Preventing rather than punishing: An early warning model of malfeasance in public procurement

Gallego, Jorge; Rivero, Gonzalo; Martínez, Juan Diego Sánchez

doi:10.1016/j.ijforecast.2020.06.006

Cited by 50 publications

(45 citation statements)

References 72 publications

(68 reference statements)

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“…Machine learning models have proven useful in other policy-related prediction issues (Kleinberg et al, 2015), such as security (Bogomolov et al, 2014), poverty (Blumenstock et al, 2015, and conflict (Blair et al, 2017;Bazzi et al, 2018). Lopez-Iturriaga and Sanz (2017) and Gallego et al (2018b) study corruption using aggregate data and newspaper evidence from Spanish provinces and public procurement in Colombia, respectively. municipalities, constructed using the share of total number of irregularities over the size of the municipality.…”

Section: Empirical Designmentioning

confidence: 99%

What Predicts Corruption?

et al. 2019

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Using rich micro-data from Brazil, we show that multiple machine learning models display high levels of performance in predicting municipality-level corruption in public spending. Measures of private sector activity, financial development, and human capital are the strongest predictors of corruption, while public sector and political features play a secondary role. Our findings have implications for the design and cost-effectiveness of various anti-corruption policies.

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Section: Empirical Designmentioning

confidence: 99%

What Predicts Corruption?

et al. 2019

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“…The most commonly used methods in the studies are linear and logistic regression, neural networks, and Naive Bayes algorithms since they are most used for classification and clustering. Namely, models are fitted on historical data and move in the direction of an early warning system that can provide pre-determined supervisory bodies with insights into the risks associated with concluding contracts with risky economic operators [1,18,21] or can identify potential cartels or collusion behavior using associative rules or graph databases algorithms to see the relationships between economic operators and eventually their daughter companies [12,25,26,29,32,43].…”

Section: A Corruption Detection Methods and Modelsmentioning

confidence: 99%

Review of Public Procurement Fraud Detection Techniques Powered by Emerging Technologies

Modrušan¹,

Rabuzin²,

Mršić³

2021

IJACSA

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Numerous studies and various methods have been used to detect and prevent corruption in public procurement. With the development of IT technology and thus the digitization of the Public Procurement Process (PPP), the amount of available data is increasing. Studies have shown progress in this area and have revealed many challenges and open issues geared to the various goals outlined in this paper. Different data mining and business intelligence techniques and methods are being used to develop models that will find any suspicious public procurement process, contracts, economic operators, or to classify observations as corrupt. In addition to using classification models, methods such as association rules and graph databases are used to find relationships between economic operators and contracting authorities, as well as to find daughter companies that participate in PPP collusion. Therefore, this paper addresses a comprehensive review of the emerging techniques and models used for the detection of suspicious or corrupted observations, their goals, open issues, challenges, methods and metrics used, tools, and relevant data sources. The findings show that models are mostly fitted on historical data and move in the direction of an early warning system. Moreover, the efficiency of fraud or anomaly detection depends on data set quality and detection of the most important red flags. The study is presenting a summary of identified fraud detection model objectives such as predicting fraud risk in contracts and contractors or finding split purchases, and detection of used data sources such as public procurement process or economic operator data.

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“…Gallego et al argued that this could help in anticipating which transactions may have high corruption risk. [28] Specialized training for procurement officials and procurement auditors could also be an effective way to prevent or detect procurement irregularities. The OECD indicated that there are three critical, overarching factors that underpin the procurement system, which may engender or heighten possible risks of corruption throughout the procurement chain and these are; a) budget management, b) personnel management, and c) staff capacity.…”

Section: Corruption In Procurement Practicementioning

confidence: 99%

Causes and Costs of Procurement Irregularities in Ghana’s District Assemblies

Quashie¹

2019

IJLS

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The Ghana government introduced procurement regulation in 2003 to govern the public procurement function in the country. However, high levels of irregularities still abound in the performance of the procurement function. The Auditor-General's reports for the years 2014 to 2018, revealed procurement irregularities at the country's District Assemblies. These irregularities could pose high corruption risk to the procurement process by creating fertile grounds for fraud and corruption in public procurement practice at the District Assemblies. Although articles have been written about procurement practice in Ghana, not much has been said about the practice at the district level. This article therefore seeks to fill this gap. The article throws a critical searchlight on public procurement practice at the country's District Assemblies. The methodology employed is a doctrinal one whereby the adherence or otherwise to public procurement laws of the country by the District Assemblies is looked at. The analysis of procurement practice at the assemblies has revealed that the hub of the matter facing public procurement in Ghana is the elusiveness of implementation of the tenets of the procurement regime. Having identified the weaknesses in the procurement practice, the article suggests palliatives by resorting to innovations reported in other jurisdictions to address the gap.

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Preventing rather than punishing: An early warning model of malfeasance in public procurement

Cited by 50 publications

References 72 publications

What Predicts Corruption?

What Predicts Corruption?

Review of Public Procurement Fraud Detection Techniques Powered by Emerging Technologies

Causes and Costs of Procurement Irregularities in Ghana’s District Assemblies

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