A quantitatively validated Latin American model for open-data corruption risk detection in public procurement
Bibliographic Data
| ID | 21381994 |
|---|---|
| Authors | Gabriel Silva Atencio (0000-0002-4881-181X, Universidad Latinoamericana de Ciencia y Tecnología, corresponding author) |
| Year | 2026 |
| Publication date | 2026-04-22 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Revista de Administração Pública (JOURNAL) |
| Journal identifiers | ISSN: 0034-7612 • E-ISSN: 1982-3134 |
| Publisher | FapUNIFESP (SciELO) (PUBLISHER) |
| DOI | 10.1590/0034-761220250356x |
| OpenAlex | W7155160038 |
| Language | EN |
This research presents the Latin American Integrated Risk Model (LAIRM), a formally delineated and reproducible computational framework aimed at detecting wrongdoing, especially in public buying processes across Latin America. The study’s scope is limited to procurement-related corruption, as opposed to other forms of public-sector malfeasance, to enable precise indicator construction and empirical validation, using open contracting data. The LAIRM was developed to address limitations in existing international benchmarks. It uses a mathematical framework based on principal-agent and institutional theories to combine weighted factors, such as non-competitive methods and vendor opacity. Cross-validation and risk tests with open data from Mexico, Brazil, and Colombia showed that the model was correct. The F1-score achieved by LAIRM was 15% higher than that of the World Bank’s Red Flags framework, with an estimated 18–25% improvement in early detection rates. The study demonstrates that the evidence-based method is applicable to large and small-scale projects. Subsequent plans to the study will ensure proper program implementation and the accuracy of the results
Empirical research · Language change · Latin Americans · Procurement · Risk management · Scope (computer science) · Vendor · Auction Theory and Applications · Corruption and Economic Development · Public Procurement and Policy
| Highly cited | No |
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