A quantitatively validated Latin American model for corruption risk detection in public procurement open data
Main Article Content
Abstract
This research presents the Latin American Integrated Risk Model (LAIRM), a formally delineated and reproducible computational framework aimed at improving the identification of corruption risks in public procurement processes across Latin America. The LAIRM was developed to address the limitations of current international benchmarks. It employs a robust mathematical structure grounded in institutional and principal-agent theories to combine weighted factors, such as non-competitive bidding, vendor opacity, and post-award modifications. Cross-validation and risk testing using open data from Mexico, Brazil, and Colombia validated the model’s efficacy. The results showed an F1-score 15% higher than the World Bank’s Red Flags framework, with an 18% to 25% increase in early detection probability. By demonstrating that this evidence-based method is applicable to both large and small-scale projects, this study bridges theoretical depth with practical value. Future work is outlined to ensure proper systemic implementation and continuous accuracy of the results.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
RAP is committed to contributing to the protection of the author's intellectual rights. In this regard, it:
- Adopts the Creative Commons Attribution BY 4.0 license, which allows articles to be reused and distributed without restriction, provided that the original work is properly cited;
- Ensures moral and usage rights of the article to authors, in accordance with Creative Commons Attribution BY 4.0. Authors retain the copyright to the published article, and the journal holds the right of first publication;
- Utilizes content similarity/plagiarism detection software (Crossref Similarity Check);
- Recommends the use of CRediT (Contributor Roles Taxonomy) authorship criteria;
- Adopts actions to combat plagiarism and ethical misconduct, aligned with the Committee on Publication Ethics (COPE) guidelines;
- Reserves the right to make changes to the original versions regarding normative, spelling, and grammatical standards to maintain high linguistic quality and layout standardization, while respecting the authors' style. Subsequently, authors will receive the final versions for approval prior to publication.
Further information on the Code of Ethics adopted by RAP can be found in Ethical Standards and Code of Conduct.
References
Acemoglu, D., & Restrepo, P. (2018). Artificial intelligence, automation, and work. In A. Agrawal, J. Gans & A. Goldfarb (Eds.), The Economics of Artificial Intelligence: An Agenda (pp. 197-236). University of Chicago Press. http://www.nber.org/books/agra-1
Adam, I., & Fazekas, M. (2021). Are emerging technologies helping win the fight against corruption? A review of the state of evidence. Information Economics and Policy, 57, 100950. https://doi.org/10.1016/j.infoecopol.2021.100950
Agencia Nacional de Contratación Pública Colombia Compra Eficiente. (2025). SECOP II. https://www.colombiacompra.gov.co/secop/secop-ii
Agu, J. C., Nkwo, F. N., & Eneiga, R. U. (2024). Governance and anti-corruption measures in Nigeria: Strategies for enhancing transparency, accountability and public trust. International Journal of Economics and Public Policy, 8(1), 1-15. https://doi.org/10.5281/zenodo.12576796
Alfian, A., Ritchi, H., & Adrianto, Z. (2023). Fraud analytics practices in public-sector transactions: a systematic review. Journal of Public Budgeting, Accounting & Financial Management, 35(5), 685-710. https://doi.org/10.1108/JPBAFM-11-2022-0175
Alnuaimi, N. T., CHatha, K. A., & Abdallah, S. (2024). Role of big data analytics and information processing capabilities in enhancing transparency and accountability in e-procurement applications. Journal of Engineering, Design and Technology, 23(5), 1729-1750. https://doi.org/10.1108/JEDT-12-2023-0544
Androutsopoulou, M., Askounis, D., Carayannis, E. G., & Zotas, N. (2024). Leveraging AI for enhanced eGovernment: Optimizing the use of open governmental data. Journal of the Knowledge Economy, 16, 12998-13033. https://doi.org/10.1007/s13132-024-02317-w
Arellano-Gault, D., Rojas-Salazar, G., & Vargas-Pineda, L. R. (2025). Critical theory in public policy and anti-corruption strategies in Latin America: unveiling the limitations (and hypocrisy?) of the dominant anti-corruption discourse. In L. Secchi & C. N. Cruz-Rubio (Eds.), Handbook of Public Policy in Latin America (pp. 356-371). Elgar.
Bahoo, S., Alon, I., & Floreani, J. (2021). Corruption in economics: a bibliometric analysis and research agenda. Applied Economics Letters, 28(7), 565-578. https://doi.org/10.1080/13504851.2020.1764476
Barata, J., & Kayser, I. (2023). Industry 5.0 – Past, Present, and Near Future. Procedia Computer Science, 219, 778-788. https://doi.org/10.1016/j.procs.2023.01.351
Borsboom, D., Deserno, M. K., Rhemtulla, M., Epskamp, S., Fried, E. I., McNally, R. J., Robinaugh, D. J., Perugini, M., Dalege, J., Costantini, G., Isvoranu, A.-M., Wysocki, A. C., Borkulo, C. D. van, Bork, R. van, & Waldorp, L. J. (2021). Network analysis of multivariate data in psychological science. Nature Reviews Methods Primers, 1(1), 58. https://doi.org/10.1038/s43586-021-00055-w
Breuer, M., Labro, E., Sapra, H., & Zakolyukina, A. A. (2024). Bridging theory and empirical research in accounting. Journal of Accounting Research, 62(3), 1121-1139. https://doi.org/10.1111/1475-679X.12545
Brückner, A., Wölke, M., Hein-Pensel, F., Schero, E., Winkler, H., & Jabs, I. (2025). Assessing industry 5.0 readiness—Prototype of a holistic digital index to evaluate sustainability, resilience and human-centered factors. International Journal of Information Management Data Insights, 5(1), 100329. https://doi.org/10.1016/j.jjimei.2025.100329
Chen, C., & Ganapati, S. (2023). Do transparency mechanisms reduce government corruption? A meta-analysis. International Review of Administrative Sciences, 89(1), 257-272. https://doi.org/10.1177/00208523211033236
Chystiakova, A., Podliehaiev, K., Khoronovskyi, O., Sokur, T., & Kubariev, I. (2025). The role of big data analytics in the investigation of corruption offences. Revista Jurídica Portucalense, 116-143. https://doi.org/10.34625/issn.2183-2705(37)2025.ic-6
Controladoria Geral da União. (2025). Portal da Transparência. https://portaldatransparencia.gov.br/
Davis, D. B., Mendoza, R. U., & Yap, J. K. (2024). Corruption risk and political dynasties: exploring the links using public procurement data in the Philippines. Economics of Governance, 25(1), 81-109. https://doi.org/10.1007/s10101-023-00306-4
Dessureault, J.-S., Lamontagne, R., & Parisé, P.-O. (2025). The ethics of creating artificial superintelligence: a global risk perspective. AI and Ethics, 5, 6241-6263. https://doi.org/10.1007/s43681-025-00793-7
Didier, N. (2025). Decolonizing Public Administration in Latin America: A systematic literature review of trending discussions in the region. Public Administration and Development, 1-18. https://doi.org/10.1002/pad.2092
Fazekas, M., & Kocsis, G. (2020). Uncovering High-Level Corruption: Cross-National Objective Corruption Risk Indicators Using Public Procurement Data. British journal of political science, 50(1), 155-164. https://doi.org/10.1017/S0007123417000461
Genest, Y. (2025). The evolution of internal audit in anti-corruption activities: leveraging data analytics and it technology. EDPACS, 70(4), 60-66. https://doi.org/10.1080/07366981.2025.2453271
Ghobakhloo, M., Iranmanesh, M., Mubarak, M. F., Mubarik, M., Rejeb, A., & Nilashi, M. (2022). Identifying industry 5.0 contributions to sustainable development: A strategy roadmap for delivering sustainability values. Sustainable Production and Consumption, 33, 716-737. https://doi.org/10.1016/j.spc.2022.08.003
Gobierno de México. (2025). Compras MX. https://comprasmx.buengobierno.gob.mx/
Gutiérrez-Romero, R., & Iturbe, N. (2024). Causes and electoral consequences of political assassinations: The role of organized crime in Mexico. Political Geography, 115, 103206. https://doi.org/10.1016/j.polgeo.2024.103206
Horochovski, R. R., Mancuso, W. P., & Pereira, T. F. (2024). A produção acadêmica sobre o Caso Lava Jato. Revista de Sociologia e Política, 32, e021. https://doi.org/10.1590/1678-98732432e021
Kaswan, M. S., Chaudhary, R., Garza-Reyes, J. A., & Singh, A. (2024). A review of Industry 5.0: from key facets to a conceptual implementation framework. International Journal of Quality & Reliability Management, 42(4), 1196-1223. https://doi.org/10.1108/IJQRM-01-2024-0030
Kenny, C., & Musatova, M. (2010). Red flags of corruption in World Bank projects: An analysis of infrastructure contracts. In S. Rose-Ackerman & T. Søreide (Eds.), International handbook on the economics of corruption (Vol. 2, pp. 299-335). Edward Elgar Publishing. https://doi.org/10.1596/1813-9450-5243
Kirby, N. (2021). An ‘institution-first’conception of public integrity. British journal of political science, 51(4), 1620-1635. https://doi.org/10.1017/S000712342000006X
Klitgaard, R. (1988). Controlling corruption. University of California Press.
Kour, R., Karim, R., Dersin, P., & Venkatesh, N. (2024). Cybersecurity for Industry 5.0: trends and gaps. Frontiers in Computer Science, 6, 1434436. https://doi.org/10.3389/fcomp.2024.1434436
León, A. J. A. V. (2012). Revisión de las reformas a la Ley de Adquisiciones, Arrendamientos y Servicios del Sector Público del 28 de mayo de 2009, en materia de licitaciones públicas [Undergraduate thesis, Centro de Investigación y Docencia Económicas]. Repositorio Digital CIDE. http://hdl.handle.net/11651/4829
Linhartova, V., & Pucek, M. J. (2024). Corruption and Human Development: Panel Data Analysis in Transition Economies. Montenegrin Journal of Economics, 20(2), 169-182. https://doi.org/10.14254/1800-5845/2024.20-2.14
Luthra, A., Dixit, S., Garg, S., Singh, A., & Anchal, M. (2025). Addressing Ethical Considerations and Responsible AI Practices. In A. Behl, C. Krishnan, P. Malik & S. Gautam (Eds.), The ChatGPT Revolution: How Conversational AI is Transforming Customer Service and Business Operations (pp. 129-149). https://doi.org/10.1108/978-1-83549-852-120251007
Madhala, R. T. (2025). Driving Digital Transformation in Insurance: The Role of System Integration and Guidewire Expertise. International Journal of Emerging Trends in Computer Science and Information Technology, 91-100. https://doi.org/10.56472/ICCSAIML25-111
Meyer, K. Z., Luiz, J. M., & Fedderke, J. W. (2025). Corruption dynamics: Integrating structure, agency and institutional logics across contexts. International Journal of Management Reviews, 28(1), e12403. https://doi.org/10.1111/ijmr.12403
Mittal, P. (2020). Big data and analytics: a data management perspective in public administration. International Journal of Big Data Management, 1(2), 152-165. https://doi.org/10.1504/IJBDM.2020.112415
North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge University Press.
North, D. C. (2025). Institutions and the Performance of Economies Over Time. In C. Ménard & M. M. Shirley (Eds.), Handbook of New Institutional Economics (pp. 25-35). Springer. https://doi.org/10.1007/978-3-031-50810-3_2
Organisation for Economic Co-operation and Development. (2019). Government at a Glance 2019. OECD Publishing. https://www.oecd.org/en/publications/government-at-a-glance-2019_8ccf5c38-en.html
Rabuzin, K., & Modrusan, N. (2019, September). Prediction of Public Procurement Corruption Indices using Machine Learning Methods. Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Vienna, Austria. https://doi.org/10.5220/0008353603330340
Rajala, T., & Jalonen, H. (2025). Beyond Simplification in Public Sector Accountability: Contradictions Between Principal‐Agent and Complexity Theories. Public Administration Review, 85(6), 1757-1770. https://doi.org/10.1111/puar.13941
Rojas, V. C. J. (2022). Responsabilidad precontractual del estado: imprecisiones en el sistema de subsanabilidad en Colombia a partir del SECOP II. [Undergraduate thesis]. Universidad Externado de Colombia.
Rose-Ackerman, S., & Palifka, B. J. (2016). Corruption and government: Causes, consequences, and reform. Cambridge University Press.
Smidt, H., Mitchell, N. J., & Bakke, K. M. (2025). A red flag for public goods? The correlates of civil society restrictions. Governance, 38(2), e12894. https://doi.org/10.1111/gove.12894
Souza, P. V. N. C. S., Ramos, T. M., & Silva, L. G. (2021). Inclinações pragmáticas na nova Lei de Licitações e Contratos Administrativos (Lei nº 14.133/2021): novos princípios, velhos problemas. Revista de Direito Brasileira, 29(11), 4-15. https://doi.org/10.26668/IndexLawJournals/2358-1352/2021.v29i11.7514
Storey, V. C., Baskerville, R. L., & Kaul, M. (2025). Reliability in design science research. Information Systems Journal, 35(3), 984-1014. https://doi.org/10.1111/isj.12564
Trequattrini, R., Palmaccio, M., Turco, M., & Manzari, A. (2024). The contribution of blockchain technologies to anti‐corruption practices: A systematic literature review. Business Strategy and the Environment, 33(1), 4-18. https://doi.org/10.1002/bse.3327
Velásquez, A. G., & Díez, C. A. D. (2019). El contrato de prestación de servicios en el estatuto general de contratación de la administración pública: un tipo contractual de compleja celebración. Vniversitas, 68(139), 1-17. https://doi.org/10.11144/Javeriana.vj139.cpse
Wachs, J., & Kertész, J. (2019). A network approach to cartel detection in public auction markets. Scientific Reports, 9(1), 10818. https://doi.org/10.1038/s41598-019-47198-1
Wahab, S., Imran, M., Ahmed, B., Rahim, S., & Hassan, T. (2024). Navigating environmental concerns: Unveiling the role of economic growth, trade, resources and institutional quality on greenhouse gas emissions in OECD countries. Journal of Cleaner Production, 434, 139851. https://doi.org/10.1016/j.jclepro.2023.139851
Yatsyna, Y., & Kudinov, I. (2023). Innovative analytical and statistical technology as a corruption counteraction tool: conceptual analysis. Amazonia Investiga, 12(67), 78-86. https://doi.org/10.34069/AI/2023.67.07.7