Dampak Artificial Intelligence terhadap Kualitas Audit dan Efisiensi Deteksi Fraud: A Systematic Literature Review
DOI:
https://doi.org/10.61104/alz.v4i2.5674Keywords:
Artificial Intelligence, Deteksi Fraud, Kecerdasan Buatan, Kualitas Audit.Abstract
Perkembangan kecerdasan buatan (Artificial Intelligence/AI) yang pesat telah mendorong transformasi mendasar dalam praktik audit keuangan, khususnya dalam peningkatan kualitas audit dan efisiensi deteksi fraud. Penelitian ini bertujuan untuk mengidentifikasi dampak implementasi AI terhadap kualitas audit, mengevaluasi efektivitasnya dalam deteksi fraud, serta memetakan tantangan dan implikasi etis dari adopsi teknologi tersebut. Metode yang digunakan adalah Systematic Literature Review (SLR) dengan protokol PRISMA, yang mensintesis 12 artikel ilmiah bereputasi dari basis data Scopus, Google Scholar, dan Web of Science yang diterbitkan pada periode 2022-2026. Hasil penelitian menunjukkan bahwa teknologi AI berbasis machine learning, deep learning, dan Artificial Neural Network secara konsisten mampu meningkatkan akurasi, memperluas cakupan pemeriksaan, serta mendeteksi anomali transaksi keuangan secara real-time. Kualitas audit meningkat signifikan melalui otomatisasi prosedur berulang dan penguatan keandalan bukti audit. Tetapi efektivitas implementasi AI sangat bergantung pada sinergi antara kompetensi digital auditor, kualitas data, kesiapan infrastruktur teknologi, dan kerangka etika yang memadai. Transparansi algoritma dan kesenjangan kompetensi sumber daya manusia menjadi tantangan utama yang perlu diatasi secara sistematis. Penelitian ini memberikan kontribusi bagi pengembangan kerangka audit digital yang akuntabel dan berkelanjutan bagi auditor, regulator, dan akademisi.
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