Comparison of The Effectiveness of Biometric Security Technology, Encryption, Ai Fraud Detection Preventing Fraud on Online Loan Applicatons - Rizqiani, Arinda Manar (Universitas Muhammadiyah Purwokerto, 2026)
The rapid growth of online lending services (peer to peer lending) in Indonesia as part of the financial technology (fintech) ecosystem has increased financial inclusion, but at the same time accompanied by a high risk of digital fraud and the rise of illegal platforms. The characteristics of fully digital services, minimal face-to-face interaction, and reliance on remote verification make online loan applications very vulnerable to various forms of fraud, such as identity theft, account abuse, synthetic identity, and loan stacking. This study aims to assess and compare the effectiveness of biometric security technology, encryption, and AI fraud detection in preventing fraud in online loan applications. The research method used is a literature review with a comparative descriptive approach to scientific articles, regulatory reports, and relevant fintech industry publications. The results of the study show that there is no single security technology that is completely effective when applied alone. Biometric technology has proven to be effective in the early stages of authentication to prevent identity misuse, encryption serves as a security foundation in protecting data confidentiality and integrity, while AI fraud detection demonstrates the most comprehensive effectiveness in detecting and preventing complex and dynamic fraud patterns. This study concludes that a multi-layer security approach that combines biometrics, encryption, and AI fraud detection is the most optimal strategy to minimize fraud risk, maintain operational efficiency, improve user comfort, and strengthen the trust and sustainability of the online lending industry in Indonesia.