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Why Python Is The Best Choice for Fintech Products

And the majority of the products that come out of these investments are created using the Python data science ecosystem. To know more about how and why Python is used extensively in fintech and finance development, let us go through this blog.


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Charles Roy

a year ago | 4 min read

How Can One Use Python for Financial Institutions?





Python is one of the best general-purpose programming languages which
means that it is designed to create various software solutions. It
comes with various frameworks and libraries that Python developers can
use. The simple and flexible Python language also comes with advanced
security features. This proves that Python is an effective tool for
projects in data analytics, scientific computing, artificial
intelligence, and web applications.
Python online course is recommended to learn python for gaining expertise.





Besides, there are many different uses of Python code in the
financial services sector. Python is the programming language that can
successfully create digital payment solutions (Stripe), f banking
platforms (Revolut), financial analytics software (Kensho), stock
marketplaces (Robinhood), and cryptocurrency payment processing system.





Some of the most popular reasons why Python can be the best programming language for financial services.












Why Python Programming Language For Fintech Products?





1. Easy to Learn





Python is a general-purpose, open-source, high-level programming
language that is easier to learn and use than it is to elaborate the
first half of this sentence. But understanding it can give you proper
Python knowledge. So here we go –





  • General-purpose programming language means that it can be used
    by any developer to create virtual programs. The means that they can
    even create their own projects is they become familiar with Python
    development.
  • Open-sourcemeans that Python is made to be used,
    edited and redistributed by any web developer for free. This is why
    Python is so popular amongst technical computing experts.
  • High-level
    programming languages are able to operate strong abstractions that are
    similar to human languages. This makes Python easy to learn and write
    for experts working on development projects.





These are the qualities of Python that make it more accessible and easier to learn for financial services providers.



















2. Very Popular





When it comes to Python, the talent pool is one of the most important
advantages. As of June 2021, Python lists at close second place in the
TIOBE Index which means that the popularity of this scientific and
technical computing language is increasing. And there is no doubt that
it is going to take the first place and be in a position where only Java
and C have been before. Besides, it has become one of the most favorite
languages for developers who have to work for finance and fintech. It
is also popular amongst people who are not professional developers. This
is because of the simplicity of its code.





3. Huge and Vibrant Community





Nowadays, in the modern software development world, it’s people who make the programming language great.
When a programming language reaches a certain level and becomes
popular, it becomes easier for developers to code with the help of their
knowledge and support from the community.





Python is no different. It comes with a user base that is vast and
diverse. Python has the most dedicated enthusiasts in its community.
There are more than 215,000 members on Python’s official server and
1,744,000+ questions tagged [Python programming language] on Stack
Overflow as of June 2021. With this many Python developers actively
working together in solving various issues, there is a big chance that
their knowledge and documentation will help other professionals who are
trying to create Python-based solutions.





4.   Perfect for Machine Learning and Artificial Intelligence





You all know that Machine Learning is a form of Artificial
Intelligence project that utilizes statistical models and algorithms to
enable predictive analytics by continually receiving new sets of data.
This is the reason why Python is commonly used in creating fintech products
in areas of automated trading, personal finance, cyber-security, risk
management, and customer service. Besides, there are various other
reasons behind selecting Python for any machine learning project. For
instance, development speed, code readability, execution speed, and
supportive communities.





5.   Easy to Market a Python-based Software





When it comes to developing ATM software or any other financial
applications, Python is surprisingly fast. It comes with libraries like
NumPy and frameworks like Django that enable the talented Python
developers to create from already existing blocks of code rather than
starting from scratch. This makes the development process faster and
results in having a competitive advantage in the financial markets.
Besides, Python applications are also highly scalable when they are
created on frameworks.





6.   Extensive Python Libraries and Tools





Fintech startups prefer Python as it comes with a wide range of
libraries and tools that enable the developers to build payment
solutions. Besides, there are some additional Python-based tools that
add to the development and make it easier for the developers to work
with this technology. And as products in the financial industry require
many third-party integrations to make the solution accessible, secure,
and more functional, Python’s libraries can be of much use.





Conclusion





As seen in this blog, Python is one of the most popular technologies
when it comes to the financial sector. Since 2007, it has started to
gain some momentum in the market and today it is a very important part
of the tech stack. Many organizations within the fintech industry are
using it to create fintech solutions. And the main reasons behind it are
that Python comes with a fantastic community for developers, extensive
libraries, tools, and reliability. All of these are very essential for
creating a perfect digital solution in the fintech sector.

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