DeXposure-Claw: An Agentic System for DeFi Risk Supervision
- URL: http://arxiv.org/abs/2606.19501v1
- Date: Wed, 17 Jun 2026 18:40:08 GMT
- Title: DeXposure-Claw: An Agentic System for DeFi Risk Supervision
- Abstract summary: General-purpose LLM agents fit this setting poorly.<n>Existing evaluations offer no regulator-aligned way to measure the resulting false alarms.<n>We introduce DeXposure-Claw, a forecast-grounded agentic supervision system.
- Score: 18.719297847519552
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Decentralized finance exposes supervisors to fast-moving, networked credit risks. General-purpose LLM agents fit this setting poorly: they over-read weak evidence and recommend high-stakes interventions, while existing evaluations offer no regulator-aligned way to measure the resulting false alarms. We introduce DeXposure-Claw, a forecast-grounded agentic supervision system that routes LLM decisions through structured evidence: (1) DeXposure-FM, a graph time-series foundation model, forecasts future exposure networks; (2) deterministic monitors and stress scenarios then turn those forecasts into typed alerts, attribution signals, and scenario evidence; and (3) data-health and confidence gates constrain escalation before DeXposure-Claw emits auditable supervisory tickets with rationales. We further develop DeXposure-Bench, a six-axis evaluation harness, whose decision axis scores tickets against a regulator-aligned absolute-loss ground truth and an explicit false-intervention rate. Experiments on five years of weekly real data fully support our system. Code is at https://github.com/EVIEHub/DeXposure-Claw.
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