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Contracts AI in Commercial Loans

Noah Waisberg • May 30, 2022 • 3 minute read

Contracts AI in Commercial Loans

Large financial firms often enter into a significant number of commercial loans. While smaller individual loans are done on the financial firm’s appropriate form loan agreement without modification, commercial loans are often heavily negotiated. Lenders (often but not always banks) and borrowers spend significant money on getting outside counsel to negotiate the wording of credit agreements. All those lawyers make changes. In general, lenders have access to the actual credit agreements themselves. However, many lack an ability to see generalized details on how credit agreements have been changed. They may have a spreadsheet or database listing borrower name, principal, interest, payment schedule. But do they know how all the agreements differ off the form? Presumably, all the money spent on negotiating credit agreements yields meaningful changes (especially to the covenants). Do lenders know what the changes are, en masse? Likely, these changes impact the risk profile of the loans. If lenders had a better understanding of the details of their loans, it might enable them to get a better handle on the risk of their loan book (which might even enable them to take on more risk).

A problem for lenders is that getting at information on how individual commercial loans differ from each other is hard. One way to do this would be to capture details every time a new credit agreement is executed. Many financial institutions have not done this. So that means that starting a practice of keeping details potentially requires reviewing a mass of already existing legacy credit agreements. Credit agreements can be long (often over 100 pages) and dense, and it can take hours to review a single agreement. This means that assembling a database from scratch listing the terms of commercial loans could be a lot of work.

Some Contracts AI comes out of the box ready to find hundreds of data points in credit agreements (as well as many more pieces of information in NDAs, commitment papers, indentures, and ISDA master agreements and CSAs, among other things). By automatically finding data in these agreements, Contracts AI can give holders of lots of commercial loans a chance of building a database of what they’ve agreed to. Depending on the data point sought, the diversity of the underlying agreements, and the particular AI in use (i.e., some are better than others on different tasks), Contracts AI can be fairly accurate at extracting data out of credit agreements. (Of course, the best way to determine accuracy is to try for yourself.) If undertaking a project to get data from your credit agreements, you will also need to determine how to do this. Some options include:

  • Dedicated contract analysis software
  • Contract management systems with AI built in
  • Embeddable Contracts AI that’s integratable with another system via API. Note that these have no user interface (which can be a plus or minus)
  • Alternative Legal Service Providers who will do the work for you, maybe using AI