CADM: Big Data to Limit Creative Accounting in Saudi-Listed Companies

• Autorzy: Bineid Maysoon , Beloff Natalia , White Martin , Khanina Anastasia

Identyfikatory

DOI

10.15439/2023F3888

• Języki publikacji: EN

Abstrakty

EN

Global financial scandals have demonstrated the harmful impact of creative accounting, a practice where managers creatively manipulate financial reports to conceal a company's actual performance and influence stakeholders' decision-making. Studies showed that Saudi-listed companies use it in preparing financial statements. Despite posing a significant risk to the Saudi financial market, it remains a challenge to detect it using ordinary auditing procedures. Big data analytics has provided useful applications in auditing, and recently, the employment of Deep Learning in fraud detection has delivered remarkably accurate results. Still, limited research has considered it in detecting creative accounting. This study proposes a novel framework using a hybrid learning approach. It suggests training on a simulated dataset of financial statements prepared (i.e., deliberately manipulated) based on financial statements available in the literature for supervised learning. It is then tested on real-world financial reports from the Saudi Open Data and Saudi Statistics. Our framework contributes to the literature with a new governing approach to limit creative accounting and improve financial reporting quality.

Słowa kluczowe

EN

creative accounting; Big Data; deep learning

PL

kreatywna księgowość; Big Data; głębokie uczenie się

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2023
• Tom: Vol. 35
• Strony: 103--110
• Opis fizyczny: Bibliogr. 72 poz., tab., il.

Twórcy

autor

Bineid Maysoon

• Department of IS and Technology University of Jeddah, SA Department of Informatics
• University of Sussex, Brighton. Falmer, BN1 9RH, UK

• https://orcid.org/0009-0007-4447-3706

autor

Beloff Natalia

• University of Sussex, Brighton. Falmer, BN1 9RH, UK

• https://orcid.org/0000-0002-8872-7786

autor

White Martin

• School of Business and Law University of Brighton Brighton, BN2 4NU, UK

• https://orcid.org/0000-0001-8686-2274

autor

Khanina Anastasia

• University of Sussex, Brighton. Falmer, BN1 9RH, UK

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Uwagi

1. Main Track Regular Papers

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