Privacy-Preserving Insurance Framework using Zero-Knowledge Proofs and Secure Multi-Party Computation

Abstract

The insurance sector has been moving towards a more digital footing on the backdrop of growing demand for transparency, efficiency and privacy of data. The common way it is built exposes it to subtle policy checks and human intervention for claim reviews and exposes consumer data. Although blockchain technology has been explored as a possible solution, the public log nature of blockchain introduces grave concerns in privacy preservation, especially, in industries with strict regulatory requirements, including healthcare and life insurance. We propose a privacy-preserving insurance system in our paper based on ZKPs and SMPC to handle these issues. Zero-Knowledge Proofs (ZKPs) enable policyholders to prove to third parties’ compliance to their policy conditions without revealing underlying information, while leveraging Secure Multi-Party Computation (SMPC) provides insurance companies, business partners, and third-party auditors to jointly compute premium prices, validate claims, and compute refunds on privatized data inputs. End to End the Privacy of Data is secured, even at point of payment, Claim or Refund settlement. We present experimental results demonstrating real-time (300-950ms) latency, perfect replication on all nodes, and no leakage across transaction types. This work addresses inefficiencies that have plagued the insurance industry for years by presenting an extensible, cryptographically secure technology that can be used in the next era of digital insurance. It proposes a verifiable secret sharing based transaction model to bring in a new trustful and privacy-preserving insurance transaction paradigm.