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Dian Anita Nuswantara
Universitas Negeri Surabaya
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Journal : Journal of Accounting Science

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Artificial Intelligence and Data Mining in Detecting Financial Statement Fraud: A Systematic Literature Review Anggi Putri; Nuswantara, Dian Anita
Journal of Accounting Science Vol. 9 No. 2 (2025): July
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jas.v9i2.2025

Abstract

General Background: Fraud in financial reporting significantly undermines stakeholder confidence and destabilises financial markets. Specific Background: The increasing complexity of financial data makes traditional fraud detection techniques inadequate, necessitating more sophisticated methods such as data mining and artificial intelligence (AI). Knowledge Gap: Despite the increasing adoption of AI in fraud detection, previous systematic literature reviews (SLRs) have generally focused narrowly on specific algorithms or data types, thus failing to provide a comprehensive assessment across multiple contexts. Objective: This study aims to critically evaluate the application of AI and data mining techniques in detecting financial statement fraud through a systematic literature review. Methods: A total of 30 peer-reviewed articles published between 2014 and 2024 were selected from Scopus, ScienceDirect, and Emerald databases using predefined inclusion-exclusion criteria and analysed narratively. Results: The review identified that supervised learning algorithms, specifically Support Vector Machine (SVM), Logistic Regression (LR), and XGBoost, were predominantly used, with XGBoost (96.94%) and LSTM (94.98%) showing the highest accuracy. Integration of financial and non-financial data improves detection stability. Novelty: In contrast to previous systematic reviews, this study offers a holistic synthesis covering algorithm types, structured and unstructured data, and diverse regional contexts. Implications: The findings highlight the transformative potential of AI in fraud detection and encourage further research on unsupervised learning and more in-depth utilisation of unstructured data
Co-Authors Adhityawati Kusumawardhani Aisyaturrahmi Ali Alnajar, Ali Elazumi Alnajar, Ali Elazumi Ali Alvin Rizani AMELIA SETYAWATI, AMELIA Anggi Putri aprilina susandini Aripratiwi, Ratna Anggraini Augy Ladyana Firstyanto Brian Adinata Budi Purwoko Cantika Sari Siregar Danis Maulia Daniswara, Endra Rasendriya Dewi Prastiwi Dhuwik Ratnasari Dita Rimbawati Dewi Djoewita, Djoewita Dr. Dewi Dwi Ariyanto Dwiarko Nugrohoseno Elfrida Ambarita Elfrida Ambarita, Elfrida Eni Wuryani Fanggidae, Apriana H.J. Fernanda Rizki Brianti Friyanto, Friyanto Girindratama, Muhammad Wisnu Girindratama HARIYATI Hariyati Hariyati Hariyati Hariyati Haryati Haryati Herning Indriastuti Ika Permatasari Imtizal Jauhara Kusuma Imtizal Jauhara Kusuma Insyirah Putikadea Irianti, Lingga Resvita Isnalita Kurniati, Fitrina Lidya Primta Surbakti Linda Oktaviani Lintang Venusita Loggar Bhilawa Mariana Marisa Intan Prawesti Merlyana Dwinda Yanthi Meylia Elizabeth Ranu Miftahul Jannah Mulyani, Heni Musyaffi, Ayatulloh Michael Nasution, Hafifah Ni Nyoman Alit Triani Norbertus Purnomolastu Nur Azizah Nurul Afifah Pujiono Pujiono Puspo Dewi Dirgantari Putri, Yeni Nor Diana Rahman, Iradah Ratih Kusumawati Raya Sulistyowati Rendra Arief Hidayat Rida Perwita Sari Rifda Fitrianty Rika Puspita Sari Rima Rifana Riusman Lase Rizal, Ach. Syaiful ROHMAWATI KUSUMANINGTIAS Ronald P.C. Fanggidae Ruben M. Nayve Jr Run, Pharatt Runn, Pharat Sakti, Maharani Evelyna Putri Sanaji Sari, Ramadhani Indah Sari, Wulan Iyhig Ratna Selfiah, Selfiah Serena, Rinasda Silalahi, Roubert Arsa Paringotan Siti Sundari Sri Setyo Iriani Sudarjo Sugangga, Amelia Sugangga, Fannie Sugangga, Rayyan Suharyoto, Suharyoto SUJARWANTO Syahar Banu, Syahar Tafonao, Aluiwaauri Tantini, Dewi Ulum, Nafi' Fahrur Warih Puspo Andjani Widi Hidayat Yoga Adi Prayogi Zalza Berlinda Pratiwi Zukhruf, Ratu Dintha Insyani