to withdraw even part of the funds were denied, he searched for details about the company and its representatives using ChatGPT. It reportedly flagged complaints, inconsistencies in company credentials and indicators associated with investment fraud. He then approached the police, who registered a case under the Information Technology Act. The police said that efforts were under way to trace the money. Deccan Herald (Prajwal D'Souza, 6 January 2026) framed the ChatGPT response as saving him from losing more money. No police official is named, no recovery is reported and the victim is unnamed.",
            "replication": {
              "produced_by": [
                "A victim querying a large language model about a company and its representatives after withdrawals were refused",
                "Public complaints and credential inconsistencies about the scheme that the model could surface"
              ],
              "must_hold": [
                "Suspicion arising before further payments",
                "Model output that points to specific red flags rather than generic caution",
                "Police registration for any tracing or recovery"
              ],
              "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": 28,
      "reviewed": 0,
      "record_mapped": 28,
      "not_assessed": 63,
      "complete": false,
      "by_state": {
        "value_present": 28,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 63,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}