Java in fintech

Because Java is the most commonly used programming language in fintech, professionals that are familiar with Java Core and Java frameworks are in high demand. Java development experts who can test ready-made software, as well as those who develop services and apps for fintech projects, are both super valuable and hard to find. But why is this language so helpful? Because Java is mainly used to develop server applications and mobile apps, it embodies the notion of object-oriented programming. It is also the foundation for Android-based applications. That’s why it is not surprising that Java is used everywhere these days— from eCommerce to fintech. Keep reading to learn why Java is an excellent choice for your fintech business.

Why choose Java for financial engineering

Modern realities need modern approaches because the number of Internet users is continually increasing, as is the quantity of electronic transactions. People are becoming more familiar with digital money and its circulation. As a result of the increasing strain on financial applications, the modern technological stack in fintech includes working with distributed systems.

Fintech applications must be capable of handling massive loads. Furthermore, because it involves money, such an application must be super secure. Any mistakes the developer makes can result in a significant loss of money.

Thus, Java is one of the most frequently used programming languages in large fintech projects. Why? Because it is a well-established language with a significant community and a broad set of technologies and libraries. It can also offer application security, which is critical for enterprise development. Many frameworks and libraries have been written for Java: there is no need to reinvent the wheel; everything has already been created and tested many times by experienced developers. Thus, Java in fintech is more dependable and quicker (thanks to Spring).

Where is Java used?

It has been one of the most in-demand programming languages on Wall Street for years. From constructing high-frequency trading systems and order management to building financial institutions’ own risk management platforms, Java can deal with everything. Plus, it is also handy for running simulations and modeling how trading techniques function.

The majority of significant e-commerce platforms use Java for internal development. It has been particularly popular in the Internet of Things (IoT), where it offers excellent support for network and communication protocols. Java in Fintech is represented by a wealth of banks, insurance institutions, trading firms, and software development companies that construct specialized external client systems utilizing this programming language. Java for finance is used by many of the world’s investment banks to build front- and back-end office e-systems, regulatory and confirmation systems, data handling projects, and other things. Examples include Goldman Sachs, Citigroup, Barclays, Standard Chartered, and others.

6 reasons to choose Java for fintech

It’s cross-platform. This is most likely the most well-known benefit of Java. Java executes within the Java Virtual Machine (JVM). Because the code does not directly contact the operating system, it can theoretically operate anywhere that supports a JVM, including Windows, Linux, macOS, mobile platforms, or robotics and embedded systems.
It’s one of the most stable languages. Don’t be surprised if the code that was written 20 years ago is still relevant and works! This is one of the reasons it is popular among organizations, particularly those in the financial sector. Many big investment institutions, including Goldman Sachs, Citigroup, and Barclays, use Java. Amazon, eBay, Oracle, IBM, and Intel also utilize Java.
Java in Fintech is a secure choice. Java is a popular programming language that has consistently been a top choice by many for years now. This is especially important for organizations that process vast amounts of data for settlement or transactions. Because of the magnitude and global brands behind it, the systems of huge organizations, especially banks based on Java, have become a testing ground for hackers. The targeted organizations reacted to the hacking attacks by building more and more robust barriers. As a result, security systems were frequently updated, patched, and upgraded on a regular basis.
Java in Fintech is simple to maintain. It has to do with coding standards that are maintained and created by the developer community. They give transparency and provide guidelines that allow code to be understood not only by individual team members who generate it but also by programmers who may eventually take over.
It’s flexible. Specifically, your team of Java developers in financial services can build the same application on several devices. It is not necessary to create numerous versions for each operating system. This saves a lot of time and money for a fintech company that develops such an application.
It’s a strongly typed language. This implies that a specific type of data must be used for it to function. The program won’t operate in any other case. As a result, it is more resistant to faults because many of them stop during the program’s compilation. Large businesses, financial institutions, and banking institutions value solutions that they have total control over, and choosing Java for fintech provides them with just that.

Hire Java developers for financial services with nCube

Java is one of the most used programming languages. It is everywhere these days, so it is not surprising that fintech businesses have a really strong interest in Java developers for financial services. A severe shortage of this expertise makes so many companies look for external partners to help them build a team of skilled developers. nCube is an experienced staff augmentation services provider which allows you to source talented developers for your project in Eastern Europe and LATAM. Contact us, and our experts will reach out to you shortly to help you learn more about how to hire a remote team of Java developers on a dedicated model.