A stochastic model to quantify and optimize the impact of operational risks on corporate sustainability using monte carlo simulation

• Autorzy: Bravo-Sepúlveda Mariana , Wilke Daniel Nico , Isaza Cuervo Felipe , Polanco Jorge-Andrés

Identyfikatory

DOI

10.17512/pjms.2023.28.2.04

Warianty tytułu

PL

Model stochastyczny kwalifikacji i optymalizacji wpływu ryzyka operacyjnego na zrównoważony rozwój korporacyjny z wykorzystaniem symulacji Monte Carlo

• Języki publikacji: EN

Abstrakty

EN

Operational risk has been widely studied, and international guidelines provide procedures for the correct management of operational risk; however, this has not been studied from a corporate sustainability point of view. Therefore, this work seeks to find a way to model and optimize the impact of operational risks on corporate sustainability. The methodology used is based on the assignment of two distribution functions for the creation of a probabilistic model that allows quantifying the probability of occurrence (frequency) and the expected monetary impact (severity) on the sustainability variables (environmental, social, and economic). The result is a statistical convolution through Monte Carlo simulation, which makes it possible to quantify aggregate losses to finally make an optimization process of the variables and estimate the financial impact. Therefore, this study extends the literature on risk quantification, proposing a stochastic model that quantifies and optimizes the operational risks that are related to corporate sustainability. The proposed model offers a practical way to quantify operational risks related to corporate sustainability while also being flexible, as it does not require historical information and can be used with data collected from the company based on the proposed probability distributions. Finally, the proposed model has three limitations: the distribution functions, use of Solver (Excel), and exclusion of some risk management strategies, which future research can consider.

PL

Ryzyko operacyjne zostało szeroko zbadane, a międzynarodowe wytyczne dostarczają procedur do prawidłowego zarządzania ryzykiem operacyjnym; jednakże nie badano tego z punktu widzenia zrównoważonego rozwoju przedsiębiorstwa. Dlatego też niniejsza praca ma na celu znalezienie sposobu modelowania i optymalizacji wpływu ryzyka operacyjnego na zrównoważony rozwój przedsiębiorstwa. Zastosowana metodologia opiera się na przypisaniu dwóch funkcji rozkładu w celu stworzenia modelu probabilistycznego, który pozwala kwantyfikować prawdopodobieństwo wystąpienia (częstotliwość) i oczekiwany monetarny wpływ (ciężkość) na zmienne zrównoważone (środowiskowe, społeczne i ekonomiczne). Rezultatem jest statystyczna konwolucja poprzez symulację Monte Carlo, który umożliwia ilościowe określenie zagregowanych strat, aby ostatecznie przeprowadzić proces optymalizacji zmiennych i oszacować wpływ finansowy. Dlatego też niniejsze badanie poszerza literaturę w obszarze kwantyfikacji ryzyka, proponując model stochastyczny, który kwantyfikuje i optymalizuje ryzyko operacyjne związane ze zrównoważonym rozwojem przedsiębiorstwa. Proponowany model oferuje praktyczny sposób ilościowego określenia ryzyk operacyjnych związanych ze zrównoważonym rozwojem przedsiębiorstwa, a jednocześnie jest elastyczny, ponieważ nie wymaga informacji historycznych i może być stosowany w połączeniu z danymi zebranymi z przedsiębiorstwa w oparciu o proponowane rozkłady prawdopodobieństwa. Wreszcie proponowany model ma trzy ograniczenia: funkcje rozkładu, użycie Solvera (Excel) i wykluczenie niektórych strategii zarządzania ryzykiem, które mogą zostać uwzględnione w przyszłych badaniach.

Słowa kluczowe

EN

operational risk; sustainability; Monte Carlo simulation; optimization

PL

ryzyko operacyjne; rozwój zrównoważony; symulacja Monte Carlo; optymalizacja

• Wydawca: Czestochowa University of Technology
• Czasopismo: Polish Journal of Management Studies
• Rocznik: 2023
• Tom: Vol. 28, No. 2
• Strony: 59--75
• Opis fizyczny: Bibliogr. 58 poz., rys.

Twórcy

autor

Bravo-Sepúlveda Mariana

• Faculty of Economic and Administrative Sciences, Universidad de Medellín, Antioquia, Colombia

• https://orcid.org/0000-0002-4935-1667

autor

Wilke Daniel Nico

• Faculty of Mechanical Engineering, University of Pretoria, Pretoria, South Africa

• https://orcid.org/0000-0002-8718-330X

autor

Isaza Cuervo Felipe

• Universidad de Medellin, Antioquia, Colombia

• https://orcid.org/0000-0002-3088-9264

autor

Polanco Jorge-Andrés

• Faculty of Engineering, Universidad de Medellín, Antioquia, Colombia

• https://orcid.org/000-0002-3469-1685

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).