基于大模型的证券交易与清算的智能辅助系统及方法

By introducing a legal form-aware restricted decoder and a joint intent encoding mechanism into a large-scale intelligent auxiliary system for securities trading and clearing, the contradiction between form and semantics in the generation of trading instructions is resolved, strong consistency in the execution of trading and clearing is achieved, default risk is reduced, and compliance requirements of financial regulation are met.

CN121810403BActive Publication Date: 2026-07-17SHANGHAI GUANKAI SOFTWARE TECH CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SHANGHAI GUANKAI SOFTWARE TECH CO LTD
Filing Date
2026-03-06
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing intelligent auxiliary systems for securities trading and clearing based on large models struggle to perceive and embed the rigid constraints of the clearing process in real time when generating trading instructions. This results in automated instructions being frequently rejected due to format inconsistencies or logical violations, increasing the risk of settlement defaults. Furthermore, the system's reliance on extensive manual verification restricts the reliability and security of intelligent methods in core financial business scenarios.

Method used

By introducing a legally form-aware restricted decoder and a joint intent encoding mechanism, compliant trading instructions that meet regulatory and exchange formal requirements are generated. Combined with regulatory rule-anchored inference chains and gradient coordination mechanisms, model parameters are optimized to ensure the formal validity and semantic rationality of the instructions.

Benefits of technology

It achieves strong consistency in the execution of trading and clearing instructions, reduces the risk of settlement default, ensures the compliance and executability of instructions, meets the requirements of financial regulators for the accuracy and atomicity of instructions, and realizes atomic execution and audit traceability under intelligent decision-making.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明公开了基于大模型的证券交易与清算的智能辅助系统及方法,属于专门适用于金融的数据处理系统或方法技术领域,包括:接收用户交易意图自然语言描述及实时约束状态信息并预处理;提取金融语义特征生成初始交易语义向量;通过法律形式感知的受限解码器生成合规交易指令;构建联合意图张量,同步生成资金划拨与证券过户指令;结合监管规则锚定推理链及梯度协调机制优化模型,生成交易清算指令包。本发明解决现有技术概率解码导致的指令不合规、券款对付原子性缺失等问题,确保指令符合监管与业务规范,实现智能决策下的原子性执行与审计追溯,降低业务风险,满足金融监管底线要求。
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