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We further categorize the related work along four dimensions that can help highlight the peculiarities and challenges of the domain. Specifically, we group the related work based on (a) the input features used by each method, (b) the sources providing the labels of the data, (c) the evaluation approaches used to confirm the validity of the methods, and (d) the machine learning methods themselves. This categorization facilitates a technical overview of risk detection methods, revealing common patterns, methodologies, significant challenges, and opportunities for further research in the field.<\/jats:p>","DOI":"10.1145\/3723157","type":"journal-article","created":{"date-parts":[[2025,3,12]],"date-time":"2025-03-12T11:30:31Z","timestamp":1741779031000},"page":"1-37","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Machine Learning for Identifying Risk in Financial Statements: A Survey"],"prefix":"10.1145","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2417-3307","authenticated-orcid":false,"given":"Elias","family":"Zavitsanos","sequence":"first","affiliation":[{"name":"Institute of Informatics and Telecommunications, NCSR Demokritos, Athena, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0478-0022","authenticated-orcid":false,"given":"Eirini","family":"Spyropoulou","sequence":"additional","affiliation":[{"name":"Institute of Informatics and Telecommunications, National Centre for Scientific Research-Demokritos, Athena, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2459-589X","authenticated-orcid":false,"given":"George","family":"Giannakopoulos","sequence":"additional","affiliation":[{"name":"Institute of Informatics and Telecommunications, National Centre for Scientific Research-Demokritos, Athena, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9629-2367","authenticated-orcid":false,"given":"Georgios","family":"Paliouras","sequence":"additional","affiliation":[{"name":"Institute of Informatics and Telecommunications, National Centre for Scientific Research-Demokritos, Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,4,3]]},"reference":[{"issue":"4","key":"e_1_3_4_2_2","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.2307\/41703508","article-title":"Metafraud: A meta-learning framework for detecting financial fraud","volume":"36","author":"Abbasi Ahmed","year":"2012","unstructured":"Ahmed Abbasi, Conan Albrecht, Anthony Vance, and James Hansen. 2012. 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