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Life after LIBOR 

Using artificial intelligence to prepare your contracts for the transition

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The days of LIBOR are numbered, but the reference interest rate is embedded in millions of financial contracts worldwide. Artificial intelligence (AI) can help banks mitigate the financial and legal risk associated with contracts maturing beyond 2021.

The most important number in the world

For decades, LIBOR has been used as the interest rate benchmark, globally, by many financial institutions, mortgage lenders, student loan officers, and credit card agencies, all of which set their own interest rates relative to LIBOR. Today, the interest rate is used as a reference for an estimated $350 trillion of loans, securities, and derivatives worldwide. 

In 2017, the UK financial regulator said that submitting LIBOR rates will no longer be required after 2021. As a result, the “world's most important number" will soon become, ironically, a non-existent number. 

A monolithic task

It's now just T-minus two years until the financial services industry says goodbye to LIBOR. But LIBOR is hardwired into almost all commercial contracts that have a variable interest rate component. So the transition from LIBOR to alternative rates poses an enormous task for banks.

Specifically, banks need to revise contracts maturing beyond 2021 to incorporate fallback provisions, terms in case LIBOR is unavailable, or to transition to an alternative reference rate. While fallback provisions may exist in some contracts, it's likely that they were designed to address the temporary unavailability of LIBOR, such as a computer systems glitch or a temporary market disruption, rather than permanent discontinuation and would therefore need to be revised.

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The volume of the contracts to review and revise is breathtaking, and millions of documents will need to be reworked. As a barometer of the magnitude of the problem, Lehman Brothers alone was a party to more than 900,000 derivatives contracts when it went bankrupt in 2008. And, while LIBOR is calculated for five different currencies, the value of contracts referencing US dollar LIBOR alone is estimated at $200 trillion.

Banks face extensive and costly administrative work to change contracts, update computer systems, and communicate with customers to transition from LIBOR.

The three phases of the transition

The transition away from LIBOR consists of three phases:

Phase 1: Contract inventory and review
The first step is to assess the impact of LIBOR on existing contracts. Banks must be able to segregate contracts that reference LIBOR from those that do not. However, this analysis is complex and requires deep domain expertise and understanding of asset classes. For example, a fixed-rate loan contract that is ostensibly not linked to LIBOR may contain an interest rate derivative linked to it. Banks must develop a set of contract review questions that address these complexities.

Phase 2: Pre-replacement rate action items
Although there is no clarity yet on the replacement rate, banks must start now to incorporate interim amendments. For example, if there are loans that do not have any fallback language, banks can incorporate a soft fallback option. Banks can also start to develop contingencies. For example, LIBOR serves seven different maturities (overnight, one week, and 1, 2, 3, 6 and 12 months). However, the replacement rate might not mimic the same tenor structure, so banks can plan for contract changes that should be implemented in this case.

Phase 3: Post-replacement rate action items
Soon, there will be clarity on the replacement rate, its characteristics, and how it will be operationalized for each asset class. In this phase, the bank must amend contracts, update systems and processes to procure and test data feeds for the new rate, and train staff to address the needs of the new rate. 

Applying AI to the LIBOR transition

AI is well equipped to perform contract reviews associated with the LIBOR transition.

Using applied computational linguistics, pattern recognition, and machine learning, AI can extract contract terms and validate them against the contract review questions and other data. For example, AI, specifically natural language understanding, can identify whether LIBOR is being referenced in the loan and direct humans to the exact locations in the loan documentation that cites LIBOR.

Using machine learning, AI can learn to identify the numerous permutations of phrases that cover fallback procedures and whether they are sufficient for the permanent discontinuation of LIBOR. And AI can validate that the amendments processed are reconciling with the guidelines given by the front-office.

AI solutions already exist to minimize legal risk, reduce costs, and boost governance with respect to contracts. Such solutions have been applied to interpret tens of thousands of credit agreements and amendments across industries and demonstrated benefits such as 80% improvement in process efficiency and 70% less time spent on processing documentation. These same solutions may now be applied to the LIBOR transition.

Driving impact from your AI investment

According to the second edition of Genpact's recent research on AI, the banking sector stands out as the top spender in AI technology, but is only average in achieving very positive outcomes from AI. This may be because banks are not leveraging or using it in the right way. Applying AI to the LIBOR transition is an ideal way for banks to harness the technology's power to drive positive outcomes. An AI solution to the LIBOR transition affords:

  • Traceability – AI makes archival data available so banks can see what changes have been made to their contracts, creating an audit trail
  • Complex interpretations – A combination of deep expertise in commercial lending and AI helps banks interpret the context of various LIBOR references and the legal aspects of the contract
  • Accuracy – AI minimizes the risk of human error and allows banks to run rules to catch any mistakes that do occur
  • Scale – AI can supplement the human workforce to assess and review existing contracts
  • Opportunity – AI to do more than address immediate LIBOR issues. For example, banks can use AI to mine loan agreements to assess and improve the degree of covenant protection available across their portfolio and accelerate the time to close a loan by reconciling draft loan contracts against term sheets

Now is the time to begin

AI can help financial institutions:

  • Assess their existing library of contracts
  • Make necessary changes for a smooth transition to alternative reference rates
  • Turn regulatory requirements into an opportunity to enhance customer experience and risk management
  • Ensure maximum return on AI investments

The transition from LIBOR to an alternative rate has the potential to cause havoc if not handled properly. Financial institutions must start now to manage the legal risk associated with the LIBOR transition. In fact, by being proactive banks can turn this challenge into an opportunity.

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This article was authored by Anu Sachdeva, global service line leader, commercial banking, Genpact and first appeared in Computer Business Review and Techsite. Similar articles appeared in Financial Director and Computing.