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Driver identification is an integral part of transportation risk management. Drivers are regularly entrusted with valuable cargo that must be insured against accidents, theft, and other adverse events. With over 100% driver turnover annually, recruiters and carriers spend an inordinate amount of time verifying that an applicant is physically and mentally prepared for delivering a customer’s cargo safely. This means that a significant amount of paperwork must be verified: the driver’s CDL; DAC records; MVRs; background checks; drug tests; medical history; and employment history. This is an expensive and time-consuming process, and the information provided is often selective or misleading. Accordingly, insurance is usually assessed on a carrier rather than the individual driver.
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With blockchain-based credentials, or Blockcerts (an open source standard developed by Learning Machine and the MIT Media Lab), risk management can now extend to the driver level. With Blockcerts, drivers own private copies of their digital records, which they can share with anybody they choose—like a prospective employer. That individual or company can then verify the authenticity of the records with the click of a button, without having to consult the organization that issued it. This saves time and money while providing a high level of certainty that the document has not been forged or tampered with.
To minimize document withholding by applicants, employers can also issue drivers new records that link to past assessments from previous employers, forming a chain of records documenting employment history. Over time, drivers will accumulate a “scorecard” based on their past performance, which becomes a risk assessment measure for insurers. The driving record could also release automated rewards for good performance, based on “smart contracts” to better incentivize drivers.
Blockcerts achieves this data linkage without relying on a giant, centralized database of private information. Those are a legacy of the digital past, difficult to manage and honeypots for attackers. Instead, carriers maintain their own separate databases while instantly verifying information issued by any other carrier. This is much more manageable.
How does this work? The blockchain serves as a distributed ledger of transactions which are pseudonymous, meaning it doesn’t store any personally identifiable information (PII). Instead, it stores the “digital fingerprint” of a transaction, which could be, for example, a carrier sending a driver a performance assessment. That performance assessment, which contains PII, is stored securely off-chain, but it contains a reference to its digital fingerprint on the blockchain. This means that wherever the private driver record is stored—in the cloud, on a mobile device, on a hard drive—it references the blockchain, but the blockchain does not reference it.
When a Blockcert is presented for verification, the algorithm calculates its digital fingerprint. If someone has tampered with the certificate, the fingerprint won’t match the copy on the chain and verification will fail. Verification will also fail if the issuer has revoked a Blockcert, or if it has expired. And because all the Blockcerts code is open source, verification is independent of any vendor or issuing institution—meaning Blockcerts will stand the test of time and remain verifiable over an entire career, from anywhere in the world. Blockcerts empowers both drivers and their employers while creating major efficiencies for the insurance system.
By 2020, blockchain-based records will be fully mainstream—thanks in large part to open standards like Blockcerts. Learning Machine is excited to partner with BiTA to lead the way in making that future a reality.
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