AXI restores the credit sensitivity lost in the transition to SOFR—enabling banks to reduce loan spreads by up to 65 basis points without sacrificing risk-adjusted returns, while strengthening SOFR with credit sensitivity that mitigates destabilizing drawdowns and enhances financial stability in the post-LIBOR era.
In the LIBOR era, banks routinely tied revolving credit facilities to credit-sensitive benchmarks. We assess the Across-the-Curve Credit Spread Index (“AXI”)—a transparent, transaction-based measure of wholesale bank funding costs—as a complement to SOFR, summarizing its behavior, construction, and loan-pricing implications. AXI aggregates observable unsecured funding transactions across short- and long-term maturities to produce a daily credit spread that is IOSCO aligned and operationally compatible with SOFR-based infrastructure. The Financial Conditions Credit Spread Index (“FXI”) is a broader market companion to AXI and serves as its fallback. FXI co-moves closely with AXI in normal times; under stress, the correlation of daily changes exceeds 0.9 for economy-wide shocks and remains strong in bank-specific stress, around 0.8 during the Silicon Valley Bank episode. Empirically, AXI is strongly correlated with standard credit-spread measures and market-stress indicators, and is inversely related to financial sector performance. SOFR+AXI exhibits correlations with macroeconomic variables with the signs and magnitudes expected of a credit sensitive rate. In loan-pricing applications, SOFR+AXI reduces funding risk and can support spread discounts of up to 65 basis points without lowering risk-adjusted returns. In stress scenarios, banks relying on SOFR-only pricing can fail to recover as much as 15 basis points on revolving credit lines over as little as three months. Taken together, AXI restores the credit sensitivity lost in the USD LIBOR transition while avoiding reliance on thin short-term markets, delivering significant economic value.
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ABOUT THE AUTHOR
Viktor Tsyrennikov is a vice president in the Financial Economics Practice of CRA International, Inc (CRA). Dr. Tsyrennikov is an accomplished economist with extensive experience in solving the most complex risk management and regulatory challenges for financial institutions. He has a proven track record in building data-driven decision systems and effective risk-management solutions based on advanced analytics and machine learning. Prior to joining CRA, Dr. Tsyrennikov was Head of Quantitative Services and Analytics at IBM Promontory in Washington DC. He is a trusted advisor to C-suite, helping translate quantitative analyses into practical recommendations and advising financial institutions regarding AI solutions and risk management, climate risk, stress testing, portfolio optimization, financial modeling and model risk, and regulatory reforms. With years of experience spanning industry, policy, and academia, he offers a unique perspective that combines innovative and strategic thinking with hands-on management expertise. His engagements include a large bank’s SIFI de-designation, developing stress testing methodology for a large clearing house, and validating banks’ entire model inventories. Dr. Tsyrennikov has been recognized with the Excellence Award for the high quality and impact of delivered work. He has published in leading economics and statistical journals.
This note is not designed to be taken as advice or a recommendation for any investment decision or strategy. Readers should make an independent assessment of relevant economic, legal, regulatory, tax, credit, and accounting considerations and determine, together with their own professionals and advisers, if the use of any index is appropriate to their goals. Neither the USD Across-the-Curve Credit Spread Index (AXI), nor the USD Financial Conditions Credit Spread Index (FXI) are associated with or sponsored by the Federal Reserve Bank of New York or the Federal Reserve System.
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