{"id":"https://openalex.org/W1968433094","doi":"https://doi.org/10.2308/ajpt-50009","title":"Financial Statement Fraud Detection: An Analysis of Statistical and Machine Learning Algorithms","display_name":"Financial Statement Fraud Detection: An Analysis of Statistical and Machine Learning Algorithms","publication_year":2011,"publication_date":"2011-05-01","ids":{"openalex":"https://openalex.org/W1968433094","doi":"https://doi.org/10.2308/ajpt-50009","mag":"1968433094"},"language":"en","primary_location":{"id":"doi:10.2308/ajpt-50009","doi":"https://doi.org/10.2308/ajpt-50009","is_oa":false,"landing_page_url":"https://doi.org/10.2308/ajpt-50009","pdf_url":null,"source":{"id":"https://openalex.org/S75845752","display_name":"Auditing A Journal of Practice & Theory","issn_l":"0278-0380","issn":["0278-0380","1558-7991"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","fnege-2","jufo-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310316290","host_organization_name":"American Accounting Association","host_organization_lineage":["https://openalex.org/P4310316290"],"host_organization_lineage_names":["American Accounting Association"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AUDITING: A Journal of Practice & Theory","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2206572","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076247828","display_name":"Johan L. Perols","orcid":"https://orcid.org/0000-0001-5642-971X","observed_orcids":["https://orcid.org/0000-0001-5642-971X"]},"institutions":[{"id":"https://openalex.org/I160856358","display_name":"University of San Diego","ror":"https://ror.org/03jbbze48","country_code":"US","type":"education","lineage":["https://openalex.org/I160856358"]},{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Johan Perols","raw_affiliation_strings":["Editor's note: Accepted by Robert Knechel","Johan Perols is an Assistant Professor at the University of San Diego","This study is based on one of my three dissertation papers completed at the University of South Florida. I thank my dissertation co-chairs, Jacqueline Reck and Kaushal Chari, and committee members, Uday Murthy and Manish Agrawal. I am also grateful to Robert Knechel (associate editor), two anonymous reviewers, and Ann Dzuranin for their helpful suggestions. An earlier version of this paper was awarded the 2009 AAA Information System Section Outstanding Dissertation Award"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Editor's note: Accepted by Robert Knechel","institution_ids":[]},{"raw_affiliation_string":"Johan Perols is an Assistant Professor at the University of San Diego","institution_ids":["https://openalex.org/I160856358"]},{"raw_affiliation_string":"This study is based on one of my three dissertation papers completed at the University of South Florida. I thank my dissertation co-chairs, Jacqueline Reck and Kaushal Chari, and committee members, Uday Murthy and Manish Agrawal. I am also grateful to Robert Knechel (associate editor), two anonymous reviewers, and Ann Dzuranin for their helpful suggestions. An earlier version of this paper was awarded the 2009 AAA Information System Section Outstanding Dissertation Award","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076247828"],"corresponding_institution_ids":["https://openalex.org/I160856358","https://openalex.org/I2613432"],"apc_list":null,"apc_paid":null,"fwci":18.0912,"has_fulltext":false,"cited_by_count":396,"citation_normalized_percentile":{"value":0.98684531,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"30","issue":"2","first_page":"19","last_page":"50"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10081","display_name":"Auditing, Earnings Management, Governance","score":0.8130000233650208,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10081","display_name":"Auditing, Earnings Management, Governance","score":0.8130000233650208,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.06499999761581421,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13720","display_name":"Benford\u2019s Law and Fraud Detection","score":0.05460000038146973,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/financial-statement-fraud-detection","display_name":"financial statement fraud detection","score":0.921999990940094},{"id":"https://openalex.org/keywords/fraud-classification","display_name":"fraud classification","score":0.5099999904632568},{"id":"https://openalex.org/keywords/misclassification-cost","display_name":"misclassification cost","score":0.7760000228881836},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.8700000047683716},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":1.0},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.949999988079071},{"id":"https://openalex.org/keywords/bagging","display_name":"bagging","score":0.9629999995231628},{"id":"https://openalex.org/keywords/c4-5-decision-tree","display_name":"C4.5 decision tree","score":0.8920000195503235},{"id":"https://openalex.org/keywords/stacking-ensemble","display_name":"stacking ensemble","score":0.7950000166893005},{"id":"https://openalex.org/keywords/predictor-variable-selection","display_name":"predictor selection","score":0.6830000281333923},{"id":"https://openalex.org/keywords/auditor-switching","display_name":"auditor switching","score":0.8600000143051147},{"id":"https://openalex.org/keywords/discretionary-accruals","display_name":"discretionary accruals","score":0.9850000143051147},{"id":"https://openalex.org/keywords/big-4-auditors","display_name":"Big 4 auditors","score":0.9200000166893005},{"id":"https://openalex.org/keywords/accounts-receivable","display_name":"accounts receivable","score":0.9909999966621399},{"id":"https://openalex.org/keywords/labor-productivity","display_name":"labor productivity","score":0.7480000257492065}],"concepts":[{"id":"https://openalex.org/C2781027943","wikidata":"https://www.wikidata.org/wiki/Q192907","display_name":"Financial statement","level":3,"score":0.7049809694290161},{"id":"https://openalex.org/C202451310","wikidata":"https://www.wikidata.org/wiki/Q328554","display_name":"Accounts receivable","level":2,"score":0.6806483268737793},{"id":"https://openalex.org/C4577558","wikidata":"https://www.wikidata.org/wiki/Q384475","display_name":"Accrual","level":3,"score":0.6259136199951172},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.5918158292770386},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.527959942817688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4754709303379059},{"id":"https://openalex.org/C177235770","wikidata":"https://www.wikidata.org/wiki/Q2146785","display_name":"Revenue recognition","level":4,"score":0.47142308950424194},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4671330749988556},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4526228904724121},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4214269518852234},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.4203885793685913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3940923511981964},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3858943581581116},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3478327989578247},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.28524380922317505},{"id":"https://openalex.org/C2781426361","wikidata":"https://www.wikidata.org/wiki/Q5326940","display_name":"Earnings","level":2,"score":0.14731064438819885},{"id":"https://openalex.org/C544937707","wikidata":"https://www.wikidata.org/wiki/Q949180","display_name":"Financial accounting","level":3,"score":0.14011791348457336},{"id":"https://openalex.org/C163867264","wikidata":"https://www.wikidata.org/wiki/Q4672792","display_name":"Accounting information system","level":2,"score":0.11211764812469482}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2308/ajpt-50009","doi":"https://doi.org/10.2308/ajpt-50009","is_oa":false,"landing_page_url":"https://doi.org/10.2308/ajpt-50009","pdf_url":null,"source":{"id":"https://openalex.org/S75845752","display_name":"Auditing A Journal of Practice & Theory","issn_l":"0278-0380","issn":["0278-0380","1558-7991"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a-star","anvur-class-a","anvur-scientific","cwts-core","fnege-2","jufo-2","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310316290","host_organization_name":"American Accounting Association","host_organization_lineage":["https://openalex.org/P4310316290"],"host_organization_lineage_names":["American Accounting Association"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AUDITING: A Journal of Practice & Theory","raw_type":"journal-article"},{"id":"mag:3121491378","doi":null,"is_oa":true,"landing_page_url":"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2206572","pdf_url":null,"source":{"id":"https://openalex.org/S4210172589","display_name":"SSRN Electronic Journal","issn_l":"1556-5068","issn":["1556-5068"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1318003438","host_organization_name":"RELX Group (Netherlands)","host_organization_lineage":["https://openalex.org/I1318003438"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"SSRN Electronic Journal","raw_type":null}],"best_oa_location":{"id":"mag:3121491378","doi":null,"is_oa":true,"landing_page_url":"https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2206572","pdf_url":null,"source":{"id":"https://openalex.org/S4210172589","display_name":"SSRN Electronic Journal","issn_l":"1556-5068","issn":["1556-5068"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1318003438","host_organization_name":"RELX Group (Netherlands)","host_organization_lineage":["https://openalex.org/I1318003438"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"SSRN Electronic Journal","raw_type":null},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1496612019","https://openalex.org/W1512098439","https://openalex.org/W1524761913","https://openalex.org/W1534363098","https://openalex.org/W1543887412","https://openalex.org/W1570448133","https://openalex.org/W1572005155","https://openalex.org/W1766594731","https://openalex.org/W1965895350","https://openalex.org/W1966510486","https://openalex.org/W1995455337","https://openalex.org/W1999531150","https://openalex.org/W2000875084","https://openalex.org/W2029864452","https://openalex.org/W2040661907","https://openalex.org/W2057190074","https://openalex.org/W2061348311","https://openalex.org/W2063269836","https://openalex.org/W2068687206","https://openalex.org/W2079228007","https://openalex.org/W2085573882","https://openalex.org/W2109676405","https://openalex.org/W2115682519","https://openalex.org/W2125055259","https://openalex.org/W2127435698","https://openalex.org/W2136903812","https://openalex.org/W2148069037","https://openalex.org/W2148143831","https://openalex.org/W2160150610","https://openalex.org/W2161390635","https://openalex.org/W2163476003","https://openalex.org/W2167332641","https://openalex.org/W2170913656","https://openalex.org/W2257113089","https://openalex.org/W2268712472","https://openalex.org/W2905259885","https://openalex.org/W2912934387","https://openalex.org/W4212883601","https://openalex.org/W4230683138","https://openalex.org/W4235328403","https://openalex.org/W4285719527","https://openalex.org/W6680202767","https://openalex.org/W6930653985"],"related_works":["https://openalex.org/W3004295839","https://openalex.org/W4323315694","https://openalex.org/W4414327711","https://openalex.org/W3107954530","https://openalex.org/W4205480656","https://openalex.org/W7223066728","https://openalex.org/W4415649477","https://openalex.org/W2774065454","https://openalex.org/W4404612128","https://openalex.org/W7113662330"],"abstract_inverted_index":{"SUMMARY":[0],"This":[1],"study":[2,135],"compares":[3],"the":[4,67,139,150],"performance":[5],"of":[6,22,27,71,129],"six":[7,76],"popular":[8],"statistical":[9],"and":[10,25,41,55,80,101,112,118],"machine":[11],"learning":[12],"models":[13],"in":[14,63,133,149],"detecting":[15],"financial":[16,108],"statement":[17,109],"fraud":[18,28,110,122,130],"under":[19],"different":[20,83],"assumptions":[21],"misclassification":[23],"costs":[24],"ratios":[26],"firms":[29],"to":[30,48,120],"nonfraud":[31],"firms.":[32],"The":[33,57],"results":[34,58],"show,":[35],"somewhat":[36],"surprisingly,":[37],"that":[38],"logistic":[39],"regression":[40],"support":[42],"vector":[43],"machines":[44],"perform":[45],"well":[46],"relative":[47],"an":[49],"artificial":[50],"neural":[51],"network,":[52],"bagging,":[53],"C4.5,":[54],"stacking.":[56],"also":[59],"reveal":[60],"some":[61],"diversity":[62],"predictors":[64,73],"used":[65,81,115,132],"across":[66],"classification":[68,84],"algorithms.":[69],"Out":[70],"42":[72],"examined,":[74],"only":[75],"are":[77,147],"consistently":[78],"selected":[79],"by":[82,116],"algorithms:":[85],"auditor":[86],"turnover,":[87],"total":[88],"discretionary":[89],"accruals,":[90],"Big":[91],"4":[92],"auditor,":[93],"accounts":[94],"receivable,":[95],"meeting":[96],"or":[97],"beating":[98],"analyst":[99],"forecasts,":[100],"unexpected":[102],"employee":[103],"productivity.":[104],"These":[105],"findings":[106],"extend":[107],"research":[111],"can":[113],"be":[114],"practitioners":[117],"regulators":[119],"improve":[121],"risk":[123],"models.":[124],"Data":[125],"Availability:":[126],"A":[127],"list":[128],"companies":[131],"this":[134],"is":[136],"available":[137],"from":[138],"author":[140],"upon":[141],"request.":[142],"All":[143],"other":[144],"data":[145],"sources":[146],"described":[148],"text.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":56},{"year":2025,"cited_by_count":48},{"year":2024,"cited_by_count":51},{"year":2023,"cited_by_count":45},{"year":2022,"cited_by_count":41},{"year":2021,"cited_by_count":33},{"year":2020,"cited_by_count":38},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":14},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":6}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2016-06-24T00:00:00"}