Research on Optimization of M&A Financial Due Diligence Process Based on Data Analysis

Abstract

With the continuous development of data technology, enterprises have put forward higher requirements for the efficiency and accuracy of financial due diligence in merger and acquisition activities. The traditional due diligence process, due to many problems such as scattered data sources, lagging analysis, and insufficient security, can no longer meet the increasingly complex needs of mergers and acquisitions. This paper focuses on data analysis, conducts in-depth research from aspects such as the acquisition, processing and risk identification mechanism of financial data, proposes data-driven optimization strategies, builds a unified interface, real-time monitoring platform and data security system, which can enhance the intelligence, standardization and systematization level of financial due diligence in mergers and acquisitions, and provide more efficient and reliable support for enterprises' merger and acquisition decisions.