库帕思高质量金融多领域思维链（Chain-of-Thought）数据集

本数据集面向教育大模型研发团队、金融科技企业及金融机构，旨在解决金融领域多学科知识体系复杂、跨领域推理能力不足等痛点。通过系统化清洗和思维链重构，整合了银行信贷、证券投资、保险精算、基金理财、期货衍生品、财务会计、风险管理、金融法规等八大核心金融领域的试题资源，涵盖从基础金融知识到高级专业实务的全方位内容。

通过思维链训练，可为基座大模型提供金融全领域的通识能力培养，同时助力金融垂类模型在跨领域业务场景下的专业推理能力提升。本数据集在八大领域基础上，重点强化了领域间交叉知识点（如银行信贷中的担保法律问题）的思维链覆盖。

This dataset is tailored for educational large language model (LLM) R&D teams, fintech enterprises and financial institutions, aiming to resolve pain points including the complex multi-disciplinary knowledge system in the financial sector and insufficient cross-domain reasoning capabilities. Through systematic data cleaning and chain-of-thought reconstruction, it aggregates question resources across eight core financial domains: bank credit, securities investment, insurance actuarial science, fund wealth management, futures and derivatives, financial accounting, risk management, and financial regulations, covering full-range content from basic financial knowledge to advanced professional practices. Leveraging chain-of-thought training, this dataset can foster general financial domain proficiency for base LLMs, while enabling financial vertical LLMs to enhance their professional reasoning capabilities in cross-domain business scenarios. Based on the eight core domains, this dataset places special emphasis on expanding chain-of-thought coverage for inter-domain cross-cutting knowledge points, such as legal guarantee-related issues in bank credit.

搜集汇总

背景与挑战

背景概述

该数据集面向教育大模型研发团队、金融科技企业及金融机构，旨在通过思维链训练提升金融领域的跨领域推理能力。它系统整合了银行信贷、证券投资、保险精算等八大核心金融领域的试题资源，覆盖从基础知识到高级实务的全方位内容。数据集特别强化了领域间交叉知识点的思维链覆盖，以支持金融全产业链的智能应用开发。