What Are The Most Viable Options For Developing Reliable Back-End In A Fintech Project?

Fintech Back-End Development: Which technologies To Base Your Product Around?
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The fintech industry today is stronger than ever. Don’t take just our word for it. Simply look at the stats – the numbers speak for themselves!

  • $50 Billion is invested in fintechs annually
  • Nearly two-thirds of all financial transactions are made online
  • More than 500 new fintechs are created every year
  • Banks can gain an up to 30% operations profit by turning to fintech
  • Nearly 2 Billion people are still unbanked

This list can go on and on, but the point still stands. Fintech is indeed the new black of the tech industry. What’s especially interesting is the fact that behind the financial success or even the global trend for digitalization it is fairly easy to forget that it is the technological aspect that makes 50% of fintech.

You will be competing against players who offer innovative services based on scalable infrastructure. Gaining the edge in the technological arms race may be the difference between becoming the next unicorn or crumbling beneath the weight of technical debt.

What to look for in fintech back-end technologies?

There are many technologies one may choose to build their back-end on. From Python to Java to even Golang, the choice typically depends on the scope of the project, one’s need to deal with legacy infrastructure, and plain old performance. That being said, there are specific elements you can’t overlook when choosing a back-end technology for your fintech project. They are:

  • Scalability
  • Robust infrastructure
  • Potential of quickly dealing with regulatory issues if the need arises
  • Potential to quickly resolve issues related to the customer interface

Java

One can say whatever they want about either Java or the next Java killer but this will not undermine an astonishing statistic: 65% of developers use it as their main programming language today. This fact alone brings a lot of fantastic benefits:

  • Finding talent is much simpler. Even new hires will know the language well.
  • Great talent is relatively cheaper. Outsourcing development or augmenting your team is much more cost-effective when you are looking for engineers who are experienced with the “traditional” tech stack.
  • Perfect fit for legacy projects. What’s to say here? If you are planning on improving your existing banking product, the odds are it is already built on Java.

Then there’s security. Java has been the go-to technology for most banks and financial institutions for well over two decades for a reason. The technology can be manipulated for both enterprise financial institutions and new fintech startups. It is well-structured and allows developers to leverage a comprehensive library of tools and third-party integrations. Java also offers security features out of the box, such as runtime constraints and an advanced security manager, helping to prevent fraud and cybercrime.

Lastly, Java is quite powerful. It offers developers a high level of functionality & deliverability, an important aspect in both finance and fintech due to the rapidly-evolving market. One of the most mature programming languages in the market, Java is both lightweight and flexible but still powerful to handle heavy volumes of data easily. Java is a fully portable programming language, i.e. it can be launched on any device, allowing institutions to provide personalized and competitive services for clients and customers.

Python

Python may not boast the history and longevity of Java, but it is definitely a solid choice for lightweight web-based fintech apps due to its simple yet robust nature.

The language is quite simple to master as its dynamically-typed syntax resembles English. In simpler words, your team will learn and master Python much quicker cutting down technology adoption costs dramatically. The ability to quickly read, understand and manipulate complex code is also an excellent feature for an industry that is evolving as dramatically as fintech. This means that both your time to market delivery and the ability to implement quick changes based on new regulations are enhanced giving you a potential edge over the competition.

Lastly, Python is known for its robust ecosystem of libraries. They allow developers to build platforms and even entire microservices without designing and coding each element from scratch. Additional support for third-party APIs and frameworks makes working with integrations faster and simpler.

Go for Python if you are mostly interested in:

  • Time to market delivery
  • The ability to implement changes on the fly
  • The ability to grow your team or replace talent at will
  • A wide assortment of integrations and APIs your project will work with

Ruby

Ruby is a relatively fresh technology when it comes to fintech-specific development projects. Nonetheless, it is one of the most prominent and quickly growing languages, primarily thanks to its powerful framework, Ruby on Rails.

Ruby and RoR work best when you are developing:

  • Digital payment systems
  • Asset management solutions
  • Analytical projects and data visualization dashboards
  • E-wallets

What makes Ruby tick?

The language owes the lion’s share of its success to two primary factors: a wide variety of ready-to-use plugins and the aforementioned RoR framework. The combination of these factors allows for the development of secure, stable, and maintainable solutions without stomping time-to-market delivery into the ground.

As for the disadvantages, Ruby suffers from the most frequent bane of open-source projects - poor documentation. The amount of information out there is huge, but finding a particular thing you really need at the moment is nothing short of a herculean feat.

The boot speed is also nothing to write home about but it is a pretty minor disadvantage.

Kotlin

Kotlin is a much newer technology than even Ruby and yet it is our weapon of choice for most fintech projects. What’s especially great about the technology is that it is designed around the mobile-first approach.

If you are developing a mobile banking app or a modern digital banking service and you can’t afford to compromise quality and security, Kotlin is a perfect choice.

Some of the greatest advantages Kotlin offers are:

  • High performance
  • Compatibility with Java
  • A highly functional JVM %20is,code%20for%20a%20particular%20system”)version
  • A reliable concurrency model
  • Simple syntax
  • The vast availability of tools, resources, frameworks, and APIs

As for the disadvantages, Kotlin is a relatively new technology and, as such, there aren’t too many experts available on the market. You know where to look for them though (wink-wink).

C++

If you are developing a data-heavy solution designed with quantitative financial analytics in mind, C++ is probably your best bet. The language is fast and efficient.

More on the matter, C++ is known for offering high speed of execution and the capability to deal with countless numerous operations simultaneously.

Developers who rely on C++ advocate reusability of code so even if it takes longer to build the initial elements of a product, the code is then easily repurposed to speed up ongoing development stages.

A wide gallery of tools and frameworks as well as great accessibility of talent on the market also have their share in the language’s success.

That being said, C++ isn’t the most reliable technology when it comes to security so you will probably face many more issues when dealing with regulatory compliance. The language is also quite massive and complex, so onboarding will not be a walk in the park for new recruits.

The Progress Locomotive never stops

Let’s face it, there’s no escaping the evolution of technology. Even in a field as relatively new as fintech, there’s always the choice between Java or Kotlin, Python, or RoR. The best thing you can do is treat the change as a great thing.

That being said, jumping on the bandwagon of “the next big thing” is probably not the brightest idea. Why bother reinventing the wheel when you are designing a Big Data analytics solution and age-old C++ works best?

Always look at the scope of your project, the requirements you have, the functionality you need, and the audience you are building the solution for. That’s the only way of adequately picking the best tech stack for the back-end of your product.

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