The quality of financial information of listed companies reflects the authenticity of the information conveyed in their financial reports, which significantly influences accurate decision-making for investors, analysts, regulatory bodies, and other stakeholders. This paper addresses the issue of evaluating the financial information quality of listed companies in the Northwest region and proposes an assessment method based on artificial neural networks. By constructing a deep neural network model and integrating multiple data sources, including financial statement data and market information, the method accurately assesses the reliability and accuracy of a company’s financial information. In experiments using a substantial amount of real-world data, the effectiveness and superiority of this approach were validated. The research results demonstrate that artificial neural networks can accurately evaluate financial information quality, providing important decision-making references for investors, managers, and others.