BLADE-FINANCE Governance Node: Authority Governance for Financial-Sector AI Decision Systems Under the Treasury Financial Services AI Risk Management Framework
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| Format: | Recurso digital |
| Sprache: | Englisch |
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2026
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| _version_ | 1866902161934254080 |
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| author | Oktenli, Burak |
| author_facet | Oktenli, Burak |
| contents | <p>Simulation-validated, software-enforced authority-arbitration reference architecture for financial-sector AI decision systems, aligned to the U.S. Treasury Financial Services AI Risk Management Framework (FS AI RMF) under the implementation framing of Executive Order 14179. An eight-stage AUTHREX pipeline (VALIDATE, SATA, ADARA, MAIVA, HMAA, FLAME, ERAM, CARA) with a four-tier HMAA authority model, a population-state coordination model across account, device, payee, and IP-cluster history, a SHA-256 canonical-form evidence chain, and a retrospective stigmergic swarm-review module that recovers coordinated rings the per-transaction path clears. Reference authority node: 36 hardware components, 33 electrical connections, 32 mechanical connections, approximately $9,228 BOM. TRL 3-4 (simulation) / TRL 2 (hardware); synthetic data only; not deployed in any financial institution. The reported recall is an actionable-risk triage measure, not an empirical fraud-detection rate. Published as fundamental research under CC BY 4.0.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20374692 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | BLADE-FINANCE Governance Node: Authority Governance for Financial-Sector AI Decision Systems Under the Treasury Financial Services AI Risk Management Framework Oktenli, Burak authority-governed autonomy financial-sector AI governance runtime assurance Treasury FS AI RMF NIST AI RMF Executive Order 14179 economic security Hierarchical Multi-Attribute Authority SHA-256 evidence chain canonical-form serialization deepfake authentication AI-agent coordinated attack retrospective swarm review stigmergic ensemble escalation-delta triage metrics Wilson interval <p>Simulation-validated, software-enforced authority-arbitration reference architecture for financial-sector AI decision systems, aligned to the U.S. Treasury Financial Services AI Risk Management Framework (FS AI RMF) under the implementation framing of Executive Order 14179. An eight-stage AUTHREX pipeline (VALIDATE, SATA, ADARA, MAIVA, HMAA, FLAME, ERAM, CARA) with a four-tier HMAA authority model, a population-state coordination model across account, device, payee, and IP-cluster history, a SHA-256 canonical-form evidence chain, and a retrospective stigmergic swarm-review module that recovers coordinated rings the per-transaction path clears. Reference authority node: 36 hardware components, 33 electrical connections, 32 mechanical connections, approximately $9,228 BOM. TRL 3-4 (simulation) / TRL 2 (hardware); synthetic data only; not deployed in any financial institution. The reported recall is an actionable-risk triage measure, not an empirical fraud-detection rate. Published as fundamental research under CC BY 4.0.</p> |
| title | BLADE-FINANCE Governance Node: Authority Governance for Financial-Sector AI Decision Systems Under the Treasury Financial Services AI Risk Management Framework |
| topic | authority-governed autonomy financial-sector AI governance runtime assurance Treasury FS AI RMF NIST AI RMF Executive Order 14179 economic security Hierarchical Multi-Attribute Authority SHA-256 evidence chain canonical-form serialization deepfake authentication AI-agent coordinated attack retrospective swarm review stigmergic ensemble escalation-delta triage metrics Wilson interval |
| url | https://doi.org/10.5281/zenodo.20374692 |