Next Article in Journal
Insolvency Risk and Value Maximization: A Convergence between Financial Management and Risk Management
Next Article in Special Issue
A Statistical Model of Fraud Risk in Financial Statements. Case for Romania Companies
Previous Article in Journal
Adapting the Default Weighted Survival Analysis Modelling Approach to Model IFRS 9 LGD
Previous Article in Special Issue
The Impact of the Development of Society on Economic and Financial Crime. Case Study for European Union Member States
Article

Privacy Intrusiveness in Financial-Banking Fraud Detection

1
Faculty of Law, Babes-Bolyai University, 400591 Cluj-Napoca, Romania
2
Faculty of Economics and Business Administration, Babes-Bolyai University, 400591 Cluj-Napoca, Romania
3
Faculty of Economics and Business Administration and the Interdisciplinary Centre for Data Science, Babes-Bolyai University, 400591 Cluj-Napoca, Romania
4
Police Faculty, “Alexandru Ioan Cuza” Police Academy, 014031 Bucharest, Romania
5
European Research Institute, Babes-Bolyai University, 400591 Cluj-Napoca, Romania
6
Faculty of Automatics, Computer Science & Electronics, University of Craiova, 200585 Craiova, Romania
*
Author to whom correspondence should be addressed.
Academic Editor: Tomas Kliestik
Received: 26 April 2021 / Revised: 18 May 2021 / Accepted: 21 May 2021 / Published: 1 June 2021
(This article belongs to the Special Issue Economic and Financial Crimes)
Specialty literature and solutions in the market have been focusing in the last decade on collecting and aggregating significant amounts of data about transactions (and user behavior) and on refining the algorithms used to identify fraud. At the same time, legislation in the European Union has been adopted in the same direction (e.g., PSD2) in order to impose obligations on stakeholders to identify fraud. However, on the one hand, the legislation provides a high-level description of this legal obligation, and on the other hand, the solutions in the market are diversifying in terms of data collected and, especially, attempts to aggregate data in order to generate more accurate results. This leads to an issue that has not been analyzed yet deeply in specialty literature or by legislators, respectively, the privacy concerns in case of profile building and aggregation of data for fraud identification purposes and responsibility of stakeholders in the identification of frauds in the context of their obligations under data protection legislation. This article comes as a building block in this direction of research, as it contains (i) an analysis of existing fraud detection methods and approaches, together with their impact from a data protection legislation perspective and (ii) an analysis of respondents’ views toward privacy in case of fraud identification in transactions based on a questionnaire in this respect having 425 respondents. Consequently, this article assists in bridging the gap between data protection legislation and implementation of fraud detection obligations under the law, as it provides recommendations for compliance with the latter legal obligation while also complying with data protection aspects. View Full-Text
Keywords: fraud detection; privacy; data protection; privacy by design; security by design; machine learning; data analytics; cybercrime fraud detection; privacy; data protection; privacy by design; security by design; machine learning; data analytics; cybercrime
Show Figures

Figure 1

MDPI and ACS Style

Găbudeanu, L.; Brici, I.; Mare, C.; Mihai, I.C.; Șcheau, M.C. Privacy Intrusiveness in Financial-Banking Fraud Detection. Risks 2021, 9, 104. https://0-doi-org.brum.beds.ac.uk/10.3390/risks9060104

AMA Style

Găbudeanu L, Brici I, Mare C, Mihai IC, Șcheau MC. Privacy Intrusiveness in Financial-Banking Fraud Detection. Risks. 2021; 9(6):104. https://0-doi-org.brum.beds.ac.uk/10.3390/risks9060104

Chicago/Turabian Style

Găbudeanu, Larisa, Iulia Brici, Codruța Mare, Ioan C. Mihai, and Mircea C. Șcheau 2021. "Privacy Intrusiveness in Financial-Banking Fraud Detection" Risks 9, no. 6: 104. https://0-doi-org.brum.beds.ac.uk/10.3390/risks9060104

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop