How to Build a Unique Technology for Your Fintech Product with Python
Fintech can be directly translated to the new technology of fueling up banking, insurance, investing, and basically, anything that relates to finance, that is, with the intention to deliver innovative, sleek and customer-friendly financial products.
Although you might be familiar with the idea of FinTech ventures, you might not know about their correlation with the rise in popularity of Python.
When you take a closer look an at these two timelines (below), you will realize that the demand for Python developers began to evolve just around the time when FinTech ventures started to appear on the financial market.
So these two are bound together and with good reason.
Why Python makes a perfect fit for your FinTech product
Simply put, Python is an excellent programming language for the financial sector.
In banking, economists already use it to solve pricing issues, trade management, risk management and more. Python is compliant with the nature and demands of the finance industry.
Of course, it’s not the only feasible technology for your FinTech product. You can go for other, more traditional, technology stacks such as Java or C++, but before you make things a little more complicated than they already are, understand that you have solutions that let you develop software more efficiently, faster and more intuitively.
Python offers simple syntax, and it’s easy to understand for non-techies
Python is well-known for its simplicity, and that’s a massive benefit because FinTech software development can be challenging.
FinTech founders have special regulations to deal with, such as:
- Provide the highest level of security to protect customer accounts and deposits
- Align with the state-level rules for the specific country
- Integrate with specific services that make essential transactions possible
- Integrate with traditional financial institutions that allow fintech solutions operate
- Connect relevant APIs to enable smooth data transfer
All these factors are critical to building a robust, flexible and trustworthy fintech product that will attract, convert and retain end-users. So why not making things lighter by deploying an easy to code language?
Apparently, with ten lines of Python code, you can do as much as 20 lines of Java!
This cuts coding in half.
Moreover, shorter code translates to the lower risk of error, what is in your business is highly desired.
Python is readable, and everyone can learn it. And that’s great especially when you have different specialists — techies and non-techies — involved in software development, and you care to have everyone on the same page.
Python makes the code easier to explain to your clients, and they can better understand how the development process is moving forward.
Python stack technology takes you to market quicker
One primary factor that distinguishes FinTech venture from traditional banking is its flexibility and ability to adapt to always growing consumer expectations.
For this reason, your technology stack must be resilient, offer a stable framework open to the upcoming upgrades.
And this is precisely what Python offers — quick deployment and less required code. This matters since the most expensive resource for a company now becomes its employees’ time.
Side note: See how productive programming languages are:
Although Python might not be the fastest language regarding performance, it can work well when you consider the time to market.
What does this mean for you?
Let’s say, an MVP version of your product is finished with the use of Python/Django stack, parts of your code can be still adapted. You can play around, changing lines of code, writing new ones to improve your features and expand your solutions.
As a result, Python lets you move fast with your product development. And the sooner your FinTech goes into the market, and then the sooner you collect feedback to develop further optimizations, identify your market fit and succeed.
Python offers open-source libraries
Another substantial advantage of Python is open-source libraries available for API integrations. They save you time when developing product and let you analyze data more efficiently because you don’t need to build everything from scratch. And fintech solutions require many third-party integrations.
This means that once you verify your integration through API, you can transfer and analyze user (and organization) data automatically and without any limitations.
Side note: Here is your list of Python libraries popular in the FinTech sector:
- Finmarketpy — analyzing financial markets
- NumPy — scientific computing
- Pandas — data analysis
- Pyalgotrade — algorithmic trading library
- Pybitcointools — commonsense Bitcoin-themed Python ECC library
- Pyfolio — portfolio and risk analytics
- Pynance — retrieving, analyzing, and visualizing data from stock and derivatives markets
- Pyrisk — financial risk and performance
- Quantecon.py — quantitative economics
- Scikit-learn — machine learning algorithms
- SciPy — scientific computing
- Zipline — algorithmic trading
Anything handy for you?
The call for being unique
There are two conflicting forces in the European world of finance. On one end there are young and demanding customers, who are too busy to visit a traditional bank and spend hours in a waiting line. They move quickly and call for solutions that will let them manage payments rapidly.
On the other end, there are traditional banking, investing, and insurance institutions with the outdated, super complicated systems and regulations that are almost impossible to adjust to the requirements of today’s digital era.
For these reasons, FinTech ventures, despite the strong consumer demands, still have to grow on black holes in the financial sector. And unfortunately, the old-school bureaucracy won’t evolve that easy.
Therefore, you should bet all your forces on building unique technology for your FinTech product with Python and make it too innovative to be ignored and too simple to be misunderstood.
And this is where Python might be your answer.
PS: I believe that this article will convince you to base your FinTech product on Python stack. But if it’s not yet, then feel free to ask your question in the comments below. And I will get back to you on it.