mlsanityData to 14 Oct 2026

Authority-Inference Separation in Agentic Finance: First-Line Control, Blockchain Enforcement, and Replayable Assurance

arXiv 2608.30519 ↗First posted 31 Aug 2026q-fin.GN cs.CRcited by 0

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

AI agents can select tools, counterparties, and transaction parameters, yet inference should not itself confer authority to execute a financial action. This study develops and evaluates Authority-Inference Separation (AIS), an intent-centered architecture for bounded agentic finance. AIS treats a financial action intent as the control object: a machine-generated proposal can receive temporary executable authority only after an independent deterministic control plane validates registered agent identity, accountable ownership, mandate and risk-appetite lineage, policy version, state, approvals, and exact economic semantics. Blockchain can then enforce the operational representation of granted authority and record portable settlement evidence, while institutional legitimacy, service delivery, accounting classification, and human accountability remain off-chain obligations. Evaluation combines four-domain instantiation, official BIS and MAS cases, a 48-fixture executable prototype, and a public-ledger observability test. Across 36 synthetic authorization attacks, a direct-agent baseline accepted 36 attack effects, a prompt-policy baseline accepted 20, and AIS accepted none; all three accepted 8/8 admissible fixtures. AIS also rejected 4/4 token replays and 8/8 recipient or rail substitutions, withheld completion in 4/4 service-delivery failures, and populated all 13 defined evidence fields. A test of 1,700 recent Base transactions associated with public x402 facilitator addresses shows that public ledgers can evidence settlement and selected authorization parameters but cannot establish institutional mandate, legal accountability, service delivery, or accounting treatment. AIS and blockchain are therefore complementary: AIS decides whether a specific intent may act, while blockchain can make granted authority bounded, executable, and independently observable.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 5 of its 40 references that are in the map. First posted on arXiv 31 Aug 2026.

Builds on

5 of 40 references.

References · 5

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  3. 2023Identifying the Risks of LM Agents with an LM-Emulated Sandboxcited by 548
  4. 2026When HTTP 402 Meets the Blockchain: Risks on Emerging x402 Paymentscited by 3
  5. 2026How Agentic Is Agentic Commerce? A Population-Scale Measurement of x402 Adoption and Authenticitycited by 2

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  2. 2026PACE: Policy-Attested Contract Execution for Safe AI Agents in Decentralized Finance
  3. 2026Behavioral Governance for Autonomous AI Agents: The AgentBound Framework
  4. 2025Agentic AI for Financial Crime Compliance
  5. 2026Insuring Every Action: An Authority Frontier Framework for Runtime Actuarial Control of Autonomous AI Agents
  6. 2026Agentic AI, Retrieval-Augmented Generation, and the Institutional Turn: Legal Architectures and Financial Governance in the Age of Distributional AGI
  7. 2026Compliant with Local Controls, Collectively Discriminatory. A Governance Architecture for Multi-Agent AI in Regulated Finance
  8. 2026Autonomous Agents on Blockchains: Standards, Execution Models, and Trust Boundaries