A taxonomy to guide research on the application of data mining to fraud detection in financial statement audits

Gray, Glen L.; Debreceny, Roger

doi:10.1016/j.accinf.2014.05.006

Cited by 97 publications

(41 citation statements)

References 22 publications

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“…Big data improves the efficiency of risk-based pricing and risk management while significantly alleviating information asymmetry problems. Also, it helps to verify and collect the data, predict credit risk status, and detect fraud [24,25,56]. Jin et al [44], [47], Peji [60], and Hajizadeh et al [28] identified that data mining technology plays vital roles in risk managing and fraud detection.…”

Section: Big Data Implications On Internet Finance and Value Creationmentioning

confidence: 99%

“…It also elaborates and interprets the risk analysis information comparatively faster than traditional systems. In addition, it also helps in detecting fraud [25,56] by reducing manual efforts by relating internal as well as external data in issues such as money laundering, credit card fraud, and so on. It also helps in enhancing computational efficiency, handling data storage, creating a visualization toolbox, and developing a sanity-check toolbox by enabling risk analysts to make initial data checks and develop a market-risk-specific remediation plan.…”

Section: Big Data In Managing Financial Servicesmentioning

confidence: 99%

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Current landscape and influence of big data on finance

2020

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In the age of technological innovation, various types of data are available with the advance of information technologies, and data is seen as one of the most valuable commodities in managing automation systems [13, 68]. In this sense, financial markets and technological evolution have become related to every human activity in the past few decades. Big data technology has become an integral part of the financial services industry and will continue to drive future innovation [12]. Financial innovations are also considered the fastest emerging issues in financial services. More specifically, they cover a variety of financial businesses such as online peer-to-peer lending, crowd-funding platforms, SME finance, wealth management and asset management platforms, trading management, crypto-currency, money/remittance transfer, mobile payments platforms, and so on. All of these services create thousands of pieces of data every day. Therefore,

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Section: Big Data Implications On Internet Finance and Value Creationmentioning

confidence: 99%

Section: Big Data In Managing Financial Servicesmentioning

confidence: 99%

Current landscape and influence of big data on finance

2020

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“…Kesediaan, kejujuran dan relevansi data Perusahaan pengguna jasa audit masih banyak memiliki kemampuan yang kurang baik dalam menyediakan data yang diinginkan oleh auditor, atau data yang disediakan oleh perusahaan masih memiliki banyak error/noise. Selain itu, kita tidak tahu sebatas apa data yang diberikan oleh perusahaan kepada auditor (Gray dan Debreceny, 2014). Meskipun data yang diberikan oleh perusahaan adalah data yang lengkap, auditor masih harus melakukan pengecekan terhadap kejujuran data yang telah diterima.…”

Section: Metode Penelitianunclassified

Potensi Artificial Intelligence (Ai) Menerbitkan Opini Auditor ?

Soeprajitno¹

2019

Jurnal Riset Akuntansi Dan Bisnis Airlangga

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The presence of Artificial Intelligence (AI) in the disruptive era is considered to be a solution for the inability of the audit to detect fraud and issue an audit opinion. The purpose of this study is to prove the potential of Artificial Intelligence (AI) to detect fraud and issue auditor opinion. This study uses the Theoretical Framework method and uses documentation techniques for previous research and by combining competencies and capabilities between the availability of big data, the use of data mining, Artificial Neural Network and involving the final analysis through the calculation of total irregularities obtained by using Fuzzy. The results of this paper reinforce the potential for the existence of Artificial Intelligence to be able to detect fraud, and publish audit opinions independently. The author hopes to provide a broader picture of the Artificial Intelligence framework to maximize its potential to help auditors detect and issue audit opinions.

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“…One major challenge is data availability, including relevance and integrity of data analysis (27). For many managers and organizations, they may not have the ability to capture data such as computer skills and knowledge, or data may contain noise and asymmetric information problem exists (28). Even if the data can be readily provided and the decision-makers are granted full access, they have to consider the integrity (27), completeness, ambiguity or quality of data.…”

Section: Big Data Analyticsmentioning

confidence: 99%