BLOG — Nov 12, 2024
AI's Financial Impact on Intel and Nvidia: A Credit Risk Perspective
This blog is written and published by S&P Global Market Intelligence, a division independent from S&P Global Ratings. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit scores from the credit ratings issued by S&P Global Ratings.
The semiconductor industry serves as the backbone of the modern digital economy, powering everything from electronics to autonomous vehicles. The sector is projected to experience strong growth as it caters to the rising need for semiconductor materials in emerging technologies like artificial intelligence (AI), autonomous driving, the Internet of Things, and 5G. This growth is fueled by intense competition and investment in research and development. However, the industry faces substantial challenges such as supply chain vulnerability exposed by COVID-19 pandemic and geopolitical risks particularly U.S.-China trade tensions, which threaten to disrupt production and distribution of essential microchips.123
In the face of these key trends, some semiconductor companies capitalized on emerging opportunities by investing heavily in AI and cloud computing, positioning themselves as leaders in advanced chip design and manufacturing. Meanwhile, some companies struggled to keep up with the rapid advancements in the industry due to outdated technologies and production processes.
In this blog, we analyze the diverging fortunes of two tech giants, Intel & Nvidia, in the face of shared opportunities and challenges. We will utilize quantitative models from S&P Global Market Intelligence to examine how their credit risk profiles have evolved over time.
Intel's Struggles Vs Nvidia’s growth
Intel has historically been a leader in semiconductor manufacturing, particularly for central processing unit (CPUs), but the rise of AI, cloud computing, and mobile processors has exposed vulnerabilities in its business model. Its slow transition to AI and cloud computing technologies has been a significant challenge. Its focus has been on legacy businesses (PCs and servers), which are increasingly commoditized. As a result, Intel finds itself falling behind in the development of AI chips. This inability to adapt to the demands of AI and high-performance computing markets has severely impacted Intel's credit metrics, increasing its credit risk.
Conversely, Nvidia has emerged as one of the biggest beneficiaries of the AI revolution, significantly improving its financial health and credit standing. Nvidia’s graphics processing unit (GPUs) have become the backbone of AI research, data centers, autonomous vehicles, and cryptocurrency mining. As a result, Nvidia’s revenue has surged, allowing it to maintain a strong credit profile with better ratings and a lower probability of default (PD) compared to Intel.
Intel’s credit rating has seen downgrades4 by S&P Global Rating due to lower-than-expected revenue growth, declining market share, straining cash flows, high capital expenditure. Table 1 shows some of the key financial metrics including debt servicing capacity (EBIT interest coverage, CFO/Debt, FFO interest coverage) which can be of great importance to bond investors. Table 1 shows that Intel’s debt servicing capacity significantly deteriorated year on year.
On the other hand, Nvidia’s financial performance improved significantly. Its revenue increased more than two-fold in the last three and half years. Despite increases in capital expenditure and debt, Nvidia maintains a considerably healthier financial position compared to Intel. As a result, its capacity to service debt has improved significantly.
Table 1. Financial Metrics of Nvidia and Intel
Source: S&P Global Market Intelligence as of September 30, 2024. For illustrative purposes only.
*Nvidia’s financial period is from February to January while Intel’s financial period is January to December.
Credit risk of Nvidia & Intel based on market implied models:
Market-based models are increasingly important for evaluating credit risk due to their ability to reflect real-time market sentiment. Traditional credit risk models, such as those relying on financial statements or historical default data, may not fully capture the fast-changing nature of financial markets. In contrast, market-based models respond more dynamically to economic shifts, market volatility, and investor sentiment, providing early warning signals of credit deterioration or improvement. These models leverage information from various financial instruments, such as corporate bonds, credit default swaps (CDS), and equity prices, to provide a real-time assessment of an entity’s creditworthiness. The below table shows the comparison of these market implied models.
Table 2. Comparison of different market implied credit risk models
At S&P Global Market Intelligence, we have developed various market implied credit risk models including Probability of default Market Signal (PDMS), Bond implied Score (BIS) and CDS market derived signal model.
PDMS produces an equity driven market-based indicator, covering 80000+ public corporates. It uses the Merton framework with additional enhancement and several adjustments to reduce the spurious results. The CDS adjustment, when available, is a crucial modification that enhances credit risk assessment by integrating insights derived from the CDS market. This adjustment increases the relevance and robustness of PDMS's credit risk assessments.
BIS model generates a credit risk signal extracted from bond market prices or spreads. It incorporates dynamics of credit market evolution across a broad set of sectors, ratings, and currencies, while considering impact of bond liquidity. It covers circa 7500+ bond issuers.
Figure 1 outlines the evolution of BIS and PDMS score for Intel and Nvidia along with S&P Global rating’ ICR from 2021. Intel's BIS score took a conservative stance at the start of 2021 compared to issuer credit rating (ICR), signaling early market concerns about the company’s performance. This reflected diminishing market confidence due to the industry’s shift from CPUs to GPUs in the generative AI era and Intel’s manufacturing setbacks. After 2022, Intel's BIS score continued to decline, aligning with its loss of market share, and weakening financial health, as seen in declining revenue and debt-servicing capacity. While PDMS reflects a more cautious outlook as the equity market is more concerned about with short-term profitability. It was driven by market-wide events unrelated to specific corporate credit risk, such as export restriction to China and weaker consumer spending. Inflation & rising interest rates also follow the same trend, as exemplified by Nvidia.
In contrast, Nvidia's BIS score improved steadily, signaling strong market confidence in its leadership in AI, semiconductors, and technological advancements. The inherent volatility seen in these models is reflective of the fluidity of the tech industry, where market sentiment can shift rapidly due to innovation, competition, and other sector-specific factors.
Figure 1. Intel & Nvidia’s different market implied scores and S&P Global Rating’s ICR
Source: S&P Global Market Intelligence as of September 30, 2024. For illustrative purposes only.
The graph highlights the diverse perspectives offered by different market signals, emphasizing the importance of considering multiple indicators. Each signal provides unique insights into credit risk, capturing aspects that may not be apparent when relying on a single measure. For example, PDMS reflects credit risk through stock price fluctuations and volatility, while BIS scores benchmark against sector curves, capturing relative risk within an industry. However, interpreting multiple market signals can be complex and time-consuming. The RiskGauge+(RG+)5 model addresses this challenge by integrating various market signals with fundamental and macroeconomic factors, creating a cohesive and comprehensive assessment. This makes RG+ an efficient, all-in-one tool for credit risk evaluation, streamlining analysis for a more accessible and holistic view.
Holistic credit risk assessment of Nvidia & Intel based on RiskGauge+ model
As shown in Figure 2, the RG+ score exhibits lower volatility compared to individual market signal models, thanks to the inclusion of fundamental data. Despite this stability, it retains the ability to provide early warning signals for changes in credit risk, leveraging insights embedded within market signal models. For Intel, the RG+ score consistently showed a decline ahead of each rating downgrade, illustrating the model’s ability to serve as an early warning indicator for credit risk deterioration. This proactive behavior in the RG+ score reflects its sensitivity to underlying shifts in financial health and market conditions. For Nvidia, we observe that the RG+ score generally aligns with the movement of ICR, with one notable exception: between June 2022 and June 2023, the RG+ score trends downward while the ICR trends upward. This divergence is largely driven by equity market volatility, as illustrated in Figure 1, where PDMS increased significantly due to a market-wide event. Despite this temporary misalignment, the RG+ score remains close to the ICR due to the integration of fundamental and other indicators. After this period, the RG+ score realigns with changes in the ICR, effectively capturing shifts in creditworthiness ahead of official rating updates.
Figure 2. Intel & Nvidia’s RiskGauge+ Score and S&P Global Rating’s ICR
Source: S&P Global Market Intelligence as of September 30, 2024. For illustrative purposes only.
To conclude, it is essential to use multiple signals including fundamental for thorough credit risk analysis. Different market signals (e.g., equity-driven, bond-driven, or CDS-based) capture distinct market dynamics, while fundamental indicators can provide a long-term view of a company’s intrinsic financial health. Together, these perspectives offer a balanced assessment, covering both market sentiment and underlying business fundamentals. Relying on just one indicator limits the view to a specific aspect of credit risk, whereas combining multiple indicators provides a holistic picture of credit risk of company. Each indicator has unique inefficiencies so, by considering multiple indicators, these inefficiencies can be mitigated by other indicators, leading to more reliable risk assessments. In conclusion, relying on multiple credit risk indicators, ensures a more robust and nuanced understanding of credit risk, reducing blind spots and enabling proactive decisions.
To learn more about the Credit Analytics models, visit our website here.
1 Semiconductor Industry - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029), Global Information, Inc. As of: February 15, 2024.
2 Semiconductor Industry Market Size, Mordor Intelligence. Source: https://www.mordorintelligence.com/industry-reports/semiconductor-industry-landscape/market-size.
3 Semiconductor supply chain resilience and disruption: insights, mitigation, and future directions. International Journal of Production Research. As of: August 13, 2024.
4 See “Intel Corp. Rating Lowered To 'A' On Operating Challenges And Deteriorating Financial Position; Outlook Negative” published by S&P Global Ratings at https://www.capitaliq.com/CIQDotNet/CreditResearch/SPResearch.aspx?DocumentId=53924963&From=SNP_CRS&srcPgId=1755.
5 RG+ will be released in Q1 2025.
6 Holistic credit risk assessment of Nvidia & Intel based on RiskGauge+ model
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