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1

Some remarks about benford’s distribution

100%
Baryła M.
Mathematical Economics
|
2012
|
issue 8 (15)
5-15
EN
The aim of the following article is to present some facts about Benford’s distribution. Its main focus is on selected descriptors of this distribution (such as mean, variance and skewness) and its two major properties, i.e. base invariance and scale invariance. At the end of the paper some applications of Benford’s distribution are presented.
2
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From business to clinical trials: a systematic review of the literature on fraud detection methods to be used in central statistical monitoring

88%
Fronc M., Jakubczyk M.
|
2022
|
vol. 69
|
issue 3
1-22
EN
Data-driven decisions can be suboptimal when the data are distorted by fraudulent behaviour. Fraud is a common occurrence in finance or other related industries, where large datasets are handled and motivation for financial gain may be high. In order to detect and the prevent fraud, quantitative methods are used. Fraud, however, is also committed in other circumstances, e.g. during clinical trials. The article aims to verify which analytical fraud-detection methods used in finance may be adopted in the field of clinical trials. We systematically reviewed papers published over the last five years in two databases (Scopus and the Web of Science) in the field of economics, finance, management and business in general. We considered a broad scope of data mining techniques including artificial intelligence algorithms. As a result, 37 quantitative methods were identified with the potential of being fit for application in clinical trials. The methods were grouped into three categories: pre-processing techniques, supervised learning and unsupervised learning. Our findings may enhance the future use of fraud-detection methods in clinical trials.
3
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Feature Engineering for Anti-Fraud Models Based on Anomaly Detection

75%
Przekop D.
Central European Journal of Economic Modelling and Econometrics
|
2020
|
issue 3
4

Decision Tree Approach to Discovering Fraud in Leasing Agreements

63%
Horvat I., Pejić Bach M., Merkač Skok M.
Business Systems Research Journal
|
2014
|
vol. 5
|
issue 2
61-71
EN
Background: Fraud attempts create large losses for financing subjects in modern economies. At the same time, leasing agreements have become more and more popular as a means of financing objects such as machinery and vehicles, but are more vulnerable to fraud attempts. Objectives: The goal of the paper is to estimate the usability of the data mining approach in discovering fraud in leasing agreements. Methods/Approach: Real-world data from one Croatian leasing firm was used for creating tow models for fraud detection in leasing. The decision tree method was used for creating a classification model, and the CHAID algorithm was deployed. Results: The decision tree model has indicated that the object of the leasing agreement had the strongest impact on the probability of fraud. Conclusions: In order to enhance the probability of the developed model, it would be necessary to develop software that would enable automated, quick and transparent retrieval of data from the system, processing according to the rules and displaying the results in multiple categories.
5
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Zwalczanie nadużyć finansowych w funduszach UE : Narzędzia stosowane do ochrony budżetu Unii, cz. II

51%
Szymański M.
Kontrola Państwowa
|
2021
|
vol. 66
|
issue 4 (399)
27-61
EN
In the next years, Member States will be spending funds from the EU’s largest package ever. It comprises money from the multi-annual financial perspective (2021–2027) and the reconstruction plan – designed to mitigate the crisis and provide the basis for developing modern and sustainable Europe. It will be a great challenge to eliminate fraud in the funds spending. However, it seems feasible to reduce fraud because over the last years EU institutions have made fraud combating their priority. The second part of the article related to the protection of EU financial interests focuses on mea sures and good practices examples that may significantly contribute to counteracting corruption, understood in a broad sense. It describes tools that are applied mainly by the institutions responsible for EU funds implementation aimed at identifying fraud, including a mechanism for anonymous reporting on irregularities (in the context of the Whistleblower Directive). The author discusses potential instruments developed in response to the most frequent irregularities areas, i.e. breaches in public procurement, conflicts of interests, or collusive tendering. An innovative instrument, designated for social control of public funds spending – the so called integrity pact – has been dis cussed in more detail. The author also presents IT tools to increase public spending transparency and to identify suspicious transactions.
PL
Druga część artykułu na temat ochrony interesów finansowych UE przed nadużyciami prezentuje działania, których wdrożenie w ramach systemu kontroli zarządczej może wspomagać przeciwdziałanie szeroko rozumianej korupcji. Wskazuje też przykłady praktyk niektórych urzędów. Odnoszą się one do obszarów największego ryzyka i dotyczą zarówno zapobiegania, jak i wykrywania nadużyć finansowych. Artykuł opisuje narzędzia stosowane głównie przez instytucje odpowiedzialne za wdrażanie środków unijnych, w tym mechanizm służący anonimowemu sygnalizowaniu nieprawidłowości (w kontekście dyrektywy poświęconej ochronie sygnalistów). W tej części przedstawiono możliwe do zastosowania rozwiązania, będące odpowiedzią na najczęściej występujące nieprawidłowości, przede wszystkim naruszenia w obszarze zamówień publicznych, konflikt interesów czy zmowy przetargowe. Przybliżono także tzw. pakt uczciwości, innowacyjny instrument kontroli społecznej wydatkowania środków publicznych. Opisano stosowane narzędzia informatyczne zwiększające przejrzystość wydatków publicznych, a także ułatwiające identyfikację podejrzanych transakcji.
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