Evaluasi SWOT Penerapan Artificial Intelligence dalam Audit Forensik dan Pencegahan Fraud Perbankan
-
Azwansyah Habibie
*
Universitas Harapan Medan, Medan,
Indonesia
- Selva Temalagi Universitas Pattimura, Ambon, Indonesia
- Suginam Suginam Universitas Harapan Medan, Medan, Indonesia
- Ayu Iryanti binti Azni Politeknik Tuanku Syed Sirajuddin, Perlis, Malaysia (*) Corresponding Author
Abstract
This study aims to evaluate the application of artificial intelligence (AI) in forensic auditing and banking fraud prevention using SWOT analysis. The main issue addressed is the imbalance between AI’s potential in detecting and preventing fraud and the limitations of human expertise, regulatory frameworks, and security risks. The results show that AI demonstrates strong capabilities in fraud detection efficiency and audit cost reduction, but weaknesses remain in auditor literacy and algorithmic transparency. Opportunities are driven by global regulatory support and collaboration with fintech, while threats arise from cyberattacks and the potential misuse of AI by fraudsters. The novelty of this study lies in the integration of SWOT analysis with measurable implementation indicators that can empirically assess the readiness and effectiveness of AI adoption in forensic auditing. This research contributes to the theoretical development of AI-based forensic auditing and provides practical implications for banking institutions to formulate more transparent, secure, and adaptive AI implementation strategies.
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