Development of a multi-objectives integer programming model for allocation of anti-fraud capacities during cyberfraud mitigation

Purpose This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisat...

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Vydáno v:Journal of financial crime Ročník 30; číslo 6; s. 1720 - 1735
Hlavní autoři: Akinbowale, Oluwatoyin Esther, Klingelhöfer, Heinz Eckart, Zerihun, Mulatu Fekadu
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Emerald Publishing Limited 01.12.2023
Emerald Group Publishing Limited
Témata:
Accountants
Accounting
Audit committees
Banking
Banking industry
Cybercrime
Decision makers
Decision making
Feasibility
Financial institutions
Fraud
Genetics
Grammatical aspect
Human resources
Integer programming
Mitigation
Objectives
Prone
Resource allocation
Suitability
South Africa
Pareto front
Optimum solution
GA solver
MOIP model
Cyberfraud
ISSN:1359-0790, 1359-0790, 1758-7239
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Shrnutí:Purpose This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots. Design/methodology/approach From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints. Findings The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives. Practical implications The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources. Originality/value The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.
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ISSN:1359-0790
1359-0790
1758-7239
DOI:10.1108/JFC-10-2022-0245