Comparison of The Effectiveness of Biometric Security Technology, Encryption, Ai Fraud  Detection Preventing Fraud on Online Loan Applicatons

Arinda Manar  Rizqiani

doi:10.30595/jesh.v4i1.464

Authors

Arinda Manar Rizqiani Universitas Muhammadiyah Purwokerto

DOI:

https://doi.org/10.30595/jesh.v4i1.464

Keywords:

Fintech, Online lending, Digital security, Fraud prevention, AI fraud detection

Abstract

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.

References

Arifin, S. (2025). Challenges and Opportunities Faced by Banks in Facing the Digital Financial Era. Persya: Journal of Sharia Banking, 3(1), 27-33.

Indonesian Internet Service Providers Association. (2025). APJII Internet Survey 2025. APJII survey. https://survei.apjii.or.id/

Ahmad, A. S. (2023). Application of big data and artificial intelligence in strengthening fraud analytics and cybersecurity resilience in global financial markets. International Journal of Advanced Cybersecurity Systems, Technologies, and Applications, 7(12), 11-23.

Ali, G., Mijwil, M. M., Buruga, B. A., & Abotaleb, M. (2024). A comprehensive review on cybersecurity issues and their mitigation measures in FinTech. Iraqi Journal for Computer Science and Mathematics, 5(3), 12.

Aziza, N., & Wardhani, D. F. (2025). Mobile Banking Application Security Evaluation: Threats, Protection and Case Studies on Digital Banking Systems. Scientific Journal of Information Technology and Robotics, 7(1), 11–22.

Bello, O. A., Ogundipe, A., Mohammed, D., Adebola, F., & Alonge, O. A. (2023). AI-driven approaches for real-time fraud detection in US financial transactions: Challenges and opportunities. European Journal of Computer Science and Information Technology, 11(6), 84–102.

Bodorin, B. E., & Ciobanu, E. (2026). AI, security, and trust in the digital wallet: Evidence from current Romanian FinTech users. International Journal of Financial Studies, 14(1), 1. https://doi.org/10.3390/ijfs14010001

Caseba, F. L., & Dewayanto, T. (2024). The application of artificial intelligence, big data, and blockchain in fintech payments to computer fraud risk: A systematic literature review. Diponegoro Journal of Accounting, 13(3).

Devaraj, S. M. (2024). Next-Generation Fraud Detection: A Technical Analysis of AI Implementation in Financial Services Security. International Journal for Multidisciplinary Research (IJFMR), 6(6).

Estherina, I. (2025, October 12). Indonesia's OJK shuts down 1,556 illegal loan apps and 284 investment scams.

Asia-Pacific Solidarity Network. https://www.asi A-Pacific C-solidarity.net/news/202 5-1 0-12/IndonesiaSOJKshut S-Dow N-155 6-Long L-Loa N-App S- AN, D-28, 4-Investmen, T-scams.htm L

Fadlilah, R. (2025). Online Loans in Financial Services Authority Regulation Number 40 of 2024 concerning Information Technology-Based Joint Funding Services from the Perspective of Maqāṣid Sharīʿah (Doctoral dissertation, IAIN Ponorogo).

Firdaus, S. E., & Baidhowi, B. (2025). Digitalization of Banking and MSME Access: Legal Opportunities and Challenges. Academic Journal of Economics and Management, 2(2), 109–113.

Habbal, A., Ali, M. K., & Abuzaraida, M. A. (2024). Artificial Intelligence Trust, risk and security management (AI trism): Frameworks, applications, challenges and future research directions. Expert Systems with Applications, 240, 122442.

International Trade Administration. (2025, November 17). Indonesia — Financial Services (Financial Technology). U.S. Department of Commerce. https://www.trade.gov/countr y-commercia l-guides/indonesiaafinancialservice s-financia l-technolog y

Isaac, J. (2025, 12 August). Association raises alarm over massive circulation of illegal online loans. Indonesia Business Post. https://indonesiabusinesspost.com/4974/market S-an D-finance/associationraise s-alar m-ove r-massiv e-circulatio n-o f-illega l-onlin eloans

Jannah, M., Hidayat, M. F., Agustiyyani, M., Buana, P. W., & Purwani, F. (2024). Implementation of Biometric Authentication to Improve Security and Privacy of Digital Wallet Users. Journal of Scientech Research and Development, 6(2), 531–539.

Jameaba, M. S. (2022). Digitalization, Emerging Technologies, and Financial Stability: Challenges and Opportunities for the Indonesian Banking Industry and Beyond. DOI: https://doi. org/10.32388/CSTTYQ, 2.

Kusuma, A. C., Lois, A., Thessaloniki, L., Darosyifa, T., & Evelin, A. (2025). Legal Implications for the Stability of the Digital Finance Industry and Post-Case Supervision of PT Investree Radhika Jaya. Causa: Journal of Law and Citizenship, 16(1), 1151–1160.

Kumar, P. (2024). AI-Powered Fraud Prevention in Digital Payment Ecosystems: Leveraging Machine Learning for Real-Time Anomaly Detection and Risk Mitigation. Journal of Information Systems Engineering and Management, 9(4).

Lestari, R. A., & Lestari, N. M. (2025). Fraud in the Implementation of Sharia Bank Financing Cards: Challenges and Construction of Legal Protection for Customers. Istikhlaf: Journal of Sharia Economics, Banking and Management, 7(1), 44–66.

Njoku, D. O., Iwuchukwu, V. C., Jibiri, J. E., Ikwuazom, C. T., Ofoegbu, C. I., & Nwokoma, F. O. (2024). Machine learning approach for fraud detection system in financial institution: A web base application. Machine Learning, 20(4), 01–12.

Ndubuisi, A. F. (2024). The intersection of false projections, identity manipulation, and emerging financial cybercrime threats. INTERNATIONAL JOURNAL OF RESEARCH, 5(12), 5529-5546.

Ogunmokun, A. S., Balogun, E. D., & Ogunsola, K. O. (2022). A strategic fraud risk mitigation framework for corporate finance cost optimization and loss prevention. International Journal of Multidisciplinary Research and Growth Evaluation, 3(1), 783–790.

Olaiya, O. P., Adesoga, T. O., Adebayo, A. A., Sotomi, F. M., Adigun, O. A., & Ezeliora, P. M. (2024). Encryption techniques for financial data security in fintech applications. International Journal of Science and Research Archive, 12(1), 2942-2949.

Ogunwobi, E. (2025). Advancing Financial Security Using Behavioral Biometrics and AI-Driven Authentication. International Journal of Research Publication and Reviews, 6(3), 720–727.

Financial Services Authority. (2025, February 25). Financing institutions, venture capital, fintech P2P lending and micro finance industry update December 2024. OJK International InformationHub.https://institute.ojk.go.id/iru/dataandstatistics/detaildataandstatistics/13379/FinancinG-Institution S-Ventur E-capita L-Fintec H-P2 P-Lendin G-An DMICROfinanc E-Industr Y-updat E-DecembeR-202 4

Oladinni, A., & Odumuwagun, O. O. (2025). Enhancing cybersecurity in fintech: Safeguarding financial data against evolving threats and vulnerabilities. International Journal of Computer Applications Technology and Research, 14(1), 62-78.

Prayoga, A. H., & Voutama, A. (2024). Development of the Bank Account Fraud Detection application using the XGBOOST algorithm. JATI (Student Journal of Informatics Engineering), 8(3), 2916–2922.

Prosper, J. (2025). Next-Gen Data Protection in Digital Transformation: A Sector-Wise Review of Encryption, Database Security, and API Threat Mitigation.

Financial Transaction Reporting and Analysis Center [PPATK]. (2025, December 3). Queen Máxima visits Indonesia as UNSGSA, emphasizes fight against "scams". PPATK. https://www.ppatk.go.id/news/read/1578/ratumximSão Pauloi-Indonesiaa-São Pauloi-S.S.a-tekankan-Wari-scam.html

Rahmah, A. T., & Fasa, M. I. (2024). The Influence of Digital Transformation and Financial Technology (Fintech) Development on Islamic Banking Service Innovation. Journal of Academic Media, 2(10).

Rebecca. (2025). Indonesia Digital Lending & P2P Platforms Market (Report No.6209380). Ken Research / Research and Markets. https://www.researchandmarkets.com/reports/6209380/indonesia-DigitaLlendin G-An D-P2 P-Platform S-Marke T

Rustan, D. M. (2025). The Role of Financial Technology (FinTech) in Increasing Financial Inclusion in Indonesia. Collaborative Journal of Science, 8(1), 928–936.

Salsabila, N. (2025). Analysis of Accounting Information System (SIA) Control of Data Security and Accounting Information. Edutik: Journal of Information and Communication Technology Education, 5(4), 1004–1012.

Siryeh, F. A., Alrammahi, H., & Abdu İbrahim, A. (2025). Tamper Detection in Multimodal Biometric Templates Using Fragile Watermarking and Artificial Intelligence. Computers, Materials & Continua, 84(3).

Saputra, F. (2025, March 14). Samir: The existence of illegal loans has a negative impact Industry Fintech lending Cash. https://keuangan.kontan.co.id/news/sami r-existence n-pinjo l-ilegalberdampa k-negati f-terhada p-industr i-fintec h-lendin g

Saputra, F. (2025, November 18). Task Force Definite: Losses due to fraud reach Rp 7,8 trillions per 11 November 2025.Cash.https://keuangan.kontan.co.id/news/satga S-Past I-Loss N-Akiba TPenipuNCAPA I-R P-7 8-Triliu N-PE R-1 1-Novembe R-2025

Shaheed, K., Szczuko, P., Kumar, M., Qureshi, I., Abbas, Q., & Ullah, I. (2024). Deep learning techniques for biometric security: A systematic review of presentation attack detection systems. Engineering Applications of Artificial Intelligence, 129, 107569.

Shethiya, A. S. (2024). AI-Enhanced Biometric Authentication: Improving Network Security with Deep Learning. Nexus Journal Academy, 3(1).

Sindi. (2025, June 11). Pinjol users in Indonesia are dominated by the age of 19 to 34 years. Medan.Mediakeuangan.id. https://medan.mediakeuangan.id/detail/296564/penggun A-Pinjo LD I-Dominas I-USI A-1 9-hing G-3 4-Tahu N

Thomas, S. T., & Santoso, E. H. (2025). Machines That Think, Data That Tells: The Artificial Intelligence Revolution in the World. Global Creative Media.

Yusop, M. I. M., Kamarudin, N. H., Suhaimi, N. H. S., & Hasan, M. K. (2025). Advancing passwordless authentication: A systematic review of methods, challenges, and future directions for secure user identity. IEEE Access.

Zhang, W., & Lin, H. (2024). Evaluating the Role of Encryption Standards in Supporting Long-Term Information Assurance in Data Storage and Transmission. Journal of Computational Intelligence, Machine Reasoning, and Decision-Making, 9(9), 1–25.