Accounting information and the risk of noncompliance with contracts by companies contracted by the public sector
DOI:
https://doi.org/10.1590/1808-057x20252241.enKeywords:
public innovation, insolvency prediction, public procurement, accounting informationAbstract
This study aimed to develop the Contractual Noncompliance Risk Index (CNRI) to evaluate the ability of accounting data from suppliers to predict defaults in Brazilian public sector contracts. Despite advances in predictive methodologies in the private sector, there is a lack of studies that adapt these methods to the public sector. Current legislation and the heterogeneity of suppliers underscore the need for instruments that leverage accounting information more effectively. This study contributes to the literature by addressing a theoretical gap in the systematic use of accounting information for the economic and financial evaluation of public-sector suppliers. Additionally, it aligns with regulatory reforms and the 2030 Agenda, reinforcing innovation (SDG 9) and effective institutions (SDG 16) through efficiency and transparency. The CNRI promotes risk-based financial audits, contract oversight, and economic and financial qualifications, thereby enhancing the credibility of accounting records in Brazilian public procurement. We used an exploratory, quantitative approach to analyze data from 311 suppliers that participated in bids or contracts with the Superior Court of Justice (Superior Tribunal de Justiça – STJ) between 2018 and 2023. Inspired by traditional insolvency prediction models, we used logistic regression to model the probability of penalties based on accounting variables, such as indebtedness, liquidity, and ROI, as well as control variables, such as company size and penalty history. Our results showed that higher long-term indebtedness, immobilization of resources, ROI, and current liquidity reduce the risk of contractual noncompliance. Additionally, the CNRI proved effective in identifying low-risk suppliers. Control variables improved the accuracy of the CNRI by accounting for sector-specific characteristics and supplier heterogeneity. This study proposes a practical, replicable, and predictive model that improves risk management, oversight, auditing, and economic and financial qualification in Brazilian public procurement.
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