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CRAS‐CBR: Internal control risk assessment system using case‐based reasoning
Author(s) -
Hwang SungSik,
Shin Taeksoo,
Han Ingoo
Publication year - 2004
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/j.1468-0394.2004.00260.x
Subject(s) - audit , computer science , benchmark (surveying) , audit risk , control (management) , risk assessment , risk analysis (engineering) , accounting , artificial intelligence , computer security , business , geodesy , geography
Information technology and the Internet have been major drivers for changes in all aspects of business processes and activities. They have brought major changes to the financial statements audit environment as well, which in turn has required modifications in audit procedures. There exist certain difficulties, however, with current audit procedures especially for the assessment of the level of control risk. This assessment is primarily based on the auditors' professional judgment and experiences, not on objective rules or criteria. To overcome these difficulties, we propose a prototype decision support model named CRAS‐CBR using case‐based reasoning to support auditors in making their professional judgment on the assessment of the level of control risk of the general accounting system in the manufacturing industry. To validate the performance, we compare our proposed model with benchmark performances in terms of classification accuracy for the level of control risk. Our experimental results show that CRAS‐CBR outperforms a statistical model and staff auditor performance in average hit ratio.