Python development

The Fintech industry uses Python as one of its most popular technologies. Some of the biggest names in technology like PayPal, Stripe, and Square, are using it. Find out what Python is, why it’s used in Fintech, what types of industry products you can create using this language, and examples of successful solutions using Python.

Stay on this page to explore everything about Python in Fintech.

The Fintech Industry and its Products are facing a number of technological challenges.

Here are some of the many challenges that Python could help resolve:

Software security

People are cautious about moving their finances online because of concerns about software security. The Fintech sector is prone to cybercrimes quite often since hackers can easily make money by stealing money from the user’s bank account and selling data on black markets. Hundreds of millions have been stolen in these attacks.

Python makes it easy to configure authorization levels and encrypt data. Many resources are available on making Python Fintech solutions more secure, making the process even easier.

Integration with different services and tools

Instead of building separate systems, Fintech solutions are often integrated with other services to create the best customer experience. For instance, apps for budgeting often require integration with banking, or insurance systems typically require integration with numerous insurance providers. Connecting everything in a secure, trouble-free manner can sometimes be a challenge.

Python can do this for the providers of financial services through technology.

Problems with the algorithms

Many different mathematical operations are carried out by Fintech solutions at the same time, and it is difficult to build software that can handle that many different operations simultaneously.

All other languages pale in comparison to Python here. Its ease of use, quick conversion of values to parameters, and numerous libraries for data and math have all made it a favorite of mathematicians and data scientists.

Learning Python is easy and the Syntax is Simple

The simplicity of the language allows Fintech developers to focus on the software structure rather than the language itself. With Python, you can also collaborate more easily since almost everyone can understand what you are writing.

In addition to its simplicity and shortcode length, Python can also lead to a faster time-to-market, helping to reduce the overall cost of your project.

Python works with Django

Together, Python and Django ensure quick coding and easy access to data management tools.

Django eliminates the need to write all the code from scratch. For example, there are many reusable pieces for authorization and management tools. As a result, Python developers can focus more on essential and complex parts of the software.

With Python you get access to many libraries

Libraries are among the many tools that aid in solving popular problems, pulling code, and establishing documentation. Numerous libraries exist in Python, many of them tailored to economists, data scientists, and mathematicians. It seems to be the perfect language for finance.

Fintech libraries for Python include SciPy, PyFolio, FinmarketPy, Pyalgotrade, Pandas, and NumPy.

Here are some of the best Fintech products that were created thanks to Python

Robinhood

The Robinhood platform allows traders and investors to invest without paying commissions. With powerful analytics, it is an excellent tool for both beginners and experienced traders. In addition, the platform offers free educational content teaching basic concepts about trading and investing, and notifies users of market news and trends.

Additionally, Robinhood supports cryptocurrencies including Bitcoin, Ethereum, and Dogecoin.

Venmo

Venmo operates as both a social network and a platform for transactions. The service allows users to link their bank accounts, debit or credit cards, or even issue Venmo cards.

Affirm

Affirm represents the current trend of “Buy now, pay later”. When a user chooses Affirm at checkout, they choose their payment schedule and pay the following month at their own pace. In contrast to credit cards, you only pay for what you need, you see the interest amount upfront and there are no late, penalty, or annual fees, and the interest is not compounded. Because of its simplicity and transparency, Affirm has become the choice of many.

Stripe

Stripe is an online payment service. By using it, small online retailers can accept credit and debit cards without having to know any coding. In order to integrate more powerful payment processing tools, bigger companies need the help of a developer. Right now, it is possible to invoice freelancers and independent contractors offline and create invoices for freelancers.

Final words

Based on what we covered so far, Python is an excellent choice for building Fintech products since it offers numerous industry-specific features such as security, integration, and algorithm creation.

In addition to the simple syntax, this technology works with Django and offers an abundance of libraries, as well as great capabilities relating to machine learning.

Python is one of the world’s most popular high-level programming languages. It conquered the third position in the TIOBE index in 2019, and its popularity keeps on rising, reaching an all-time high in October 2020 at 11.28%. Its popularity among programmers is because it is perfectly suited for machine learning, artificial intelligence, and web development. Python ranked as the second most sought for language according to Google’s search trends for 2019. Stack Overflow’s survey ranked Python as the fastest-growing programming language on the mobile development market.

The choice of the programming language you use depends on various factors: what the purpose of your product is, what is its function requirement, what security needs to be in place, etc.

So, is Python a good fit for your next project?

In 2018, Python was rated as the #1 programming language. Its popularity has also increased over the years. Much of this increase has to do with its large number of libraries that allow for both machine learning and artificial intelligence. There is also a draw to Python embedded versions that can be found in microcontrollers, as well as Python’s ability for big data analysis.

Python is an easy programming language to learn and has a low entrance barrier. Beginner developers are able to easily learn the language and begin using it. The data visualization libraries available in Python also makes it easy for users to comprehend and visualize complex data.
Python supports different programming styles. If you ever decide to change how you approach development, Python will be able to keep up. Unlike Java, Python is a less-limited programming option that fully supports various programming styles like procedural, functional, or even object-oriented.
Python provides its users with lots of open-source libraries. These libraries help to streamline the process of developing programs. Both time and money are saved by using these libraries. Python libraries hold a significant amount of pre-written coding options, so developers don’t have to waste any extra time writing the basics.
Python is really helpful in creating prototypes and MVPs. Its code is efficient, and programmers are able to create the same functionality using fewer coding lines when compared to any other computer language. If you ever need to test a product on its audience or quickly show investors your ideas, Python is the go-to option.

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