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Marsh targets gig economy with new blockchain solution

3rd October 2018 - Author: Charlie Wood

Global re/insurance broker Marsh is working with data security platform Evident on the first blockchain-based verification solution for clients in the sharing and gig economies.

marshMarsh has been considerably active in incorporating blockchain into its value chain since the company’s partnership with IBM was first announced five months ago.

This new solution is aimed at streamlining the on-boarding of gig economy workers by simplifying insurance and identifying verification processes with the added trust, safety, and risk management inherent in blockchain technology.

Individuals in the gig economy contract their services out to be paid per task. Originally a consumer-to-consumer market, rapid improvements in technology have enabled the gig economy to grow into an entirely new market in recent years.

Built on the IBM Blockchain Platform and open source Hyperledger Fabric, with input from insurance standards leader ACORD, this solution is hoped to digitise certificates of insurance into immutable records so that all permissioned parties can instantly verify information.

“The beauty of blockchain technology is its ability to provide trust, efficiency, and security across ecosystems,” said Sastry Durvasula, Chief Digital, Data and Analytics Officer at Marsh.

“As the need for insurance and identity verification grows, our collaboration with Evident harnesses the power of blockchain to transform a major business challenge for the sharing and gig economies.”

“Verification and validation cause significant friction in the sharing economy. Solving this challenge requires a solution that brings together trusted information from several parties,” said David Thomas, Chief Executive Officer of Evident.

“Integration of our platform’s identity verification capabilities with Marsh’s blockchain will streamline the onboarding of gig workers and offer an unparalleled ability to verify key information, all while ensuring our customers minimize their exposure to their data.”

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