It rates nations, names your index fund, and prices your gasoline.
It scores the debt of nations, names the index in your retirement account, and prices the oil in your tank. Meet the 165-year-old data company most people have never Googled.
Almost everyone has quoted S&P Global without knowing it. Say "the market was up today" and you probably mean the S&P 500. Read that a country was downgraded and you are reading an S&P letter grade. Fill your tank and the wholesale price traces back, at least in part, to a benchmark this company sets each afternoon. It is one of the most cited firms in finance and one of the least Googled - a data business hiding in plain sight behind the numbers other people trade on.
The company sells reference points. Not opinions you can take or leave, but the shared numbers that markets agree to treat as the baseline. A rating agency, a stock index, and a commodity benchmark are all versions of the same trick: become the thing everyone else measures against, and you stop competing on price. You start collecting a toll.
01What the company actually does
S&P Global runs four core businesses, each dominant in its own corner of finance. S&P Global Ratings assigns credit grades - the familiar AAA-to-D scale - to companies, banks, and entire governments, and those grades help set how much it costs them to borrow. S&P Dow Jones Indices owns and calculates the S&P 500 and the Dow Jones Industrial Average, along with hundreds of thousands of other benchmarks. S&P Global Market Intelligence sells the data terminals, research, and analytics that analysts live inside all day. And S&P Global Commodity Insights - the business long known as Platts - assesses the prices of oil, gas, metals, and crops that physical traders write into their contracts.
A fifth division, S&P Global Mobility, holds the automotive data and forecasting that arrived with the IHS Markit merger. In 2025 the company said it intends to spin Mobility off into a separate public company, a move to keep its focus on the four franchises it considers core.
02A 165-year head start
The story starts in 1860, when Henry Varnum Poor published a thick book on the finances of American railroads. His argument was simple and, at the time, faintly radical: investors had a right to clear, verifiable numbers before they handed over their money. That idea - independent, checkable financial information - is the seed of everything the company sells now.
Poor's firm eventually merged, in 1941, with the Standard Statistics Bureau, founded by Luther Lee Blake in 1906, to create Standard & Poor's. The S&P 500 arrived in 1957. McGraw-Hill bought the business in 1966 and folded it into a publishing empire, and for decades the whole thing was known as McGraw Hill Financial. Only in 2016 did it rename itself S&P Global, putting the initials it was best known for on the front door.
Poor publishes railroad finances
Henry Varnum Poor makes the case for independent investor information.
Standard & Poor's forms
Poor's Publishing and Standard Statistics merge.
The S&P 500 launches
The 500-stock index becomes the U.S. equity benchmark.
Rebrand to S&P Global
McGraw Hill Financial takes on the S&P name.
IHS Markit merger closes
A $44 billion deal adds vast data assets across energy, finance, and autos.
Martina Cheung named CEO
She succeeds Douglas Peterson on November 1.
03Who pays, and why they keep paying
The customer list reads like a directory of global finance: investment banks, asset managers, hedge funds, private equity firms, insurers, corporations, commodity traders, central banks, and governments. What ties them together is that they all need the same neutral numbers, and it is expensive and awkward to build those numbers themselves.
The flagship data platform, S&P Capital IQ Pro, is a good example of the stickiness. It carries data on more than 60 million private companies and over 110,000 private-equity and venture funds, and analysts use it to screen for acquisition targets, build financial models, and dig through filings. Once a deal team runs on it, switching costs are high. In 2025 the company folded in expanded private-markets datasets from With Intelligence and layered generative-AI tools on top - ChatIQ for plain-English questions, Document Intelligence for reading filings, a Chart Explainer for the graphs.
04The problem it solves
Markets run on trust in numbers. A lender deciding whether to buy a bond, a pension fund choosing what to track, a refiner hedging next month's crude - each needs a figure that both sides of the trade will accept as fair. Producing that figure independently, consistently, and at scale is genuinely hard, and the value only exists if everyone treats it as neutral. S&P Global's job is to be that neutral third party, over and over, across ratings, indices, and benchmarks.
A credit rating is shorthand for risk. When S&P moves a borrower's grade, it can change what that borrower pays to raise money - sometimes measurably, and sometimes for an entire country. The rating is an opinion, but a widely trusted one, which is exactly what gives it weight.
05How it makes money
There are two engines. The first is transactional: the Ratings business charges fees when it rates new bonds and debt issuance, so it earns more when companies and governments are borrowing heavily. The second is recurring: data, analytics, and index licensing are sold by subscription, and index fees scale with the assets that track S&P benchmarks. The combination is unusually durable. In a boom there is more issuance to rate and more money flowing into index funds; in a downturn everyone reprices risk and leans harder on the data. The number is needed either way.
Fees each time a new bond or loan is issued and graded.
Recurring revenue from data terminals, research, and analytics.
Fees that scale with assets tracking S&P indices and benchmarks.
The 2022 merger with IHS Markit, a roughly $44 billion all-stock deal, was the clearest statement of the strategy. On paper it looked like a data acquisition. In practice the prize was proprietary information - decades of energy, financial, and automotive data that a rival could not simply rebuild. Martina Cheung, who helped drive that integration before becoming President and CEO in November 2024, has spent her career on exactly this: turning hard-to-copy data into products people renew.
06How it differs from the alternatives
S&P Global rarely competes on a single front. In credit ratings it sits in the "Big Three" with Moody's and Fitch. In indices it faces MSCI and FTSE Russell. In market data it runs against Bloomberg, LSEG (Refinitiv), FactSet, and Morningstar. In commodity benchmarks it lines up against Argus Media and ICE. Most rivals are strong in one of these arenas. S&P Global's distinguishing feature is that it holds a leading position in all four at once, which lets it bundle, cross-sell, and defend on multiple sides.
The other difference is age. A 165-year record of collecting and standardizing data is itself the product. Newer entrants can build better software, but they cannot go back and gather the history, and history is what makes a benchmark credible.
Think of S&P Global as infrastructure rather than a vendor. Its ratings, indices, and benchmarks are the plumbing beneath decisions across capital and commodity markets - quietly load-bearing, rarely front of mind, and hard to route around.
07What you can actually do with it
For a portfolio manager, S&P Global is where you check a bond's rating before you buy and pick the index your fund will follow. For a banker or private-equity associate, Capital IQ Pro is where you screen targets and pull the financials into a model. For an energy trader, Platts assessments are the reference prices that settle contracts. For a corporate treasurer, an S&P rating shapes the cost of the next debt raise. For a researcher or journalist, the indices and data are the shorthand for how a market or an economy is doing. The through-line is decisions made with a shared, defensible number instead of a guess.
08The state of play
The near-term story is focus. With the planned Mobility spin-off, S&P Global is trimming toward its four highest-conviction franchises and pushing generative AI deeper into its products so customers can ask their data questions in plain language. The bet is the same one Henry Varnum Poor made in 1860 - that markets will always pay for information they can trust - updated for an era where the raw data is infinite and the scarce thing is a number everyone agrees on.