As the banking industry evolves, more financial institutions are developing software to enhance customer experience, increase operational efficiency, and stay competitive. With its flexibility, simplicity, and robustness, Python has become a top choice for building banking applications for various reasons:
Simplicity and Security
Python is known for its simplicity and ease of use, making it a popular choice among developers. However, its simplicity does not come at the cost of security. Python has robust security features that make it suitable for building banking applications requiring strict security measures. Additionally, Python's syntax is highly compatible with mathematical functions, allowing developers to handle complex calculations, a critical feature in the finance industry.
Proven Track Record in FinTech
Python has a proven track record in the fintech industry, making it an ideal choice for building banking applications. With a wide range of pre-built libraries and tools available, developers can save time by using existing solutions rather than building software from scratch. These libraries, such as Pandas, NumPy, and SciPy, can help developers handle massive data sets, visualize data, and conduct statistical analyses. It is also used to write software for Cashpoints/ ATMs and enhance payment processing. Python's extenPython'ssystem allows developers to leverage existing solutions rather than building everything from scratch, significantly saving time and resources.
Cryptocurrency and Market Analysis
Python is an excellent choice for building applications that require market analysis and prediction, such as trading platforms. With Python, developers can create scripts that analyze market data in real time and make intelligent predictions based on that data. For example, a tool called Anaconda provides information about real-time cryptocurrency prices and analyzes it automatically. Python is also used to build platforms for pricing, risk management, and trade management 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 allow for the easy creation of dependency graphs for business logic or applications, even in larger historic banks.
Trading
Python is highly suited for building software for stock markets, enabling developers to define winning trading strategies based on market trends and future market conditions. For instance, Django, a popular Python-based framework, is used for building trading platforms and stock market analysis software.
Real-life Examples
eFinancialCareers (employment website from the Wall Street Journal) added Python to the six best programming languages for the banking industry. Several prominent companies and financial institutions like J.P. Morgan, Bank of America, PayPal, and eBay have integrated Python into their software development projects. Solutions like Venmo and Stripe, also listed below, are built with Python, too.
Venmo
A live example of Python capabilities is the well-known service called Venmo, which has been and is being built using this language. It is a rather full-featured payment system with many social media features that are increasingly popular in banking or payment-related apps. Payment services were developed using the aforementioned Django framework.
Stripe
A US-based company that has developed a solution for receiving and processing payments, Stripe is mostly used for mobile payment processing. Stripe system is considered 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, including Facebook.
Zopa
P2P lending platform created in 2005, Zopa aims to offer alternative personal financing compared to banks, and it allows you to take a loan, repay a loan, and sign many documents - essentially everything you could do during a regular loan process.
Dashlane
Dashlane is one of the leading user-friendly password managers, as well as a secure digital wallet that provides high security and protection.
Kroodle
The site Kroodle belongs to one of the largest Netherlands insurance companies. The system includes various insurance types, each with its own parameters displaying the price for the required insurance services. Thus, the creation of several data entry forms is 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 has become a core language for J.P. Morgan's AthenMorgan'sm and Bank of America's QuarAmerica'sm, with over 5,000 Python developers in the latter. 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 to Python.
Bank of America
Python is the core language for Bank of America’s Quartz program. There are close to 10 million lines of Python code in Quartz, and they get 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 on 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
Other sources:
- 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)
Conclusion
There are alternative options to Python, such as Golang, but in reality, Go is more often than not too simple to power and to be used in major banking platforms as it often lacks functionality for proper security implementation and complex staff management. On the other hand, Python does not make sacrifices when it comes to a choice between simplicity and security, and that’s why it does so well 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.
Python's simplicity, security, and wide range of libraries and tools make it an excellent choice for building banking software applications. With its proven track record in fintech and its ability to handle complex calculations, market analysis, and trading, Python can help banks enhance customer experience and improve operational efficiency.
Interested in knowing more? Get in touch with our industry expert Karl Õkva to discuss the details and schedule an e-meeting: karl@thorgate.eu or Schedule a meeting with Karl!
More like this:
