The financial services industry has seen significant growth over the past decade, with advancements ranging from innovative mobile banking applications to blockchain-encoded data storage. Banks and fintech have always been receptive to new technologies due to the need for high transaction volume, risk management and immediate processing.
Finance has been at the forefront of technology, either through developing an in-house team or partnering with some trusted, dedicated software development teams such as KMS Solutions, DXC Technology, etc. Analyzing the income statements of these IT companies, it is found that banks are among their most popular customers.
To help banks stay competitive in the digital race, a dedicated software team needs to master some advanced fintech programming languages. Considering the specifics of the banking industry, such as strict security standards and the requirement to comply with legislation, we have identified 7 technologies that are widely used in the banking and financial industry.
From: HackerRank surveyJava ranks first in financial interviews and second in fintech, underscoring its dominance over other programming languages. Java has been used by some of the world’s largest banks for over 25 years, and because it has been used for so long, Java remains an important programming language even as new technologies emerge.
Java has a friendly learning curve, can handle significant amounts of data, and boasts robust security features that have contributed to its popularity in the BFSi segment. Security is paramount in finance and it is necessary to provide the platform to users on multiple platforms. Java provides a solution with its strong security APIs and a security manager that can isolate suspicious code, virtual machines, and other security measures that are convenient and effective.
Furthermore, this programming language is also unparalleled, making it ideal for mission-critical financial applications. Not to mention the possibility of working on any device thanks to the use of virtual environments.
Java is also known for its extensive library of open source tools and frameworks. These tools include frameworks for building web applications such as Spring and Hibernate, and data analysis tools such as Apache, Hadoop, and Spark. A wide variety of tools and frameworks available make it easy for developers to build and deploy financial applications and systems.
Python is widely used in Fintech and is considered one of the most popular programming languages among industry professionals due to its accessibility, simplicity and flexibility.
A few reasons that together make Python a favorite for FinTech enterprises include:
- Clean, easy syntax (ie 4 lines of Python can draw 10,000 pseudorandom numbers)
- Strong financial algorithm performance
- Has a huge collection of libraries and frameworks that can be used for various purposes.
Some implementations of Python libraries are:
- Data analysis. Python provides various libraries such as Pandas and NumPy that allow efficient and easy data analysis. These libraries allow you to clean, transform, and analyze data in ways that make it easier to extract insights and make informed business decisions. Software engineers can analyze financial data to develop financial models that can predict market trends and patterns.
- Quantitative Finance. it can be used for quantitative financial applications such as portfolio optimization, risk management, and financial modeling. Libraries such as QuantLib, Pyfolio, and PyAlgoTrade provide useful tools for these types of applications.
- Visualization of financial data. Python has several data visualization libraries such as Matplotlib and Seaborn. These libraries enable the creation of interactive and informative charts, graphs, and other visualizations that can help stakeholders understand complex financial data.
Python is a programming language well-suited to finance because of its ability to perform mathematical operations. Given the growing demand for technology collaboration between the banking industry and other quasi-financial institutions, Python’s popularity in the financial industry is expected to grow. If you look at financial technology, big banks like Bank of America have worked hard to convert their technology stack from legacy code to Python.
Although C/C++ was created in the late 1970s, it is a common choice of programming language for Fintech businesses that prioritize speed. With its special compiler, C++ stands out for its ability to develop complex and multi-level systems.
The language’s compiler strictly enforces type matching, making it less error-prone and offering greater security to applications written in this language. Thus, C++ is used in the financial services industry, which is important for managing and mitigating various types of risks, including market, credit, and operational risks. This programming language allows developers to build robust systems that can analyze and model large data sets to identify potential risks and take corrective measures.
Low-latency software is extremely important in online trading and forex, and as a result C++ is a popular choice for companies operating in these industries. Its ability to create high-speed programs, combined with powerful memory management and optimization capabilities, make it an ideal language for building financial trading systems that require fast and efficient real-time processing of large amounts of data.
Furthermore, C++ can be used to create algorithmic trading in fintech because it can handle large data sets and perform fast transactions.
C# is the next generation of C++ that maintains a significant presence in fintech (fourth ranked language) and finance (fifth ranked) according to HackerRank. It is a high-level, object-oriented programming language used to create dynamic applications that run on Microsoft and the .NET ecosystem.
Since Java is considered a “legacy language for finance” and developers tend to have a psychological bias to move to something more modern with better enterprise support, C# is the best alternative. For example, Java developers who regularly use Eclipse will be able to immediately see how Visual Studio, the most popular C# IDE, is so superior to Eclipse.
C# is often used in finance and fintech because it is a powerful, flexible and reliable language that can perform complex calculations and data analysis. It has libraries and frameworks for working with data, including LINQ, a language-integrated query system that makes it easy to manipulate data from different sources.
5. Ruby / Ruby on Rails
Ruby’s creators describe it as a language that emphasizes “simplicity and productivity.” Perhaps this is why businesses in the digital banking industry are using Ruby in conjunction with its Ruby on Rails framework. Software developers cite ease of use (which saves time and money) and the framework’s built-in security features as the main reasons they prefer it.
Ruby has many programming features relevant to fintech and finance, namely speed, security and flexibility. The programming language can be used to create a variety of financial solutions;
- Build the components of the panel. Design and implement your financial dashboard components. This can include features such as charts, tables, graphs, and key performance indicators (KPIs) to visualize financial data. Gems like Chartkick, Highcharts or D3.js can help with data visualization.
- Integration of payment gateways. Ruby offers libraries and APIs that facilitate integration with popular payment gateways. For example, Stripe, PayPal, and Braintree gems provide Ruby bindings to interact with their respective payment APIs. These libraries simplify payment processing tasks, including creating payment forms, processing payment responses, and securely managing transactions.
SQL is different from the other programming languages mentioned above. However, it is important to the BFSI sector as it harnesses the power of databases, making it a key tool for those working in the field.
Financial Institutions Professionals in various fields such as business, marketing, sales, and finance recognize the importance of business data analysis to success. SQL is an important tool in this process that acts as a path to success. This programming language is integrated into data processing platforms, used in statistical modeling, and is becoming an increasingly valuable skill among financial analysts.
Furthermore, because the financial world has a lot of structured data with complex relationships, perhaps more than any other industry, business and financial analysts use SQL to find patterns and turn mountains of data into useful information.
React Native, an open source mobile development framework built on top of React, allows you to develop cross-platform mobile apps for both iOS and Android. This can be beneficial for financial and fintech companies that aim to provide their customers with mobile applications such as banking applications, investment platforms or payment solutions.
In addition, this language also supports the enterprise testing process as it offers a number of testing utilities such as Jest and React Testing Library that help ensure the quality and reliability of financial applications. These tools facilitate unit testing, integration testing, and component testing, enabling developers to identify and fix problems early in the development cycle.
Find the right dedicated software development team that offers the right technical package
These programming languages provide the necessary tools and frameworks for everything from data analysis, algorithmic trading, and risk management to building financial dashboards, payment systems, and blockchain applications. They enable professionals in the BFSi sector and other related fields to leverage technology and effectively manage vast amounts of data, automate processes and make data-driven decisions.
Therefore, when finding a dedicated software development team, it is important to consider the software engineers’ familiarity with the aforementioned technology stack. At KMS Solutions, our developers specialize in building financial and fintech solutions using appropriate programming languages to ensure high performance of the software.
We also have 180+ resources supporting multiple clients in the BFSI segment and have helped more than 250+ enterprises across industries to develop software solutions like ACB, DiscoveryMarket, Axi etc., develop financial applications and create engineering teams. Contact us now to learn more about our customized solutions.