S&P Global

On Sept. 1, 2026, Bloomberg reported that S&P Global is looking at spinning off its Market Intelligence desktop platform CapitalIQ. Before the news, shares were down 1.6%; after the report, they rose as much as 4.3%; shares ended the session up 1.0%.

Why it matters: Given that the spinoff is worth "high-single-digit billions of dollars," we view the 2.6-percentage-point move (representing $3.3 billion in market value) as large. To us, this suggests that the market applies a conglomerate discount to S&P Global's valuation. This news comes as S&P reworked its reporting structure and leadership in Market Intelligence earlier this year. We see this potential move as S&P attempts to separate its interface business from its data business. The last time S&P Global broke out its desktop revenue was in 2024 ($1.17 billion). We generally believe the desktop business was growing slower than Market Intelligence overall. With FactSet trading at an enterprise value/forward sales ratio of about 4.8 times, the high-single-digit billion valuation looks ambitious to us. It’s not clear from the article whether any adjacent businesses, such as Visible Alpha, would be included in the spinoff.

The bottom line: As discussions are in the early stages and a theoretical spinoff would represent less than 8% of the firm's market cap, we are maintaining our Morningstar Economic Moat Rating of wide and $505 per share fair value estimate on S&P Global.

Between the lines: In this age of AI, we think S&P Global’s management views interfaces as less strategic, even if they are important to customers. We think it’s likely that S&P does not want to compete on interfaces. While separating the interface from the data layer could sacrifice vertical integration benefits, a separation could reduce channel conflict with upstart providers. Today, competing interface providers and new entrants such as AlphaSense, Quartr, and Tikr may be reluctant to use S&P data because S&P’s CapIQ is a direct competitor.

After updating our model, we raise our fair value estimate on S&P Global to $525 per share from $505 as we tweak our ratings margin assumptions higher from higher productivity. In particular, we think the firm can keep a lid on headcount as AI enables the firm to rate debt more efficiently. Our fair value estimate is based on discounted cash flow analysis and equates to about 26 times our 2027 non-GAAP earnings per share estimate. We continue to expect S&P to generate high-single-digit revenue growth in ratings through the cycle, driven by pricing and nominal GDP growth. We note that ratings revenue growth has been topsy-turvy historically as issuance levels have been volatile.

For market intelligence, we expect about 6% organic revenue growth driven by strong retention, new products, and market growth, which is in line with historical patterns. We believe that higher oil prices over time, coupled with pricing power, can lead to growth of around 8% per year in 2027-30 at S&P Energy though the near term might be weaker from Iran War-related disruptions. We see total index revenue growing 7%-9% per year after 2026, driven by growth in ETF AUM in the low double digits, partially offset by pricing compression.

By 2030, we expect non-GAAP operating margin to be about 55.7%, about a 500-basis-point increase from 2025. We attribute the margin expansion to revenue growth and continued expense discipline as well as the divesting of lower-margin Mobility Global (which accounts for roughly 100 basis points of margin expansion). Specifically, S&P Global’s businesses typically have limited variable costs, and thus our high-single-digit organic revenue forecast should allow for operating leverage.

We believe S&P Global's well-established benchmark businesses warrant a wide Morningstar Economic Moat Rating based on intangible assets and network effects.

Credit ratings provide value to bond issuers (such as corporate issuers) as well as bond investors, creating a network effect. Bond issuers value credit ratings from Moody's and S&P because of their wide acceptance among asset owners and asset managers. This is particularly important in cross-border bond issuance deals. While a local country's domestic rating agency could have value for its domestic bonds, a rating from a Big Three firm is critical for a cross-border marketed security, as global investors desire broad comparability across global bonds. For example, an investor wants to know that a B+ rating for a company in California is similar to a B+ rating for a company in Chile or a B+ rating for a company in India.

This broad acceptance makes it essential for corporate issuers to get a rating on any debt they issue. By getting a bond rating from a market leader such as S&P, the bond issuer pays less in interest (often 30-65 basis points in savings per year). The cost of a vanilla corporate bond credit rating costs around 8 basis points and is typically much less than the underwriting fees and legal fees (50-100 basis points combined).

It's not just bond investors and bond issuers who value credit ratings. In our view, acceptance among index providers and government regulators also supports the rating agencies' wide moats. For example, the Bloomberg Barclays US Aggregate Bond Index, which among other uses serves as the index for the over $300 billion-plus BND exchange-traded fund, only considers ratings from either S&P, Moody's, or Fitch. Among banking regulators, rating agencies are used extensively to determine a bank's capital adequacy. Last, as the number of ratings increases, the value of ratings research subscriptions sold to buy-side investors increases.

Credit rating agencies such as S&P have built a moat through intangible assets as well. The incumbents are advantaged by their multidecade records, which allow investors to see how credit ratings performed. For example, it would be difficult for a new player to establish what the absolute and relative probabilities of a B versus BB versus BBB defaulting are over the next 10 years without sufficient sample size and time. Another hurdle for a new entrant would be establishing management relationships with the thousands of companies that issue debt. Given the strong record of incumbents, corporate management teams are unlikely to find much value in investing time and resources with another ratings provider.

Regulations provide another hurdle. To receive a nationally recognized statistical rating organization designation (which bestows many advantages) from the Securities and Exchange Commission, the agency must be nationally recognized. Even though the number of firms with an NRSRO designation has increased to about 10 since the introduction of the Credit Rating Agency Reform Act of 2006, we believe the network effect has been strong enough to result in limited traction for other rating agencies.

S&P has been able to leverage its moat to obtain solid pricing power, typically around 3%-4% per year. In 2026, S&P's rack rate for corporate finance ratings was 8.35 basis points, compared with 6.25 basis points in 2016 and 4.25 basis points in 2007, which implies fee compound annual growth rates of 3% and 4%, respectively.

S&P Dow Jones indexes has built a strong moat with its flagship benchmark, the S&P 500 index. S&P monetizes its indexes in primarily three ways: index subscriptions, asset-linked fees, and transaction royalties on exchange-traded futures and options. Active asset managers pay to benchmark performance against an index. Index benchmarks are critical to asset owners, asset managers, and consultants, which often have little incentive to switch. An asset manager may prefer to be indexed against the Russell 1000, but if asset owners and consultants prefer the S&P 500, the asset manager would risk outflows. The largest ETFs in the US are based on the S&P 500 index, and we believe S&P Dow Jones has strong brand awareness among investors. Index switches tend to be rare in the ETF space and don't always move to a low cost for the provider. Finally, S&P generates trading royalties from exchange-traded derivatives, notably S&P 500 index futures on the CME, as well as S&P 500 index options and VIX options on the Cboe. Because of high trading volume, these index derivatives benefit from a network effect as they have the most liquidity.

We view Platts, which is part of the Energy (formerly Commodity Insights) segment, as essentially an index business for certain commodities. Similar to how the S&P 500 dominates US large-cap equities and MSCI dominates international equities, typically one benchmark dominates a certain commodity. Moreover, Platts' prices are used in long-term contracts, thus guaranteeing the use of its prices for a certain period.

Commodity switching by market participants tends to be rare and is not usually driven by pricing. Rather, the infrequent switches we have noted seem more the result of concerns about price assessment volatility or methodology.

We regard market intelligence as a less-moaty business. Market intelligence includes Kensho data and platforms. Here, competitors such as Bloomberg, FactSet, and LSEG are more formidable and the rise of artificial intelligence may alter business models. We view enterprise solutions as an array of data, software, and workflow tools from legacy Markit.

Ratings revenue, which has high incremental margins, has often surprised to the upside, such as in 2020, 2021, and 2024. In addition, refinancing walls could support stronger than expected issuance.

The spinoff of Mobility (Carfax) may strengthen management's focus and accelerate organic subscription revenue growth.

S&P Global's benchmarks are difficult to displace and value-based pricing could result in a greater than expected pricing power and margin growth.

Higher interest rates, corporate deleveraging, and increased spreads could lead to a decline in bond issuance, which would weigh on ratings revenue. Notably, spreads in 2024 and 2025 for high-yield were lower than usual, indicating relatively loose credit conditions.

Market intelligence faces a variety of competitors such as FactSet, LSEG, and Bloomberg, and a tougher macro environment could elongate sales cycles. Also, the rise of AI could lower the barrier to entry for competitors.

The rise of private credit poses a challenge for rating agencies, as private credit is often unrated.