Construction of Accounting Information Quality Assessment Model Based on Big Data Analysis

This article aims to build an accounting information quality assessment model based on big data analysis to cope with the limitations of traditional assessment methods in data processing, assessment efficiency and accuracy. Through the comprehensive application of big data technology and machine learning algorithm, it aims to improve the comprehensiveness and accuracy of accounting information quality assessment. Firstly, this article constructs an assessment index system of accounting information quality including key dimensions such as reliability, relevance, timeliness and integrity. Then, the massive accounting data is cleaned, transformed and integrated by using the big data processing platform to form a data set suitable for analysis and assessment. The model is trained and tested by machine learning algorithm, and the scores of each assessment index and the comprehensive assessment results are obtained. The results show that the accounting information quality assessment model based on big data analysis performs well in key indicators such as accuracy, recall and F1-score, which significantly improves the efficiency and accuracy of accounting information quality assessment. This model can provide a new tool for enterprise's accounting information quality management.