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Building a Unique Technology for Fintech Product with Python

Fintech is a maze. It’s a thrilling and extremely complex industry for software development. There are state level regulations, integrations with different services and institutions, bank API connections, etc. to deal with. Another challenge is the high level of trust from the end users required to run finance, mortgages, investments and such. These, in turn, require the highest level of security, functionality, and correspondence with requirements.

What I’m trying to say is that the more unique the software is, the higher it’s valued. Without a properly working and trustworthy software, any financial venture will die down and lose worth. People need financial technology that will last, and I’m going to tell you how we achieved this with Python/Django technological stack while developing fintech products. It’s especially pleasant to say after Python has become the world’s most popular coding language.

Fintech: The Importance of Being Unique

In the world of finance, there are two streams that still coexist. On one hand, there are the millennials who stride gloriously into the future while mastering contactless payments, using on-line banking and all kinds of digital financing services. In an effort to avoid old school bureaucracy, they build their lives in a way that no generation before them did.

On the other hand, there’s the good old traditional financing services. This is a hell of a machine, hundreds of years old, that you can’t stop that easily. Even if it acknowledges the effect that new technology has on finance, it still doesn’t see it as neither as a threat, nor as a worthy competitor.

An attitude like this is especially typical of the most developed countries, such as the G7, which have the most of the money. The most of the old money, I might add. As well as the most people who are ready to operate it and the most highly technological startups. However, the thing is, their financial system is so old and hard-shelled, that it’s not always ready to change.

Deloitte has proven this in their statistics for 2017 that shows exactly how G7 sees and uses financial technology as opposed to the rest of the world. Deloitte researchers note:

“Surprisingly, with regard to mobile payments, 40 percent of executives from the United States expect little to no impact to their industry. With the caveat that the sample
size is relatively small, 7 out of the 17 US banks (41 percent) saw little to
no impact from mobile wallets and other payment technologies, vs. 14 out of 36
(37 percent) of the nonbanks.”

Meanwhile, developing countries have a number of black holes in the financial sector that allow space for growth. These black holes are slowly but surely being taken over by fintech. By doing so, it gives people in these countries more opportunities, like working with
developed countries and getting paid easily and securely. Fintech removes financial borders, and that’s one of my favorite things about it.

Usage of emerging technologies: G7 vs rest of the world (ROW)


No matter how skeptical the G7 is towards fintech, technology continues changing finance. One of the reasons is that technology is more flexible and is able to adapt to new users’ needs, such as the needs and demands of the millennials. With their new habits, their high digital sensitivity, and digital presence, this generation feels the need to be productive every waking moment, can’t afford to waste time, travels a lot, and values financial freedom no matter where they are.

Confirming my thoughts, the Wall Street Journal, for example, says that the ease of payments attracts people that are comfortable with technology and have a busy lifestyle. Users of mobile payments mostly have higher education, work full time, are predominantly male, and are also very active financially. For instance, compared to nonusers of mobile financial apps, they are more likely to have bank accounts, retirement accounts, and/or own homes. Equally, they are no stranger to auto loans and mortgages.

Statistics that the WSJ uses in the article basically show that mobile payment users are more financially active, use a variety of financial products, and earn more than non-users. At the same time, they’re more careless with their expenses, get into debt, and even take money from their retirement accounts. This is why experts expect a whole new niche in fintech – simple tools that will help millennials manage their money better. Millennials who use mobile payments are reported to have a greater risk of financial distress and mismanagement, despite higher incomes and education levels.


In the era of digital disruption, finance has to be especially sensitive towards new customer demands. Will they use your service when it becomes more common and necessary? Can you create a product now that can grow and develop to serve millennials when they grow up and start earning big money? The same as the generation at which the current financial system is aimed. This is especially important when it comes to branches like mortgages, investments, and wealth management.

As I said above, I can’t stress enough how important it is to offer a unique technology that is custom tailored to fit customer needs. So far, it’s impossible to avoid integration with traditional financial and state institutions. You have to make sure your cooperation runs smoothly and that they deem you reliable enough to choose you as a partner; to choose your technology and not someone else’s, or worse, create a technology of their own.

We realized the importance of top-notch technology when Moneypark, formerly a start-up client of urs and now Switzerland’s largest technology-based mortgage intermediary, acquired Defferrard & Lanz and became part of Helvetia. All this occurred because their technological solution and business approach was the most convincing.

How Is Python Used In Finance & Fintech

So where do you get this technology robust enough to withstand stress of worldwide financial perturbations, but flexible enough to follow all the new changes and customers’ needs? We chose to use the Django framework within Python, and continue discovering its power. We’re not trying to say that Python is the savior and the silver bullet, but we do know for sure what advantages Python has for finance.

1. Python/Django stack takes you to market a lot quicker. It’s simple: this combo lets you build an MVP quickly, which increases your chances to find your product/market fit.

One of the advantages fintech has over traditional banking services is its ability to change quickly, adapt to customer demands, and offer additional services and improvements in accordance to the customers’ wishes. To do so, you have to be able to get to market quick, toughen up against real life problems, constantly improve, and grow. This is the only way fintech will be able to compete and/or collaborate with traditional banking and finance.

The technology must be flexible and offer solid ground for numerous additional services. Obviously an MVP is of importance, but the complexity of projects doesn’t always allow to develop it fast. However, the Python/Django framework combo takes into account the needs of an MVP and allows to save some time. They basically work like a Lego – you don’t need to develop small things like autorisation or user management tools from scratch. You just take whatever you need from the Python libraries (Nimpy, Scipy, Scikit-learn, Statsmodels, Pandas, Matplotlib, Seaborn, etc.) and build an MVP.

Another big advantage that Django gives you at the MVP stage is a simple admin panel or CRM – it’s built-in; you just have to set it up for your product. Of course, at the MVP stage, the product isn’t complete, but you can test and easily finish it, as it’s very flexible.

After the MVP is done, this tech stack allows to adapt parts of code. This means that after you validate the MVP, you can either easily change some code lines or even write new ones, if this is required for the product to function flawlessly.

Read: What you need to consider before building a fintech product

Millennials are people who are used to living in a fast-paced world. They feel like they have to be productive every waking moment, and this is what they expect from everyone else and from the services they use. There’s no time for error. Maximum transparency and high-quality service are critical for them, and I don’t think they’ll be letting it go anytime soon.

Let’s say that no matter how much I love Uber, as soon as they make a mistake as little as searching for a driver for too long, I get very annoyed. I’m sure we all expect and deserve better than this. I can’t even begin to describe the panic that takes over people if heaven forbid, Slack crashes.

This is why customer development is so important – a whole generation depends on it. Consequently, the sooner you get your product to market, the quicker you collect feedback and the faster you’ll make improvements. Python programming in finance allows you to do this with your hands behind your back.

2. Python is the language of Mathematicians and Economists. Fintech obviously can’t exist without these two groups, and most of the time they use – wait for it – Python to calculate their algorithms and formulas. While R and Matlab are less common among economists, Python became the most useful programming language for finance, as well as the programming “lingua franca” of data science. Because economists use it to make their calculations, of course it makes them easier to integrate with a Python based product. However, the presence of and communication with the technical partner is nevertheless important because sometimes even pieces of code that are written in the same language are hard to integrate.

3. Python has simple syntax which is easier for collaboration. Becoming the “lingua franca”, in my opinion, was just a matter of time. Thanks to its simplicity and easy-to-understand syntax, Python is very legible and everyone can learn it. Python creator Guido van Rossum describes it as a “high-level programming language, and its core design philosophy is all about code readability and a syntax which allows programmers to express concepts in a few lines of code.”

Not only is it easy to understand for technical specialists, it is for clients as well. As you can imagine, people involved in the development process from both sides have different levels of technical understanding. With Python, engineers can explain the code much easier, and clients can better understand how the development is progressing.

As The Economist says about Python:

“The language’s two main advantages are its simplicity and flexibility. Its straightforward syntax and use of indented spaces make it easy to learn, read and share. Its avid practitioners, known as Pythonistas, have uploaded 145,000 custom-built software packages to an online repository. These cover everything from game development to astronomy, and can be installed and inserted into a Python program in a matter of seconds.”

Which brings us to the next point.

4. Python has open libraries, including those for API integration. Open libraries help develop the product and analyze large amounts of data in the shortest amounts of time, as you don’t have to build your tools from scratch. This can save a lot of time and money, which is especially valuable while building MVP.

As I mentioned, fintech products require a lot of integrations with third parties. Python libraries make integrating your product with other systems through different API a lot easier. In finance, API can help you to collect and analyze the required data about users, real estate, and organizations. For instance, in the UK, you can get people’s credit history by API, which is required to proceed further financial operations. In the online mortgage industry, you also check real estate data and you always need to verify someone’s identity, which is much easier to do with API. By using and combining different libraries/packages, you can get the data or filter it in one click without having to develop new tools for that.

Django Stars, for instance, use the Django Rest Framework to build APIs or to integrate with external ones, as well as Celery to queue or distribute tasks.

5.Python hype is real. Python will continue developing, giving access to more and more specialists,which is good because we’re guaranteed to have enough people to develop and maintain our products in the future. According to the HackerRank 2018 Developer Skills Report, Python is the second language coders are going to learn next and is among TOP-3 languages in financial services and other progressive industries.


“Python wins the heart of developers across all ages, according to our Love-Hate index. Python is also the most popular language that developers want to learn overall, and a significant share already knows it.”

Python can be used for all kinds of purposes, from traditional ones like web development to cutting edge, like AI. It’s versatile – it has over 125,000 third-party Python libraries. It’s the go-to language for data analysis, which makes it attractive for non-technical fields like business, and the best programming language for financial analysis.

Again, I’m not trying to sell you Python because it’s the only language that can save the world. I’m only speaking from my own experience because I saw what wonders Python can do when applied within the Django Framework.

The world of fintech is demanding – your product has to be trustworthy, 150% secure, and functional. Adhering to state regulations, dealing with integration with services, institutions, and bank API connections should all be built to last to support the new generations of millennials who are taking over the future. To get to the top and be among the ones who are disrupting the financial market, you need to be unique, efficient, user-oriented, and open for the future. That’s what Python is about.

The article is written by Arthur Bachinskiy. This article about building fintech product with python is originally published on Django Stars blog. You can also visit our content platform Product Tribe created by professionals for those involved in a product development and growth processes.

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