Year: 2025
Type: article
Abstract: This paper addresses the inefficiencies and heavy reliance on human judgment in traditional internal control auditing, as well as the challenges posed by sparse sample data. In this context, we propose a transfer learning–based predictive model for internal control deficiencies. The core idea uses U.S. SOX 404 data as the source domain and Chinese A-share listed companies as the target domain. The model is designed using a “pre-training—transfer—adaptation—calibration” framework, and is developed along four dimensions: the data and labeling system, model pre-training, model fine-tuning, and evaluation metrics. The research provides explainable risk indicators and practical guidelines for regulators, audit practitioners, and corporate governance.
DOI: 10.54097/dhv74d62
Author: Dongjie Lin
Institution: Central University of Finance and Economics
Language: English
Subfield: Accounting
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4414464863
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