Against the backdrop of the accelerating digital economy, the corporate operating environment is characterized by high complexity and uncertainty. The widespread application of big data technology has fostered the deep integration of information flow, value flow, and resource flow, presenting new challenges and opportunities for corporate internal control and audit models. Based on relevant research findings domestically and internationally, combined with typical corporate practice cases, this paper systematically explores how big data technology drives the intelligent restructuring of corporate internal control systems and the digital transformation of audit processes. Research indicates that by building data driven risk early warning mechanisms, promoting process automation and platform integration, strengthening data governance capabilities, and cultivating interdisciplinary audit talent, enterprises can significantly enhance organizational agility, compliance levels, and governance effectiveness. Simultaneously, this paper also identifies current practical obstacles such as data security, lack of standards, and technical barriers, and proposes corresponding countermeasures. It aims to provide theoretical support and practical pathways for advancing the high-quality development of corporate internal control and audit models.