The last few years have seen a meteoric rise in the use of digital financial services, which is expected to climb even higher as the years go by. More and more people are beginning to prefer online financial transactions over exchanging paper currency. As a result, every financial industry, be it banking, stock exchange, cryptocurrency etc., is rolling out its own app, website, and other digital applications. However, this trend is swiftly catching up with the non-financial sector as well. So, with a multitude of different applications out there, every individual and company are looking to make their application both competitive and unique. Thus, financial technology (fintech) and software development services have become the need of the hour.
Now, one could argue that there are several programming languages including C#, C++, Java, Python etc. that could help build a fintech application. So, why single out Python? The answer lies in the three most important requirements of any fintech software, i.e., it should be secure, have a good performance, and be open to customization. These key aspects of the finance and fintech industry have made Python the most popular choice among its programmers for the following reasons:
Ease of Access and Support
Python is much easier to learn, when compared to other languages, thanks to its simple syntax that is quite close to the English language. It also has a wide variety of open-source libraries that are constantly developing, which in turn provide access to numerous frameworks and tools. Simultaneously, its large community of users not only keeps the language up to date but also provides tech support whenever a fellow programmer needs it. This results in a bug-free and error-free software that reaches the consumer faster than a software made using an alternate programming language, which means that along with being easily available, Python programmers deliver software that are more stable and reliable than any counterparts.
Security and Features
Most Fintech software utilize and have access to huge quantities of sensitive information like identity proofs, bank account details etc., making it a treasure trove for hackers. These personal and financial data, if leaked, could have disastrous consequences for both the customer and the company. Therefore, one of the main focuses of Fintech solutions is to make this software as secure as possible in order to protect customer privacy. Python, owing to its vast range of libraries and pre-existing frameworks, not only allows for adding and programming these security features at a pace much faster than other languages but also provides the programmer with the required tools to experiment with, and develop new and improved security solutions. The seemingly endless supply of libraries provided by Python is a boon for any programmer as it has a little something for everyone. One could potentially find the right library for the work at hand no matter how complex or unique, irrespective of the field, be it finance, gaming, or any other.
Performance and Uses
Fintech software are heavily data-driven and reliant on mathematical calculations, both of which can easily be integrated into Python. Along with this, Python also facilitates the incorporation of data analysis and machine learning, which are useful for making financial market predictions and developing personalized consumer applications. In addition to its compatibility with finance professionals’ use of MATLAB, a programming and numeric computing platform, Python also allows for the creation of formulas and algorithms capable of performing financial calculations for the user. Python can also be used to develop data visualization tools that have the ability to represent complex analyzed data in the form of easy-to-understand charts, graphs, and diagrams that can then be used for spotting patterns, determining trends, and making data-driven decisions – financial or otherwise. Last but not least, Python supports cross-platform availability, which makes software built using Python available to a broader audience, whether they be Android, Windows, MacOS, iOS, or Linux users.
Flexibility and Customization
Since a data breach is every fintech company’s biggest nightmare, they need to constantly check for and update their applications based on the regularly changing rules and regulations regarding data privacy. At the same time, during the prospect of expanding the reach of an existing fintech application, it will have to be adapted for the international rules that govern the country, region, or area where the application is to be introduced. Hence warranting, that every fintech application needs to be developed with room for customization and flexibility. This is provided for by Python, as it enables easy changes with the help of its variety of libraries and tools that are in a constant state of development, keeping everything up to date and easy to access. As this is a unique characteristic of Python, it makes Python’s abilities virtually limitless, meaning that it has no end to its growth potential while opening the door for limitless possibilities.
To sum up, Python is a continuously growing programming language that is rapidly gaining popularity with the community of fintech programmers due to its thousands of libraries, frameworks, and tools that make coding, developing, and testing any fintech application much more convenient when compared to other programming languages. While most applications or features of said applications do not have to be coded from scratch, making the process both faster and easier, the same libraries and frameworks can also be used to create new and unique features for better competitive results. Although the latter may prove to be a little difficult sometimes, it can always be sorted out with the help of a software development company, taking advantage of their experience and expertise for a better resultant software. Therefore, Python is not so slowly but steadily climbing the ladder for the coveted title of the powerhouse behind the finance sector for its support for fintech applications.