Blockchain-based Immutable Evidence and Decentralized Loss Adjustment for Autonomous Vehicle Accidents in Insurance

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Authors: Mehmet Parlak

Published: 2023-03-29 21:50:13+00:00

AI Summary

This paper proposes a blockchain-based decentralized application (dApp) called Tamper-Proof to verify the authenticity of accident footage from autonomous vehicles and decentralize loss adjustment. The system uses a hybrid of decentralized and centralized databases with smart contracts to ensure the integrity and provenance of evidence, mitigating the risk of deepfakes in insurance claims.

Abstract

In case of an accident between two autonomous vehicles equipped with emerging technologies, how do we apportion liability among the various players? A special liability regime has not even yet been established for damages that may arise due to the accidents of autonomous vehicles. Would the immutable, time-stamped sensor records of vehicles on distributed ledger help define the intertwined relations of liability subjects right through the accident? What if the synthetic media created through deepfake gets involved in the insurance claims? While integrating AI-powered anomaly or deepfake detection into automated insurance claims processing helps to prevent insurance fraud, it is only a matter of time before deepfake becomes nearly undetectable even to elaborate forensic tools. This paper proposes a blockchain-based insurtech decentralized application to check the authenticity and provenance of the accident footage and also to decentralize the loss-adjusting process through a hybrid of decentralized and centralized databases using smart contracts.

Key findings

The proposed Tamper-Proof dApp effectively addresses the challenges of deepfakes in insurance claims by providing a secure and verifiable record of accident footage. The decentralized loss adjustment mechanism promotes fairness and efficiency in claim processing, aligning economic incentives of loss adjusters with accurate decisions.

Approach

The approach uses a dApp to record video footage of accidents, creating a hash of the video and storing it on both a private (IBM Blockchain Platform) and public (Ethereum) ledger. This ensures tamper-proof evidence, while decentralized loss adjustment, incentivized through token staking and Schelling games, improves fairness and efficiency.

Datasets

UNKNOWN

Model(s)

UNKNOWN

Author countries

Turkey

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