There are companies that do a combination of things: Real-time trading (manual, semi, auto), pricing (model-driven, or sourced), risk-management, etc. They can either provide their own prices using models, or apply prices from partners. The business is usually separated into discrete units which feed into each other, and outward to partners/customers.

Yes, exchanges support real-time trading, but not every company has all their models running in modern paradigms. It's not uncommon to find companies that run multiple VMs for the sole purpose of... running Excel calculations. Yes, this is exactly what it sounds like. A server that has a several, multi-meg Excel files in memory with external APIs that plug values into cells and read outputs. As I said, within the grand scheme of things, for sports who still run on legacy models, this is a major bottleneck. Remember, many of these companies were started in the 90s, and that's when these models were created. The people who created them are usually swallowed up by the financial industry and now come with a hefty price tag. So the question for the business is "Do we spend millions recreating these proven models and run the risk of them failing? Or do we simply just add another VM?"

At my company things have slowly started changing, but the new models (written in F#) still need a lot of work.