- Main trends of fintech software solutions
- Top 5 languages for finance & fintech software development
- Java in fintech development
- How to choose a programming language for fintech project
- Choose ELITEX as your responsive partner
- Final thoughts
The financial sector globally is experiencing immense change due to its transition to digital space. Fintech software solutions henceforth have become an integral part of financial operations. They are pushing progress forward: next-gen banks, on-demand insurance, online banking apps, algorithmic trading platforms, and digital wallets are involved in the banking operations we use on a daily basis. The choice of programming languages for fintech development greatly influences the speed, security, and scalability of the future product.
Main trends of fintech software solutions
Financial software is continuously evolving, driven by various trends that are reshaping financial services. These trends collectively enhance efficiency, security, overall customer experience, and convenience, driving innovation and redefining the future of technology. Understanding them will, therefore, be the first step in our journey.
- Open banking that relies on safe banking data sharing via API between authorized organizations online in a more secure and standardized way;
- Biometrics in contactless solutions to ensure the security of mobile banking app development;
- Digital wallets that connect online and offline payments in smooth transaction experiences across different platforms;
- Regtech and compliance solutions to help financial institutions automate and manage the immense volumes of standards, laws, and regulatory requirements, as well as monitor transactions and suspicious activities;
- AI and ML include chatbots and assistants in fintech software solutions to improve customer satisfaction via smart banking services, while ML algorithms are used for credit scoring, risk assessment, and investment recommendations;
- Development of autonomous AI-driven finance solutions in order to help users effectively manage their money.
Top 5 languages for finance & fintech software development
The fintech industry relies heavily on software systems. However, the selection of technologies and programming languages for finance development depends on the specific use case, taking into account factors such as performance requirements, scalability, integration capabilities, and regulatory compliance.
The fintech software development services involve the building of a wide range of applications, from mobile banking apps to trading platforms and personal finance apps. Different applications require different approaches and, consequently, different coding practices. High-frequency trading platforms, for instance, demand C++ or Java to execute complex algorithms smoothly, while data analysis and risk modeling in banking often leverage Python and R for their extensive libraries and statistical capabilities.
However, we offer to take a closer look at one particular example. Let’s stop at the probably most popular type of software: banking applications. The banking industry has one of the fastest paces in terms of going digital, so let’s try to imagine that we are building software solutions for a bank. A solid digital presence, in this case, means a robust website, mobile application, core banking system, analytics software, and additional features such as risk and treasury management systems, fraud detection and anti-money laundering (AML) software, and customer relationship management (CRM).
Important note: The security of the banking system isn’t so much dependent on the programming language itself but rather on the coding method. So, in fact, any of the languages can be used for secure software, and the language will be the same as in core solutions in most cases.
Nevertheless, there are some concerns about the safety of the JS, mainly revolving around client-side security vulnerabilities and the potential for malicious code injection. However, strict adherence to security best practices through code review and input validations can mitigate these risks.
AngularJS is good for creating single-page applications (SPAs) and dynamic websites. Being an open-source framework, it comes with the MEAN stack and allows many code editors and integration of various tools and filters along with server-side rendering. It is also an excellent tool for creating interactive and responsive user interfaces, handling complex data models, and efficiently managing application logic. It is mainly used in fintech applications such as online banking portals, investment platforms, and financial dashboards.
React Native advantages in terms of fintech
React Native is an excellent choice among fintech programming languages due to its high speed, reliability, vast community, extensive ecosystem, and the possibility to cut costs by 30–40%. Cross-platform development enables devs to write code once and share it from 90% to 99% between both platforms. React Native is primarily the framework for creating mobile applications, so, with a significant probability, the banking apps, investment platforms, and payment wallets you use on your phone were built leveraging the power of React.
Node.js for mobile banking apps
Despite this, large fintech companies are using Node.js due to the speed, safety, functionality, privacy, and much more. For this purpose, PayPal has developed its own extension, Kraken.js, to the Express.js framework. Walmart.com also runs on Node.js.
Java in fintech development
Java developers build secure platforms for financial data; numerous institutions generally use it as the leading or one of the leading programming languages for fintech development. Its object-oriented nature, scalability, and reliability make it well-suited for handling complex financial transactions, data processing, and integrating various systems and APIs. As a result, almost half of all development projects in the financial services industry use Java.
It is reasonably fast for developing critical apps and platforms, and that’s the key to its popularity. Financial industry development with Java enables platform-independent programming and multi-threading support, which makes software compatible with diverse environments. Java’s emphasis on solid type-checking, exception handling, and memory management contributes to creating robust and secure fintech applications, minimizing the risk of errors, vulnerabilities, and financial breaches.
Python is frequently considered the best programming language for the finance industry due to its high versatility and relative easiness of use. The language accepts various data types, quickly detects errors, is highly adaptable, and allows third-party integration. In fact, that’s the most popular tool for working with data, AI, and machine learning, which is an expansive tendency recently.
In addition to data analysis and quantitive finance, Python frameworks like Django and Flask provide the necessary tools for building web interfaces, APIs, and backend systems (a sphere where Node.js vs Python are often compared) for banking portals and financial service platforms, as well as pricing, risk, and trade management systems. The language’s simplicity and readability make it an accessible choice for developers, while the ability to handle complex calculations, perform statistical analysis, and generate reports makes it also suitable for developing risk management tools and monitoring compliance with regularity standards as well as data security utilities.
C++ is an excellent example of a general-purpose programming language that provides great opportunities to build whatever you want; however, it requires decent programming skills. It is commonly employed in building high-frequency trading systems, algorithmic trading platforms, and risk management tools that require real-time processing and low-latency execution. It is undoubtedly the best programming language for finance regarding handling complex calculations, direct memory management, and integration with hardware, making it a preferred choice for building highly performative fintech applications.
C# (C Sharp) shares many common features with the previous one; however, it’s a bit more simplified. C# also provides developers a productive environment, extensive library support, and integration capabilities for building robust and secure fintech applications.
One key difference between C# and C++ is their primary usage and focus. C++ is a lower-level language used for applications that require real-time processing and direct hardware interaction, such as high-frequency trading systems. On the other hand, C# is a higher-level language that makes integrations with other technologies easier. It is commonly used for developing enterprise-level applications, including banking systems, trading platforms, and risk management tools, where development with integration with existing systems and frameworks is crucial.
How to choose a programming language for fintech project
There are multiple options to choose from when developing fintech software. The selection process involves taking into account various factors, including project requirements, scalability, security, performance, existing infrastructure, and development team expertise. By carefully evaluating key factors, fintech companies can make informed decisions and choose the best coding language for the finance industry for their specific goals.
Defining the project scope for financial products
Timeline and budget limitations
Time and budget constraints are another factor to consider. Some languages, such as Ruby or Python, are known for high productivity and easiness of use, making development cycles faster; JS and PHP will likely require medium-sized budgets and timelines, while C++ can require high development costs in terms of time and budget. It’s crucial to balance time and budget considerations with the long-term scalability and maintainability of the particular language to avoid future development bottlenecks.
Choose ELITEX as your responsive partner
ELITEX is a trusted development partner for numerous businesses and organizations worldwide. Our expertise extends to developing cutting-edge fintech solutions complemented by vast experience in the financial sector. We stay up-to-date with industry trends and technologies, ensuring an innovative and efficient approach to your project.
The abundance of programming languages offers a diverse array of options, with pros and cons for specific tasks, especially when it comes to the development of fintech products. It is crucial to recognize that different technologies excel in different areas rather than seeking the single best programming language for all fintech projects.
The choice of programming language should be guided by your project’s specific requirements and existing infrastructure. A decent financial solution takes into account a wide range of factors, and as soon as it is done, the choice will be almost obvious.
What is the best programming language for finance & fintech development?
There is no just the best programming language, as different languages excel in various areas of financial sector development.
Can I use multiple programming languages in the same application?
Yes, mixing different languages and technologies in the same application is possible. For instance, there are plenty of websites where two or more languages were used for back-end and front-end developments.
What language is preferred for high-frequency trading systems?
Languages like C++, Python, and Java are commonly used in trading systems due to their performance and data-processing capabilities.
Can an existing fintech application be migrated to a different programming language?
Yes, it is possible, although it may require significant effort and careful planning. In certain situations, it is a good idea, while sometimes, writing code from scratch using another language is a better solution.
What are the best languages for financial analysts?
Languages like Python and R are popular among financial analysts due to their extensive libraries and tools for data analysis and statistical modeling.
JS is commonly used for web, mobile apps, and server-side development, as well as API integration.
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