Melhoria da qualidade nas demonstrações financeiras numa empresa de contabilidade

O papel da inteligência artificial

Abstract

Analysing the quality of income statements in an accounting firm is often a laborious and error-prone task, undermining the reliability of the financial information provided to business clients. To tackle this issue, a diagnostic assessment of internal processes and market practices was carried out, leading to the development of an application model tailored to the firm’s operational context. The solution was designed using real accounting data, applying financial ratios as objective quality indicators and benchmarking against sector best practices. At the core of the model is an algorithm capable of automatically assessing the quality of income statements, aiming to reduce errors, improve consistency, and accelerate the review process. The model was tested with actual client data, and its application proved effective in detecting material inaccuracies and inconsistencies that would otherwise go unnoticed. It also supported a more standardised and transparent validation process, reinforcing the quality assurance mechanisms within the firm. Given the positive results, a phased implementation is recommended, ensuring seamless integration into existing workflows. Continuous monitoring and evaluation of its impact are essential to promote iterative refinement and long-term sustainability of the solution. This initiative not only strengthens the reliability of financial reporting but also contributes to operational efficiency and reinforces the firm’s positioning as a technology-driven accounting service provider.