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LSTA Automates its Credit Agreement

May 14, 2019 - On May 10th, the LSTA hosted a webinar to discuss the automation of the LSTA’s Form of Revolving Credit Facility (the “LSTA Revolver”) using OpenLaw’s open source markup language.  LSTA’s Bridget Marsh and Tess Virmani were joined by Aaron Wright of Cardozo Law, Michael Rice of OpenLaw, and Douglas Landy of Milbank to discuss the pros and cons of automating the LSTA Revolver and different lessons learned during the exercise. Blockchain technology creates new opportunities for lenders, borrowers, and agents to streamline the structuring, execution, and administration of credit agreements.  Today, the process of originating and administering a syndicated loan often is time-consuming, expensive, and manual, with many human touchpoints, all of which create the risk of error.  The LSTA has worked with OpenLaw to develop an end-to-end prototype based on the LSTA Revolver to model how parties can create a loan, execute the credit agreement on a blockchain, and automate certain interactions that typically arise in the context of a syndicated loan, which together can help to provide the building blocks for faster settlement of loan trades.  The LSTA Revolver prototype demonstrates that (i) the drafting of syndicated loan agreements can be partly automated using legal technology tools with evidence of the parties' agreement and associated electronic signatures stored on a blockchain; (ii) smart contracts can be used to automate certain aspects of loan administration, particularly responsibilities performed by the agent; (iii) blockchain technology and smart contracts can be used to hard code regulatory compliance, in the form of approved addresses that can help ensure compliance with KYC/AML requirements; (iv) blockchain technology and smart contracts can be used to hard code disqualified lender lists to help streamline the borrower consent process; and (v) blockchain technology can be used to digitally represent  a lender’s interest in a syndicated loan, creating opportunities to shorten settlement times for syndicated loan trades (and as explained during the webinar, these “transfer tokens” will not raise any questions about a loan being interpreted as a security).  The presenters also highlighted the practical limitations of this new technology and smart contracts. For example, (i) only select provisions of the LSTA Revolver could be converted into code-based provisions, (ii) smart contracts can streamline the role of administrative agent, but will not entirely remove the agent from the syndicated lending process; and (iii) because smart contracts can only interact with tokenized assets (transfer tokens), unless digital assets quickly gain widespread usage, blockchain-based applications and services will take time to adopt.  Despite these limitations, the presenters all agreed that a new future for digital syndicated lending is beginning — one that promises to ensure greater efficiencies.  Bridget Marsh is diving deeper into this topic this week when she will speaking at the CLOC in Las Vegas with Joe Dewey and Ziggy Williamson of Holland & Knight about how machine learning can help improve loan market and other associated processes.  The Holland & Knight team will be discussing their machine learning and other products which certainly will help market participants as they plan a LIBOR transition. Click here for the replay and here for the Consensys article on the automation of the LSTA Revolver.

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