The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network
碩士 === 國立臺灣大學 === 會計學研究所 === 84 === To express proper audit opinion, auditors to a large extent must rely on their professional judgment while collecting and evaluating audit evidences. Yet, as judgment exercised in other professions, audit judgment itsel...
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ndltd-TW-084NTU003850152016-07-13T04:10:50Z http://ndltd.ncl.edu.tw/handle/51247972721150876874 The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network 審計人員內部控制判斷行為研究─類神經網路之應用 Wu,Meng-Da 吳孟達 碩士 國立臺灣大學 會計學研究所 84 To express proper audit opinion, auditors to a large extent must rely on their professional judgment while collecting and evaluating audit evidences. Yet, as judgment exercised in other professions, audit judgment itself lacks clear and objective criteria. Its process still remains largely unknown. Therefore, behavioral accounting studies often selected audit judgment as research topics and applied statistical techniques to analyze auditors'' judgment policy. This study, using neural net as the tool, attempts to capture the internal rules employed by auditors as they try to form judgment, and compares the judgment policy captured through neural net with the results of previous studies. This study survey 42 auditors in Taiwan''s big 6 CPA firms using a fractional factorial design of simulated cases questionnaires. Each case is distinct on variational combination of six important internal control factors in purchasing cycle. Auditors are asked to express their judgment about the strength of internal control of each case. We then use these data as our learning and testing cases for back- propagation neural net to capture auditor''s decision policy. We find that network model with an architecture of one hidden layer and three processing elements in hidden layer has the best prediction capability. Moreover, if the hidden layer is removed, the net model can not converge. This means that variables have interactive effects and representing auditors'' judgment policy by a linear model will result in significant prediction error. By analyzing the significance of these six cues, we find that auditors regard segregation of duties as the most important factor while payment control is second. With respect to prediction capability, the best model has a 88.68% accuracy rate when applied to the test cases. Chen,Kuo-Tay 陳國泰 1996 學位論文 ; thesis 83 zh-TW |
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碩士 === 國立臺灣大學 === 會計學研究所 === 84 === To express proper audit opinion, auditors to a large extent
must rely on their professional judgment while collecting and
evaluating audit evidences. Yet, as judgment exercised in other
professions, audit judgment itself lacks clear and objective
criteria. Its process still remains largely unknown. Therefore,
behavioral accounting studies often selected audit judgment as
research topics and applied statistical techniques to analyze
auditors'' judgment policy. This study, using neural net as the
tool, attempts to capture the internal rules employed by
auditors as they try to form judgment, and compares the
judgment policy captured through neural net with the results of
previous studies. This study survey 42 auditors in Taiwan''s big
6 CPA firms using a fractional factorial design of simulated
cases questionnaires. Each case is distinct on variational
combination of six important internal control factors in
purchasing cycle. Auditors are asked to express their judgment
about the strength of internal control of each case. We then
use these data as our learning and testing cases for back-
propagation neural net to capture auditor''s decision policy. We
find that network model with an architecture of one hidden
layer and three processing elements in hidden layer has the
best prediction capability. Moreover, if the hidden layer is
removed, the net model can not converge. This means that
variables have interactive effects and representing auditors''
judgment policy by a linear model will result in significant
prediction error. By analyzing the significance of these six
cues, we find that auditors regard segregation of duties as the
most important factor while payment control is second. With
respect to prediction capability, the best model has a 88.68%
accuracy rate when applied to the test cases.
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author2 |
Chen,Kuo-Tay |
author_facet |
Chen,Kuo-Tay Wu,Meng-Da 吳孟達 |
author |
Wu,Meng-Da 吳孟達 |
spellingShingle |
Wu,Meng-Da 吳孟達 The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network |
author_sort |
Wu,Meng-Da |
title |
The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network |
title_short |
The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network |
title_full |
The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network |
title_fullStr |
The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network |
title_full_unstemmed |
The Study on Auditor''s Internal Control Judgment Behavior - An Application of Neural Network |
title_sort |
study on auditor''s internal control judgment behavior - an application of neural network |
publishDate |
1996 |
url |
http://ndltd.ncl.edu.tw/handle/51247972721150876874 |
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