智能财务工具在公司治理中风险预警功能的实现路径与应用

胡应林

经济与产业发展 ›› 2025, Vol. 02 ›› Issue (06) : 1 -3.

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经济与产业发展 ›› 2025, Vol. 02 ›› Issue (06) : 1 -3. DOI: 10.12349/ecin.v2i6.7867

智能财务工具在公司治理中风险预警功能的实现路径与应用

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The realization path and application of risk early warning function of intelligent financial tools in corporate governance

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摘要

随着数字经济与人工智能融合加深,企业治理和财务管理模式正迎来变革。智能财务工具依托大数据、AI和云计算,已成为公司治理风险预警的重要手段。高效的预警体系不仅提升财务透明度和内控效率,还强化了决策支持与风险防范。本文梳理智能财务工具在治理中的理论基础,分析其技术架构与功能优势,探讨其在风险预警中的实现路径,包括数据采集、智能分析、动态监测与实时预警。结合案例,评估其在风险管控、决策支持与合规管理中的成效。研究指出,实践中仍存在技术瓶颈、组织障碍和管理挑战。为此提出优化建议,强调智能财务在提升风险识别与治理现代化中的作用,并展望其在智能决策与战略治理中的创新趋势。

Abstract

As digital economy and artificial intelligence converge, corporate governance and financial management models are undergoing transformative changes. Intelligent financial tools, leveraging big data, AI, and cloud computing, have become crucial for early risk warnings in corporate governance. These efficient early-warning systems not only enhance financial transparency and internal control efficiency but also strengthen decision-making support and risk prevention. This paper examines the theoretical foundations of intelligent financial tools in governance, analyzes their technical architecture and functional advantages, and explores implementation pathways for risk warning through data collection, smart analysis, dynamic monitoring, and real-time alerts. Case studies evaluate their effectiveness in risk control, decision support, and compliance management. The research identifies persistent challenges including technical bottlenecks, organizational barriers, and managerial difficulties. Practical optimization suggestions are proposed to emphasize intelligent finance’s role in modernizing risk identification and governance, while envisioning innovative trends in intelligent decision-making and strategic governance.

关键词

智能财务 / 风险预警 / 公司治理 / 大数据 / 人工智能

Key words

intelligent finance / risk early warning / corporate governance / big data / artificial intelligence

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胡应林. 智能财务工具在公司治理中风险预警功能的实现路径与应用[J]. 经济与产业发展, 2025, 02(06): 1-3 DOI:10.12349/ecin.v2i6.7867

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