{ "id": "AIBD-0180", "title": "RBI Innovation Hub's MuleHunter.AI adopted by 23 banks; RBI declines to disclose mule accounts found", "summary": "MediaNama's RTI (December 2025) found 23 banks had implemented RBIH's MuleHunter.AI, which analyzes transaction patterns to spot mule accounts; the RBI refused to release detection figures, citing ...", "date_observed": "2025-12-30", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "MediaNama (Prabhanu Kumar Das) reported on 30 December 2025 on a Right to Information response. It showed 23 banks had implemented MuleHunter.AI as of 10 December 2025. That was up from at least 15 in August and nearly 20 in November 2025. The report named Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank. The tool was developed by the Reserve Bank Innovation Hub (RBIH). It analyzes transaction and account activity patterns across banks to identify accounts likely used as mules in financial fraud. The Reserve Bank of India (RBI) said that it cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI. The reason given was that it holds such information in a fiduciary capacity with banks and disclosure could harm competitive interests. RBI Governor Sanjay Malhotra is reported as saying that the tool is showing a good success rate, without figures. RBIH's own project page was not available. News headlines from May to September 2026 describe an I4C-RBIH memorandum and deployment across 31 banks. The articles behind those headlines are not among the sources.", "category": "general benefit", "unexpected": false, "purpose": "Identify bank accounts likely used as money mules in financial fraud.", "system": "MuleHunter.AI", "model_version": null, "developer": "Reserve Bank Innovation Hub (RBIH)", "deployer": "23 Indian banks as of 10 December 2025, including Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank", "location": null, "domain": "Anti-money laundering and cyber fraud", "segment": "Mule account detection", "benefit_type": "Reduced Risk", "taxonomy_note": "Adoption only; the type names the mule-account fraud the tool is meant to catch.", "registry_ids": {}, "ratings": [ { "group": "organizational", "depth": null, "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "depth": null, "reason": "No fraud loss avoided is documented." } ], "ai_role": { "status": "unassessed", "statement": "The tool is described as AI-based pattern analysis across banks. No detection result is available to assess its contribution. RBIH, a central-bank subsidiary, developed it. Commercial and public-sector banks deploy it." }, "evidence": [ { "kind": "news report", "citation": "Prabhanu Kumar Das, MediaNama, 30 December 2025", "title": "RTI Reveals 23 Banks Have Implemented Mulehunter.AI, But Total Mule Accounts Identified Still Not Disclosed", "url": "https://www.medianama.com/2025/12/223-rti-23-banks-mulehunter-mule-accounts/", "date": "2025-12-30", "written_by": "independent", "quote": "cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI" }, { "kind": "press release", "citation": "Press Information Bureau (2026). I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds. Ministry of Home Affairs via PIB, 12 May 2026.", "title": "I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "date": "2026-05-12", "written_by": "makers", "quote": null } ], "replication": { "produced_by": [ "Cross-bank transaction and account-activity pattern analysis run by a central-bank-owned hub" ], "must_hold": [ "Bank adoption and data sharing with the hub", "Public disclosure of detection outcomes, without which no evaluation is possible" ], "echoes": [ { "date": "2026-05-12", "setting": "I4C and RBIH memorandum on AI-driven mule-account detection", "model_version": null, "outcome": "unknown", "source": "Google News RSS headlines (Indian Express, Economic Times, DD News) only" } ] }, "paired_incident": null, "headline": "RBIH's MuleHunter.AI adopted by 23 banks; RBI withholds figures", "metric": null, "comparator": null, "later": { "status": "persisted", "date": "2026-05-12", "note": "I4C and RBIH signed an MoU to feed suspect identifiers from I4C's Suspect Registry into MuleHunter.ai and to use the data to retrain it.", "quote": "Under the MoU, I4C and RBIH will collaborate for sharing of mule account related intelligence and suspect identifiers from I4C-MHA’s Suspect Registry to strengthen AI-driven fraud detection systems such as MuleHunter.ai™ implemented across banks. RBIH will utilise the datasets for training and enhancement of AI-driven fraud-risk assessment models, including MuleHunter.ai™.", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277" }, "value": null, "developer_country": "India", "deployer_country": "India", "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "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" }, { "date": "2026-10-21", "change": "Added what happened since from the cited sources.", "source": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Reserve_Bank_of_India; https://en.wikipedia.org/wiki/Canara_Bank", "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" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "reported", "shade": "medium", "claim_status": "Independently reported", "claim_basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "profile": { "case_id": "AIBD-0180", "catalog_version": "1.0.0", "source_fingerprint": "3a66e7de9ab0a77fb448b9bf589ebea2a990899ef305b2b3dc90d0d5b687ffd1", "collection_refs": [ { "collection_id": "aibd", "version": "snapshot-8bf7cfec9cb185aa" }, { "collection_id": "aibd", "version": "2026-10-25" }, { "collection_id": "chanticleer", "version": "2026-10-25" } ], "source_ids": [ "AIBD-0180-source-0001", "AIBD-0180-source-0002" ], "families": { "strategic assessments": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "evaluations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "monetary observations": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] }, "institutional decisions": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial", "record_ids": [] } }, "fields": { "actors[]": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "developer": "Reserve Bank Innovation Hub (RBIH)", "deployer": "23 Indian banks as of 10 December 2025, including Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer", "deployer" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "actors[].ownership_control": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_contribution": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "ai_relationship": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "category": "general benefit", "ai_role": { "status": "unassessed", "statement": "The tool is described as AI-based pattern analysis across banks. No detection result is available to assess its contribution. RBIH, a central-bank subsidiary, developed it. Commercial and public-sector banks deploy it." } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "ai_role", "category" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].alternatives": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].assessor_date": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].depth": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].display_confidence": { "state": "value_present", "value": { "kind": "structured", "data": { "confidence": "medium", "evidence_word": "reported", "claim_status": "Independently reported", "basis": "Sources: one independent news report and the makers' press release. The cited evidence includes no independent study or report and no finding by a regulator or court.", "interpretation": "Existing display rule preserved; the richer outcome-specific confidence question still needs review." } }, "provenance": { "kind": "curatorial", "basis": "Derived from the existing case display properties; not a new evidentiary judgment.", "record_fields": [], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "assessments[].rationale": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "reason": "No fraud loss avoided 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" }, "assessments[].rubric_version": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].status_basis": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "assessments[].target": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "ratings": [ { "group": "organizational", "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "reason": "No fraud loss avoided 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" }, "availability": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "brief": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_kind": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "case_links[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_links": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "claims[].evidence_strength": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, 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RBIH will utilise the datasets for training and enhancement of AI-driven fraud-risk assessment models, including MuleHunter.ai™.", "url": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277" } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "later" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "human_oversight": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "id": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "id": "AIBD-0180" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "id" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "infrastructure_dependencies[]": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiaries": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].beneficiary_count": { "state": "not_assessed", "review_state": "not_assessed", "coverage": "partial" }, "outcomes[].benefit_type": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "benefit_type": "Reduced Risk", "taxonomy_note": "Adoption only; the type names the mule-account fraud the tool is meant to catch." } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "benefit_type", "taxonomy_note" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "outcomes[].claim": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "account": "MediaNama (Prabhanu Kumar Das) reported on 30 December 2025 on a Right to Information response. It showed 23 banks had implemented MuleHunter.AI as of 10 December 2025. That was up from at least 15 in August and nearly 20 in November 2025. The report named Canara Bank, Punjab National Bank, Bank of India, Bank of Baroda, AU Small Finance Bank and Federal Bank. The tool was developed by the Reserve Bank Innovation Hub (RBIH). It analyzes transaction and account activity patterns across banks to identify accounts likely used as mules in financial fraud. The Reserve Bank of India (RBI) said that it cannot provide data on the number of mule accounts identified or acted upon through MuleHunter.AI. The reason given was that it holds such information in a fiduciary capacity with banks and disclosure could harm competitive interests. RBI Governor Sanjay Malhotra is reported as saying that the tool is showing a good success rate, without figures. RBIH's own project page was not available. News headlines from May to September 2026 describe an I4C-RBIH memorandum and deployment across 31 banks. The articles behind those headlines are not among the sources.", "benefit_type": "Reduced Risk" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "account", "benefit_type" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "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": "organizational", "reason": "No count of mule accounts identified or frozen is disclosed. The RBI refused the RTI request for that data." }, { "group": "societal", "reason": "No fraud loss avoided 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": "Identify bank accounts likely used as money mules in financial fraud." } }, "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": { "developer_country": "India", "deployer_country": "India" } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; external sources were not rechecked.", "record_fields": [ "developer_country", "deployer_country" ], "source_refs": [] }, "review_state": "record_mapped", "coverage": "partial" }, "purpose": { "state": "value_present", "value": { "kind": "record_fields", "fields": { "purpose": "Identify bank accounts likely used as money mules in financial fraud." } }, "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": "2025-12-30", "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 Organizational Efficiency 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": "Added what happened since from the cited sources.", "source": "https://www.pib.gov.in/PressReleasePage.aspx?PRID=2260277", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer and the deployer added from the organization's own site or a registry.", "source": "https://en.wikipedia.org/wiki/Reserve_Bank_of_India; https://en.wikipedia.org/wiki/Canara_Bank", "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" }, { "date": "2026-10-21", "change": "Notes about which sources could be read were reworded for readers; 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": "value_present", "value": { "kind": "record_fields", "fields": { "replication": { "produced_by": [ "Cross-bank transaction and account-activity pattern analysis run by a central-bank-owned hub" ], "must_hold": [ "Bank adoption and data sharing with the hub", "Public disclosure of detection outcomes, without which no evaluation is possible" ], "echoes": [ { "date": "2026-05-12", "setting": "I4C and RBIH memorandum on AI-driven mule-account detection", "outcome": "unknown", "source": "Google News RSS headlines (Indian Express, Economic Times, DD News) only" } ] } } }, "provenance": { "kind": "legacy_record", "basis": "Preserved from the existing AIBD record; 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I4C and RBIH Sign MoU to Strengthen AI-Driven Detection of Mule Accounts and Cyber Financial Frauds. 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News headlines from May to September 2026 describe an I4C-RBIH memorandum and deployment across 31 banks. The articles behind those headlines are not among the sources.", "replication": { "produced_by": [ "Cross-bank transaction and account-activity pattern analysis run by a central-bank-owned hub" ], "must_hold": [ "Bank adoption and data sharing with the hub", "Public disclosure of detection outcomes, without which no evaluation is possible" ], "echoes": [ { "date": "2026-05-12", "setting": "I4C and RBIH memorandum on AI-driven mule-account detection", "outcome": "unknown", "source": "Google News RSS headlines (Indian Express, Economic Times, DD News) only" } ] } } }, "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": 27, "reviewed": 0, "record_mapped": 27, "not_assessed": 64, "complete": false, "by_state": { "value_present": 27, "not_reported": 0, "unresolved": 0, "not_assessed": 64, "not_applicable": 0, "withheld": 0, "source_unavailable": 0 } } } }