Chan Ye Xin Xi Wang·2025-04-24 01:18Core Insights - The tax big data market in China is experiencing significant growth, with the market size projected to increase from 30.869 billion yuan in 2019 to 103.213 billion yuan by 2024, indicating a strong demand driven by ongoing tax administration reforms [1][9]. Tax Big Data Industry Definition and Classification - Tax big data refers to the vast and diverse data sets generated, collected, stored, and managed during tax management, collection, and inspection processes, encompassing structured, unstructured, and semi-structured data [1]. Tax Big Data Industry Value Chain Analysis - The industry value chain includes data collection from various sources, data storage and processing, and application services, with a focus on optimizing tax management and enhancing taxpayer services [3]. Development History of China's Tax Big Data Industry - The industry has evolved from initial informatization in the 1980s to intelligent applications post-2013, with significant advancements in data integration and risk management [5]. Current State of China's Tax Big Data Industry - The market is growing steadily, with a notable increase in demand for tax big data software and services due to the implementation of data-driven tax management strategies [9]. Downstream Application Areas of Tax Big Data - The industry exhibits a diversified application landscape, with tax collection accounting for 45% of the market, risk prevention at 25%, taxpayer services at 18%, and economic analysis at 10% [11]. Key Enterprises in China's Tax Big Data Industry - Major players include Digital China, which focuses on tax digitalization solutions; Aerospace Information, a leader in electronic invoicing; Inspur, which provides infrastructure and data governance; and Yonyou Network, specializing in enterprise tax management [13][14][16]. Future Development Trends of China's Tax Big Data Industry - The industry is expected to enhance data governance and compliance, expand data sharing and integration across departments, and leverage technologies like AI and blockchain to innovate business scenarios and improve efficiency [18][19][20].