MD MAMUNUR RASHID | Senior Research Fellow, Consumer and Organizational Data Analytics (CODA) Research Centre, King’s College London
STUART J. BARNES | Chair in Marketing, Consumer and Organizational Data Analytics (CODA) Research Centre, King’s College London
MD ABDUR RAHMAN | Associate Professor, Department of Cyber Security and Forensic Computing, University of Prince Mugrin
The insurance industry continually struggles to identify the validity and justification of insurance claims, which put service providers and clients in a complicated trust relationship. The complexity is not only concerned with people who are involved in fraudulent claims, but due to the nature of certain businesses, genuine claims are often handled with a mindset of potential fraud.
The current insurance business model is largely a traditional, paper-based, error-prone claiming mechanism. Current practices comprise complex and costly processes, often resolved by the involvement of the legal administrators. The overall process also has a multi-point authentication issue, as it needs to maintain an immutable ledger, which is distributed and validated among different parties.
Recently, technology has made evolutionary advancements in the area of distributed ledgers. In this paper, we present a novel architecture that will allow a massive amount of heterogeneous data to be used for insurance claims evidence. Our framework leverages the state-of-the-art networking technology and both blockchain and off-chain decentralized repositories. The framework also employs explainable artificial intelligence for bringing trust within the reasoning and deep learning algorithms and helping in different ecosystems of the insurance industries. Our solution uses advanced technologies in the insurance industry that could potentially enhance transparency, trust, and automation in handling insurance claims.