When Markets Evolve Quickly: The Case for Proactive Credit Surveillance

In today's complex global credit environment, market participants face an escalating challenge: navigating a rapidly shifting risk landscape. On the surface, global credit markets appear to be smooth sailing, characterized by compressed corporate spreads and contained default rates. Yet beneath this calm exterior, a different narrative is unfolding.¹ Private credit quality is quietly softening, the Artificial Intelligence (AI) revolution is driving starkly asymmetric outcomes across sectors, and structural macroeconomic headwinds - such as shifting tariffs and geopolitical fragmentation - continue to intensify. For risk managers and investors, the ultimate risk is not the credit rating migration itself but being caught off guard by its sudden arrival.

To address this challenge, S&P Global Market Intelligence developed the Credit Transition Signals (CTS).² CTS is a quantitative, model-driven surveillance tool designed to generate forward-looking probabilities of credit deterioration and improvement for corporations rated by S&P Global Ratings - across both public and private entities globally. What sets CTS apart is its holistic, multi-dimensional framework. By integrating ratings history, company fundamentals, and macroeconomic factors with real-time, market-implied signals, CTS provides a continuous, high-frequency view of credit migration risk for rated entities. In this case study, we demonstrate how CTS delivers the granular, predictive insights necessary for proactive credit surveillance.

CTS in Action - Discriminative and Predictive Power

Figure 1: Actual percentage of downgrade in 12 months by rank groups (based on predicted probability of deterioration, from high to low)

To evaluate CTS's incremental discriminative power over traditional indicators, we analyzed the realized downgrade rates of a global cohort of companies carrying a 'Negative' CreditWatch (CW) or Outlook (OL) designation from S&P Global Ratings from 2013 to 2025. The sample was segmented into five risk buckets (quintiles) based on CTS's predicted 1-year probability of deterioration. Figure 1 highlights the model's robust rank-ordering ability. Despite all issuers sharing the same qualitative negative CW / OL, the realized 12-month downgrade rate for the highest-risk quintile was 54%, while the lowest-risk quintile was just 17%. The results demonstrate CTS’s capability to add critical risk-differentiation beyond traditional, qualitative credit rating indicators.

Figure 2: Predicted 1-year probability of deterioration prior to downgrade actions for the sample companies with non-negative CW&OL 

We also evaluated CTS’s capability to generate potential early warning signals for companies classified under 'stable' or 'positive' CreditWatch (CW) or Outlook (OL) designations. Figure 2 illustrates that for issuers with non-negative indicators between 2013 and 2025, the model's predicted probability of deterioration began rising steadily up to 24 months prior to an actual downgrade event. This consistent upward trend serves as a crucial leading indicator. By detecting early signals of potential credit deterioration in addition to traditional rating indicators, the tool gives investors and risk managers valuable lead time to pre-emptively mitigate risk and optimize capital allocation.

Case Study - Divergence of Credit Transition Trend Across Industries

Figure 3: Change in median predicted 1-year probability of deterioration by industry (April 2025 vs. May 2026)

Figure 3 illustrates the shift in the median 1-year probability of deterioration across corporate industries from April 2025 to May 2026, revealing a stark divergence in credit deterioration risk:

• Most pronounced escalation in risk:
  • Software & Services: The median deterioration probability nearly doubled, jumping from 7% to 13%, driven by leverage deterioration, refinancing risk, valuation pressures, and structural AI shocks.
  • Commercial & Professional Services: The probability climbed from 8% to 11% as firms grappled with margin compression fueled by persistent inflation and corporate client spending cuts.
• Other notable risk increases: Elevated credit migration risk was also observed in Household & Personal Products, Food, Beverage & Tobacco, and Media & Entertainment.
• Demonstrated resilience: Semiconductors, Technology Hardware, and defensive industries (including Consumer Staples Distribution, Consumer Durables, and Energy) showed remarkable strength. These industries were buoyed by robust cash flows, stabilized capital expenditures, and resilient pricing power amidst steady demand.

Figure 4: Comparative trend analysis of sub-industries in the IT sector

Figure 4 tracks the monthly time-series of the median 1-year probability of deterioration for sub-industries within the Information Technology sector from April 2025 to May 2026. While both the Semiconductors and Technology Hardware industries saw their credit migration risk profiles improve - marked by an approximate 5% decrease in median deterioration probability - the Software & Services industry experienced a significant credit downturn. Its 1-year probability of credit deterioration surged by a staggering 6% over the year, nearly doubling to 13%. This divergence, which began widening around August 2025, vividly illustrates the asymmetric impact of the AI revolution. On one hand, semiconductors and hardware manufacturers enjoy immediate tailwinds from the physical buildout of data centers and high-performance computing infrastructure, strengthening their cash generation and debt profiles. On the other hand, legacy software players face structural threats. Generative AI is eroding pricing power, escalating customer churn, and clouding long-term revenue predictability.³

Conclusion - Proactive Credit Monitoring for a Dynamic Market

In an era characterized by rapid technological disruption and macroeconomic volatility, proactive credit monitoring of rated entities has become an absolute necessity. Relying solely on traditional indicators is no longer sufficient. S&P Global Market Intelligence’s CTS tool bridges this gap, providing the forward-looking, data-driven insights that asset and risk managers require to navigate today's complex credit landscape. By delivering a timely and highly granular view of credit transition risk for the rated universe - across both public and private corporations, CTS empowers market participants to confidently safeguard their portfolios, optimize capital allocation, and capture emerging opportunities in a fast-moving market.

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