Addressing the Exception Prioritization Problem in Continuous Auditing Systems With Thresholding

21102 6 112262 2 338988 document 112262 Intelligent Sys in Account - 2025 - Svanberg - Addressing the Exception Prioritization Problem in Continuous Auditing.pdf application/pdf 6ee054e3af26e8f0bc1dcbb0171f6f47 MD5 676295 2026-01-07 10:11:24 https://pure.iiasa.ac.at/id/eprint/21102/1/Intelligent%20Sys%20in%20Account%20-%202025%20-%20Svanberg%20-%20Addressing%20the%20Exception%20Prioritization%20Problem%20in%20Continuous%20Auditing.pdf 21102 1 1 application/pdf text en public cc_by_nc_4

Intelligent Sys in Account - 2025 - Svanberg - Addressing the Exception Prioritization Problem in Continuous Auditing.pdf

published 112285 2 339026 document 112285 lightbox.jpg image/png a09cbe62bbd2885f9db26bc308cd7cbe MD5 57774 2026-01-07 10:21:28 https://pure.iiasa.ac.at/id/eprint/21102/2/lightbox.jpg 21102 2 2 image/png other Thumbnails conversion from text to thumbnail_lightbox en public

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/112262 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/112262 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/112262 archive 353 disk0/00/02/11/02 2026-01-07 10:12:34 2026-01-07 10:12:34 2026-01-07 10:12:34 article show Svanberg J. Öhman P. Samsten I. Neidermeyer P.E. Rana T. Danielson M. 9381 Addressing the Exception Prioritization Problem in Continuous Auditing Systems With Thresholding pub ASA CAT Continuous auditing research has grappled with the challenge of managing the abundance of detected exceptions in internal audit applications for the past 30 years. A key issue in continuous auditing involves the uncontrolled proliferation of exceptions, where the sheer volume makes manual follow‐up impractical, undermining the viability of the technology. The root cause of this problem is the combination of strong class imbalance and the predominant rule‐based systems design. Prior investigations have attempted ad hoc remedies like introducing additional layers to prioritize the most suspicious exceptions or aggregating data. Currently, there is no universal method to address this prioritization challenge, leaving internal auditors without a means to focus specifically on exceptions most likely to represent genuine faults. Our research explores the origin of this prioritization dilemma and proposes a systems design that can deal appropriately with class imbalance. This solution allows full control of the exception volume by a simple approach in machine learning called thresholding and combined with methods to interpret the output of a continuous auditing system our design effectively focuses the internal auditors' attention on the most significant exceptions. We discuss the implications of thresholding for practice and the literature. 2025-12-10 published doi:10.1002/isaf.70022 3245 public Intelligent Systems in Accounting, Finance and Management 32 4 e70022 TRUE Wiley info:eu-repo/semantics/article