Why Python for banking?

 

Python is growing in popularity year by year.


Python is fast and simple

There are other options like (Golang) but in reality, Go is more often than not too simple to power and to be used in major banking platforms as it is often lacking functionality for proper security implementation and complex staff management. Python, on the other hand, does not make sacrifices when it comes to a choice between simplicity and security and that’s why it works so great in the financial industry. Python is also used due to its math syntax as it allows for more flexibility when it comes to calculations and other math-related tasks.

Proven track record in fintech

There is a variety of already developed solutions. Therefore there is a wide variety of libraries that can be used to apply the best practices. So that saves a lot of time because one can use already existing libraries instead of writing the code from scratch. These libraries, for example, help to simplify the development process by visualizing the massive amounts of data thus enabling easy statistical calculations based on this information. It is also used to write software for Cashpoints/ ATMs as well as to enhancing payment processing.

Cryptocurrency and market analysis

It is easy to conduct various market analysis using Python. For example, one can build scripts that will analyze the current information on the market and make intelligent predictions based on that. For example, a tool called Anaconda provides information about real-time cryptocurrency prices and analyze it automatically. Most web platforms analyzing cryptocurrencies are built using Python. Python is now often the main language used to build pricing, risk, and trade management platforms for investment banks. This can then be used to trade stocks, commodities, FX, etc. While the core is often built using C++, due to legacy code, Python classes and decorated methods are more and more being used to create dependency graphs for the business logic and applications even in bigger historic banks.

Trading

Stock markets also require a lot of analysis and Python can currently handle it better than others. For example, developers can easily define the winning trading strategies and get recommendations based on the future conditions of one or another market. Such software can be created not only Python but Django framework based on Python.

Examples:

eFinancialCareers (employment website from the Wall Street Journal) added Python to six best programming languages for the banking industry.

A live example of the Python capabilities is a well-known service called Venmo that has been and is being built using this language. It is a  rather a full-featured payment system with many of the social media features that are currently more and more popular in banking or payment related apps. Payment services were developed using the before-mentioned Django framework.

Stripe

A USA-based company that has developed a solution for receiving and processing of payments. It is mostly used for mobile payments processing and Stripe system is considered as one of the top solutions along with Braintree and PayPal. Only founded in 2011, it has achieved massive success. It is used by many mobile apps, even Facebook.

Zopa

P2P lending platform created in 2005. Its aim is to offer alternative personal financing compared to banks and it allows to take a loan, repay a loan, sign many documents - essentially everything you could do during a  regular loan process. The total amount of loans made using Zopa has 2 billion British pounds (£)

Dashlane

Dashlane is one of the leading user-friendly password manager as well as a secure digital wallet that provides a high level of security and protection.

Kroodle

The site belongs to one of the largest Netherlands insurance company. The system includes various insurance types, each with its own parameters display the price for the required insurance services, thus the creation of several data entry forms was necessary. In Kroodle, the users can view, buy, edit, cancel their insurance and even invite their Facebook friends and get bonuses based on that thanks to the integration of the Facebook API.

J.P.Morgan

Python is the core language for J.P. Morgan’s Athena program. Kirat Singh (a former MD at Bank of America Merrill Lynch) has said that everybody in J.P needs to know Python. JP Morgan is trying to move all of their stack over tp Python.

Bank of America

Python is the core language for Bank of America’s Quartz program. Singh has said “Everyone at J.P. Morgan now needs to know Python and there are around 5,000 developers using it at Bank of America. There are close to 10 million lines of Python code in Quartz and we got close to 3,000 commits a day.” Bank of America actually has over 5,000 Python developers, with over 10 million lines of Python in one project alone

PayPal and eBay

A long article has been published by the lead developer in Paypal/eBay that goes in depth of various myths related to using Python as well as bringing in multiple examples of Python utilization in multi-billion dollar systems: https://www.paypal-engineering.com/2014/12/10/10-myths-of-enterprise-python/#python-does-not-scale

finance with python

The list of the most popular languages in FinTech (Source: HackerRank)

 Hours it takes to solve a problem in code on average (Source: connellybarnes.com)

Interested in knowing more? Get in touch with our industry expert Karl Õkva to discuss the details and schedule a e-meeting: karl@thorgate.eu or Schedule a meeting with Karl!

Want to read more about Python in Fintech? See this: Choosing the right stack for your Fintech Solution

Wondering if a custom-built software is worth it? This may make the decision easier: To Build Or To Buy

Or just get in touch with us and the industry experts can help you with your questions!