If there were a TV sitcom with programming languages as characters, then the biggest hit among the FinTech crowd would be “Everybody Loves Python.”

But why, exactly, has Python become the go-to programming language for applications across the finance industry? Think power, ubiquity and transparency.

First and foremost, Python is a powerful and versatile language. It’s easy to learn and use, making it an ideal choice for both experienced programmers and newcomers to the field — making it easy for FinTech developers to fill and swap out positions as needed. Python also has a veritable army of developers, who all freely contribute to a vast range of libraries and frameworks that makes every other Python developer’s life that much easier. Python programmers can quickly and easily access a wide variety of tools and resources to help them build high-quality applications — and that network of tools grows day by day.

Python also has a solid reputation for being able to handle large amounts of data — no small thing in FinTech. Financial institutions generate vast amounts of data every day, and Python’s utility in data analysis and manipulation make it a top choice for processing and interpreting lots of data. What’s more, since machine learning has become so essential to data analysis, programmers have leaned into Python’s capabilities for machine learning and artificial intelligence. Python powers applications covering fraud detection, risk assessment investment analysis and more.

Python also plays nicely with others, and is known for its interoperability with other languages and systems. Financial institutions tend to have complex IT infrastructures that include multiple programming languages, legacy systems and third-party software. So Python’s flexibility and ability to integrate with other systems and languages make it a valuable tool for the developers who’ve been tasked with creating applications that can slide in easily into these environments.

Many developers love the fact that Python is an open-source language, free to use and modified and/or distributed by anyone. For companies looking to  save money, this means they can reduce software development costs and make development teams more collaborative. 

Finally, FinTech and financial services are often fans of how well Python lends itself to rapid prototyping and development. Financial institutions are constantly looking for new ways to improve their services and stay ahead of the competition. Python’s ease of use and versatility make it ideal for quickly building and testing new applications and features.

So, in a lot of ways, Python seems to have it all for FinTech devs, from versatility and interoperability to data handling,  as well as being open-source and good for rapid prototyping and development. Corporate C-suite types see a cost-efficient language that can help them make informed decisions about their technology stack and stay ahead of the curve in an industry that doesn’t wait for stragglers to catch up.