arXiv:2606.11537v1 Announce Type: new Abstract: Financial and tabular question answering requires more than fluent reasoning: answers must be grounded in the exact facts, formulas, units, signs, and scales that support them. A single misread cell or incorrect operation can silently produce a plausible but wrong result. We introduce \textsc{MOCA-Agent}, a market-of-claims code agent that replaces free-form multi-agent debate with claim-level verification. The system decomposes each question into typed atomic claims, asks specialist trader agents to buy or sell those claims, clears their orders
The increasing complexity and unreliability of large language models for precise numerical and financial tasks drive the need for more robust, verifiable AI agentic systems.
This development represents a significant step towards enabling AI agents to handle complex financial and numerical reasoning with greater accuracy and auditability, critical for widespread adoption in sensitive domains.
The method of AI-driven financial analysis shifts from free-form multi-agent debate to structured, claim-level verification, enhancing accuracy and trustworthiness.
- · Financial services industry
- · AI agent developers
- · Quantitative analysis platforms
- · Regulatory technology (RegTech)
- · AI models without built-in verification
- · Manual data verification processes
- · Companies relying on opaque AI financial models
Financial institutions gain access to more reliable and auditable AI tools for complex reasoning and decision-making.
Increased trust in AI-driven financial analysis could lead to its integration into core trading and investment strategies, reducing human oversight in certain areas.
The 'market-of-claims' paradigm could extend beyond finance to other critical domains requiring verifiable AI reasoning, accelerating automation across regulated industries.
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Read at arXiv cs.AI