An Ai- Powered and Blockchain – Integrated Model for Automated Claims Processing and Fraud Detection in the Insurance Industry
Main Article Content
Authors
Abstract
This research presents an advanced model that integrates Artificial Intelligence (AI) and blockchain technologies to automate claims processing and strengthen fraud detection within the insurance industry. Traditional systems often face challenges such as lengthy manual procedures, human error, and vulnerability to fraudulent activities. The proposed AI–blockchain framework addresses these issues by combining predictive analytics, machine learning, and natural language processing for accurate claim assessment, while blockchain ensures transparency, data immutability, and secure record-keeping. The integrated system achieved higher accuracy, reduced processing time, and improved fraud detection performance compared to conventional methods. By merging AI’s analytical intelligence with blockchain’s decentralized security, the model enhances operational efficiency, customer trust, and data integrity. This innovative approach represents a significant step toward building a fully digital, secure, and customer-centric insurance ecosystem.
Downloads
Article Details
Section
References
- Alharby, M., Aldweesh, A., & Van Moorsel, A. (2018). Blockchain-based smart contracts: A systematic mapping study of academic research. In Proceedings of the 2018 International Conference on Cloud Computing, Big Data Blockchain (ICCBB) (pp. 1–6).
- Yli-Huumo, J., Ko, D., Choi, S., Park, S., & Smolander, K. (2016). Where is current research on blockchain technology? A systematic review. PLoS ONE, 11(10), 1–27.
- Habibi, Z., Hosseini, A., & Rahmani, L. (2024). Exploring the impact of smart contracts on financial transactions: A review of blockchain applications. Business, Marketing and Finance Open, 1(2), 13–24.
- Ahmad, S., Karim, R., Sultana, N., & Lima, R. P. (2025). InsurTech: Digital transformation of the insurance industry. In Financial Landscape Transformation: Technological Disruptions (pp. 287–299). Emerald.
- Ladva, P., & Grasso, A. (2024, May 2). The evolution of AI in the insurance industry. Swiss Re. https://www.swissre.com/risk-knowledge/advancing-societal-benefitsdigitalisation/evolution-of-ai-in-insurance-industry.html
- Leleko, S., & Holoborodko, Y. (2025, March 5). The power of AI in insurance: Existing opportunities and upcoming trends. Spd Technology.
- Komperla, R. C. A. (2021). AI-enhanced claims processing: Streamlining insurance operations. International Journal of Insurance Technology, 3(2).
- Eling, M., Nuessle, D., & Staubli, J. (2021). The impact of artificial intelligence along the insurance value chain and on the insurability of risks. The Geneva Papers on Risk and Insurance – Issues and Practice, 1–37.
- Sinha, K. P., Sookhak, M., & Wu, S. (2023). Agentless insurance model based on modern artificial intelligence. In Proceedings of the 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI) (pp. 49–56). IEEE.
- Koster, O., Kosman, R., & Visser, J. (2021). A checklist for explainable AI in the insurance domain. In International Conference on the Quality of Information and Communications Technology.
- Dhieb, N., Ghazzai, H., Besbes, H., & Massoud, Y. (2020). A secure AI-driven architecture for automated insurance systems: Fraud detection and risk measurement. IEEE Access, 8, 58546–58558.
- Volosovych, S., Zelenitsa, I., Kondratenko, D., & Szymla, J. (2022). Transformation of insurance technologies in the context of a pandemic. Insurance Markets and Companies, 12(1), 1–13.
- Balasubramanian, R., Libarikian, A., & McElhaney, D. (2021). Insurance 2030: The impact of AI on the future of insurance. McKinsey & Company.