Challenges, Issues, and Recommendations for Blockchain- and Cloud-Based Automotive Insurance Systems

Abstract

Despite the rapid expansion in the insurance industry, many issues remain unresolved and may require immediate action. As the insurance sector continues to evolve with the development of new technologies, it faces more challenges, especially related to data security and fraud. The fraud-prevention data and tactics presently used by insurance firms are outdated and ineffective. Additionally, insurance firms have traditionally handled the settlement of all consumer claims through lengthy manual processes. These manual processes need to be changed to provide opportunities for insurance businesses to grow. In the case of vehicles, the information obtained from an automobile data recorder can be used as evidence. Data from automated vehicles are critical because they can help the police, law enforcement agencies, and insurance companies to reconstruct the events leading up to a collision. Insurance companies require the forensic analysis of accident videos, which is a time-consuming process and involves a large amount of storage. Due to hardware limitations and associated costs, the current standalone (and often dedicated) computing infrastructures used for this purpose are quite limited. Previous research focused on simple video analysis tasks within cloud computing and blockchain technology. The requirements for a large-scale auto-insurance system are quite high and need more thorough investigation. In this paper, a review of the contribution of recent approaches to storing accidental data in cloud computing using blockchain is provided. We focused on the latest cloud and blockchain studies related to auto-insurance along with the related issues and challenges. Some useful solutions and recommendations are provided to address the identified issues and challenges in the cloud-based and blockchain-based auto-insurance sector.