Managing Unstructured Data in a Post-LIBOR World
The phase-out of the London Interbank Offered Rate (LIBOR) represents much more than a shift in lending rates. The benchmark rate for global lenders, and the basis for consumer loans around the world, LIBOR is embedded in financial contracts with a total value estimated as high as 340 trillion worldwide.
Identifying and remediating LIBOR-related exposure is one of the greatest challenges the financial services industry has ever faced—and it’s one for which many firms are woefully unprepared.
While banks have been advised to stop writing new loans tied to LIBOR by October 2020, the phase-out is not expected to be complete until the end of 2021. In order to be prepared—and to reduce the risk of lawsuits due to misrepresentation of rate terms, interest owing, and other fallout—banks must remediate contracts to reflect the shift to the replacement rates in advance of that date.
The Steep Cost of LIBOR Transition
A significant portion of these costs are due to the need to closely review each contract to identify legacy LIBOR-linked loans and transition these agreements to new rates. Financial firms cannot even begin to estimate and address their LIBOR exposure without a clear, complete, and accurate view of their agreements. And while a smaller institution may be able to manually comb through contracts to identify LIBOR, for large enterprises with millions of contracts, manual review simply isn’t feasible.
Unstructured Data, the Greatest LIBOR Compliance Risk
There are several contract analysis solutions designed to search repositories for specific agreements. But the process of identifying LIBOR contracts is hindered by the presence of unstructured data—namely legacy contracts and loan agreements with content that cannot be automatically searched for LIBOR-linked terms.
Additionally, key contract terms are often buried in variously worded clauses and within inconsistent formats—and LIBOR text could exist anywhere in your organization’s agreements—resulting in time-consuming, expensive manual effort.
Why Contract Intelligence Matters
Given the potential costs riding on the successful transition of LIBOR-linked contracts, organizations can’t afford to let their documents fall through the cracks. The presence of unstructured data makes it difficult to avoid this pitfall. However, gaining total visibility into your contracts is possible with a sophisticated approach to data and a robust Contract Intelligence solution:
- That can scan multiple sources (repositories, fileshares, emails, etc.) for contracts that may contain LIBOR-related terms and obligations. The right technology should combine the common sense of a human—finding and assessing contracts with relevant LIBOR clauses—and the efficiency of a well-oiled machine.
- With flexible, highly accurate Optical Character Recognition (OCR) capabilities that can ingest vast volumes of contract content in a broad range of formats—with minimal manual intervention. If your OCR tool is accurate only 80 percent of the time, you risk overlooking LIBOR terms within 20 percent of your contracts. While that may not seem like a huge margin of error on paper, those inaccuracies can add up over thousands or millions of agreements.
- With flexible Classification and Extraction capabilities that allow for the creation and refinement of LIBOR-related terms, including:
- Clauses that refer to “interest rate” or “rate”
- The terms "inter-bank offered rate," "LIBOR," or "IBOR," and variants of those terms
- Clauses that refer to “fall-back” and “adjudication”
The Final Verdict
Financial firms have less than two years to complete one of the largest undertakings in their history, and there is much riding on the successful identification and remediation of LIBOR-linked agreements. While sifting through countless legacy contracts is onerous—and frankly impossible for many enterprises—a robust contract intelligence solution offers firms a powerful way to get a handle on this immense task. Click here to learn more about how to prepare for the post-LIBOR transition.