Artificial Intelligence-Driven Corporate Finance: Enhancing Efficiency and Decision-Making Through Machine Learning, Natural Language Processing, and Robotic Process Automation in Corporate Governance and Sustainability

Nitin Rane, Saurabh Choudhary, Jayesh Rane
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引用次数: 1

Abstract

This research paper delves into the transformative possibilities of Artificial Intelligence (AI) within corporate finance, specifically focusing on its role in improving efficiency and decision-making processes. Through the utilization of machine learning, natural language processing (NLP), and robotic process automation (RPA), AI introduces innovative methods for enhancing corporate governance and sustainability practices. In the contemporary business landscape, corporations encounter mounting pressure to streamline operations while simultaneously addressing concerns regarding environmental, social, and governance (ESG) issues. Conventional finance methodologies often struggle to efficiently handle large volumes of data and extract actionable insights promptly. However, AI presents a shift in paradigm by enabling automated data analysis, recognizing patterns, and conducting predictive modeling, thus enabling finance professionals to make data-informed decisions swiftly and accurately. Machine learning algorithms play a pivotal role in detecting patterns and correlations within financial data, facilitating proactive risk management and strategic planning. Additionally, NLP technologies facilitate the extraction of valuable insights from unstructured data sources like regulatory filings, news articles, and social media, thereby enabling informed decision-making in corporate governance and sustainability endeavors. Moreover, RPA simplifies repetitive tasks and workflows, thereby reducing operational expenses and freeing up human resources for more strategic pursuits. Through the automation of routine processes such as data entry, reconciliation, and reporting, RPA enhances operational efficiency and ensures adherence to regulatory standards. Through the adoption of AI technologies, corporations can unlock novel avenues for innovation, optimize resource allocation, and promote sustainable growth within today's dynamic business milieu.
人工智能驱动的公司财务:通过机器学习、自然语言处理和机器人流程自动化提高公司治理和可持续发展的效率和决策能力
本研究论文深入探讨了人工智能(AI)在企业财务领域的变革可能性,特别关注其在提高效率和决策过程中的作用。通过利用机器学习、自然语言处理(NLP)和机器人流程自动化(RPA),人工智能为加强公司治理和可持续发展实践引入了创新方法。在当代商业环境中,企业面临着越来越大的压力,既要简化运营,又要解决环境、社会和治理(ESG)问题。传统的财务方法往往难以有效地处理大量数据并迅速提取可操作的见解。然而,人工智能通过自动数据分析、识别模式和进行预测建模实现了模式的转变,从而使财务专业人员能够迅速、准确地做出基于数据的决策。机器学习算法在检测金融数据中的模式和相关性、促进主动风险管理和战略规划方面发挥着关键作用。此外,NLP 技术有助于从监管文件、新闻文章和社交媒体等非结构化数据源中提取有价值的见解,从而在公司治理和可持续发展方面做出明智的决策。此外,RPA 还能简化重复性任务和工作流程,从而降低运营成本,将人力资源释放出来,用于更具战略性的工作。通过数据录入、对账和报告等常规流程的自动化,RPA 提高了运营效率,并确保遵守监管标准。通过采用人工智能技术,企业可以在当今充满活力的商业环境中开辟新的创新途径,优化资源配置,促进可持续增长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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