MetLife Subsidiary LumenLab Pilots Blockchain Insurance System for Diabetes
Singapore-based digital innovation center Lumenlab is testing a blockchain-enabled insurance solution for diabetes sufferers, according to a press release published August 20.
Lumenlab is a subsidiary of financial services provider MetLife and has reportedly developed the new project within the Monetary Authority of Singapore’s (MAS) regulatory sandbox.
The pilot, dubbed Vitana, is a parametric, automated insurance product targeting those who develop gestational diabetes - a condition that is said to affect one in five pregnant women in Singapore. It has been co-developed with insurance firm SwissRe, UK tech and
blockchain specialists Cognizant, and electronic medical records (EMR) provider Vault Dragon.
The blockchain solution has been designed to securely integrate EMR data in order to trigger an automatic payout upon diagnosis, effectively removing the need for manual policy claims.
As LedgerInsights outlined following Lumenlabs’ demo of Vitana at Consensus earlier this year, the bulk of electronic health records in Singapore are tied up in manual, centralized data silos. Singapore residents who have coverage are first required to personally pay for their treatment and only later claim it back from their insurer.
In the new system, Vault Dragon will securely provide EMR data to confirm or refute a diagnosis: in the case of a confirmation, a smart contract will send a customer’s encrypted bank account details to the insurer, prompting an automated payout. No additional patient data will be aggregated or stored on Metlife servers.
As a Cointelegraph analysis highlighted this spring, blockchain technology has been gaining increasing traction in the global healthcare industry to innovate data sharing, security and insurance systems.
In April, German Camelot Consulting Group launched its own blockchain-based solution for the management of sensitive medical data, arguing that existing healthcare systems transfer sensitive patient data by analog means, running an “immensely high” risk of error and misuse.