Leveraging AI and Big Data for Real-Time Risk Profiling and Claims Processing: A Case Study on Usage-Based Auto Insurance

Abstract

The integration of Artificial Intelligence (AI) and Big Data analytics in the insurance industry has revolutionized traditional processes, particularly in risk profiling and claims processing. This case study explores the application of AI and Big Data in the context of usage-based auto insurance (UBI), where real-time data collected from connected vehicles is leveraged to create dynamic, personalized risk profiles and optimize claims handling. By analyzing vast amounts of data from telematics devices, including driving behavior, vehicle performance, and environmental factors, AI algorithms can predict risk with unprecedented accuracy, enabling insurers to offer tailored premiums and enhance customer satisfaction. Furthermore, AI-driven automation in claims processing streamlines operations, reduces fraud, and accelerates settlement times. This case study demonstrates the transformative potential of these technologies in improving operational efficiency, customer engagement, and profitability within the auto insurance sector, while highlighting the challenges of data privacy, regulatory compliance, and the need for robust data infrastructure.