With the coming December 2021 retirement of LIBOR, Chief Data Officers in financial institutions are preparing to face their Y2K moment. An estimated $350 trillion of financial instruments are linked to this globally accepted benchmark rate for short-term loans, including adjustable rate mortgages, credit cards, student loans, bonds, securities and more. The data management challenge is colossal. Over 100 million transactions reference LIBOR and must be replaced with alternative risk-free rates (“RFRs”), such as SOFR for the U.S. dollar and SONIA in the UK. Making the switch won’t be a simple search-and-replace exercise. Here’s why:
- RFRs are overnight rates, whereas LIBOR is published for multiple terms (e.g., one-week, three-month, etc.).
- Credit risks are embedded in LIBOR, while RFRs are “risk-free,” making a simple conversion impossible.
- RFRs have different behavioral characteristics than LIBOR, resulting in different historical spreads, so fallback rates must be applied.
Instead of viewing the LIBOR transition as just another costly, resource-consuming exercise, organizations should see this change a catalyst to uplevel and automate their data management processes to better understand and trust their data. Here are some benefits that one large financial institution told ASG they received from implementing an automated data intelligence system in just four months:
- Discovered LIBOR rates across 150 Applications and 20,000 Cobol programs.
- Solved a nine-month attestation request from their largest client that was being passed from department to department in search of a root cause.
- Shrunk their footprint of redundant applications, including consolidating ten UDTs to one!
With these successes, this data governance organization was able to easily justify additional investment for other use case