Fraud detection using fraud triangle risk factors
The objective of this study is to identify the financial statement fraud factors and rank the relative importance. First, this study reviews the previous studies to identify the possible fraud indicators. Expert questionnaires are distributed next. After questionnaires are collected, Lawshe’s approa...
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| Veröffentlicht in: | Information systems frontiers 2017-12, Vol.19 (6), p.1343-1356 |
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| creator | Huang, Shaio Yan Lin, Chi-Chen Chiu, An-An Yen, David C. |
| description | The objective of this study is to identify the financial statement fraud factors and rank the relative importance. First, this study reviews the previous studies to identify the possible fraud indicators. Expert questionnaires are distributed next. After questionnaires are collected, Lawshe’s approach is employed to eliminate these factors whose CVR (content validity ratio) values do not meet the criteria. Further, the remaining 32 factors are reviewed by experts to be the measurements suitable for the assessment of fraud detection. The Analytic Hierarchy Process (AHP) is utilized to determine the relative weights of the individual items. The result of AHP shows that the most important dimension is Pressure/Incentive and the least one is Attitude/rationalization. In addition, the top five important measurements are “Poor performance”, “The need for external financing”, “Financial distress”, “Insufficient board oversight”, and “Competition or market saturation”. The result provides a significant advantage to auditors and managers in enhancing the efficiency of fraud detection and critical evaluation. |
| doi_str_mv | 10.1007/s10796-016-9647-9 |
| format | Article |
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First, this study reviews the previous studies to identify the possible fraud indicators. Expert questionnaires are distributed next. After questionnaires are collected, Lawshe’s approach is employed to eliminate these factors whose CVR (content validity ratio) values do not meet the criteria. Further, the remaining 32 factors are reviewed by experts to be the measurements suitable for the assessment of fraud detection. The Analytic Hierarchy Process (AHP) is utilized to determine the relative weights of the individual items. The result of AHP shows that the most important dimension is Pressure/Incentive and the least one is Attitude/rationalization. In addition, the top five important measurements are “Poor performance”, “The need for external financing”, “Financial distress”, “Insufficient board oversight”, and “Competition or market saturation”. The result provides a significant advantage to auditors and managers in enhancing the efficiency of fraud detection and critical evaluation.</description><identifier>ISSN: 1387-3326</identifier><identifier>EISSN: 1572-9419</identifier><identifier>DOI: 10.1007/s10796-016-9647-9</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Analytic hierarchy process ; Business and Management ; Control ; Fraud ; Fraud prevention ; Hierarchies ; Information systems ; IT in Business ; Management of Computing and Information Systems ; Operations Research/Decision Theory ; Questionnaires ; Risk analysis ; Risk factors ; Systems Theory</subject><ispartof>Information systems frontiers, 2017-12, Vol.19 (6), p.1343-1356</ispartof><rights>Springer Science+Business Media New York 2016</rights><rights>Information Systems Frontiers is a copyright of Springer, (2016). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-a814a20a2cbab3012f132b3ad57b80e6ce975228b62581e1d9f4aaaca9997f1d3</citedby><cites>FETCH-LOGICAL-c316t-a814a20a2cbab3012f132b3ad57b80e6ce975228b62581e1d9f4aaaca9997f1d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10796-016-9647-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10796-016-9647-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Huang, Shaio Yan</creatorcontrib><creatorcontrib>Lin, Chi-Chen</creatorcontrib><creatorcontrib>Chiu, An-An</creatorcontrib><creatorcontrib>Yen, David C.</creatorcontrib><title>Fraud detection using fraud triangle risk factors</title><title>Information systems frontiers</title><addtitle>Inf Syst Front</addtitle><description>The objective of this study is to identify the financial statement fraud factors and rank the relative importance. First, this study reviews the previous studies to identify the possible fraud indicators. Expert questionnaires are distributed next. After questionnaires are collected, Lawshe’s approach is employed to eliminate these factors whose CVR (content validity ratio) values do not meet the criteria. Further, the remaining 32 factors are reviewed by experts to be the measurements suitable for the assessment of fraud detection. The Analytic Hierarchy Process (AHP) is utilized to determine the relative weights of the individual items. The result of AHP shows that the most important dimension is Pressure/Incentive and the least one is Attitude/rationalization. In addition, the top five important measurements are “Poor performance”, “The need for external financing”, “Financial distress”, “Insufficient board oversight”, and “Competition or market saturation”. The result provides a significant advantage to auditors and managers in enhancing the efficiency of fraud detection and critical evaluation.</description><subject>Analytic hierarchy process</subject><subject>Business and Management</subject><subject>Control</subject><subject>Fraud</subject><subject>Fraud prevention</subject><subject>Hierarchies</subject><subject>Information systems</subject><subject>IT in Business</subject><subject>Management of Computing and Information Systems</subject><subject>Operations Research/Decision Theory</subject><subject>Questionnaires</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Systems Theory</subject><issn>1387-3326</issn><issn>1572-9419</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kD1PwzAQhi0EEqXwA9giMRt8duKPEVUUkCqxwGxdHLtKKUmxnYF_j0sYWJjudHqeO91LyDWwW2BM3SVgykjKQFIja0XNCVlAozg1NZjT0gutqBBcnpOLlHasgFw1CwLriFNXdT57l_txqKbUD9sq_Exz7HHY7n0V-_ReBXR5jOmSnAXcJ3_1W5fkbf3wunqim5fH59X9hjoBMlPUUCNnyF2LrWDAAwjeCuwa1WrmpfNGNZzrVvJGg4fOhBoRHRpjVIBOLMnNvPcQx8_Jp2x34xSHctKCkcC4LnahYKZcHFOKPthD7D8wfllg9piMnZOx5WF7TMaa4vDZSYUdtj7-2fyv9A3EfGVt</recordid><startdate>20171201</startdate><enddate>20171201</enddate><creator>Huang, Shaio Yan</creator><creator>Lin, Chi-Chen</creator><creator>Chiu, An-An</creator><creator>Yen, David C.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CNYFK</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M1O</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20171201</creationdate><title>Fraud detection using fraud triangle risk factors</title><author>Huang, Shaio Yan ; Lin, Chi-Chen ; Chiu, An-An ; Yen, David C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-a814a20a2cbab3012f132b3ad57b80e6ce975228b62581e1d9f4aaaca9997f1d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Analytic hierarchy process</topic><topic>Business and Management</topic><topic>Control</topic><topic>Fraud</topic><topic>Fraud prevention</topic><topic>Hierarchies</topic><topic>Information systems</topic><topic>IT in Business</topic><topic>Management of Computing and Information Systems</topic><topic>Operations Research/Decision Theory</topic><topic>Questionnaires</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Systems Theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huang, Shaio Yan</creatorcontrib><creatorcontrib>Lin, Chi-Chen</creatorcontrib><creatorcontrib>Chiu, An-An</creatorcontrib><creatorcontrib>Yen, David C.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Complete</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Library & Information Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Library Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>Information systems frontiers</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huang, Shaio Yan</au><au>Lin, Chi-Chen</au><au>Chiu, An-An</au><au>Yen, David C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fraud detection using fraud triangle risk factors</atitle><jtitle>Information systems frontiers</jtitle><stitle>Inf Syst Front</stitle><date>2017-12-01</date><risdate>2017</risdate><volume>19</volume><issue>6</issue><spage>1343</spage><epage>1356</epage><pages>1343-1356</pages><issn>1387-3326</issn><eissn>1572-9419</eissn><abstract>The objective of this study is to identify the financial statement fraud factors and rank the relative importance. First, this study reviews the previous studies to identify the possible fraud indicators. Expert questionnaires are distributed next. After questionnaires are collected, Lawshe’s approach is employed to eliminate these factors whose CVR (content validity ratio) values do not meet the criteria. Further, the remaining 32 factors are reviewed by experts to be the measurements suitable for the assessment of fraud detection. The Analytic Hierarchy Process (AHP) is utilized to determine the relative weights of the individual items. The result of AHP shows that the most important dimension is Pressure/Incentive and the least one is Attitude/rationalization. In addition, the top five important measurements are “Poor performance”, “The need for external financing”, “Financial distress”, “Insufficient board oversight”, and “Competition or market saturation”. The result provides a significant advantage to auditors and managers in enhancing the efficiency of fraud detection and critical evaluation.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10796-016-9647-9</doi><tpages>14</tpages></addata></record> |
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| subjects | Analytic hierarchy process Business and Management Control Fraud Fraud prevention Hierarchies Information systems IT in Business Management of Computing and Information Systems Operations Research/Decision Theory Questionnaires Risk analysis Risk factors Systems Theory |
| title | Fraud detection using fraud triangle risk factors |
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