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Accenture’s Fintech and the Evolving Landscape: landing points for the industry structure report showed that global fintech investment grew by 75% from US$ 9.6 billion in 2014 to US$22.3 billion in 2015. IT has embraced the potential of FinTech. Now FinTech has become one of the most disruptive and exciting segments in digital technology (Blockchain is at first place as disruptive technology). This environment created a huge opportunity for FinTech startups as well as for the IT industry. As the FinTech space continues to grow, IT companies begin preparing themselves with skilled resources and tech stacks for FinTech applications.
FinTech startups started getting proposals for offshore Python development for Software and Applications. FinTech applications can be build using other programming languages, but Python is leading the development and acquired the first place among FinTech development tools of Outsourcing companies. In the following write-up, we aim to prove why your fintech app should be developed specifically in Python Language.
Before we begin, we want you to know that Python is a machine language and around 25 years old. Python is written in a way that this programming language can perform a vast number of mathematical tasks and help FinTech developers avoid the algorithmic issues. FinTech is nothing but banking and finance industry that is solely operated digitally through processing data and analysis of different tasks via algorithms used in Application Development.
Why is Python a more useful language for FinTech?
It Works With Algorithms: FinTech is tightly connected with many figures, calculations and data (structured and unstructured) and so on. So the application is required to be efficient in mathematical tasks. Offshore python programmers stuck with this algorithmic problem. Here, Python shows its apparent advantages. This 25 years old programming language comes with syntax that is close to mathematical syntax that is required in financial algorithms. Mathematical syntax also helps developers assign value parameters.
Conversion: Simple mathematical calculations/equations or any other task can be done in plain Python. Developers can write any mathematical or algorithmic statement in simple one line of Python Code. As less is more, Python saves developer’s time to write codes in bulk that speed up the development process and quality of the FinTech App.
Performance: Python is claimed to be less efficient in performance parameters. Here, it is worth noting that the programming language is available with several auxiliary libraries that provide additional help and support to developers. Developers should choose the right Python library wisely as the choice of library to enhance the process of interaction with mathematical tasks. Using the right library and tool in Python helps developers deliver a high-performance FinTech App than its counterparts written in other languages.
Quick Compilation: Python’s libraries such as Numba and Cython supports quick code compilation of the software being created. These libraries are available with significant functions that support compilation of Python code into machine code statically or dynamically. These libraries increase processing speed, and software development cycle goes smoothly.
Innovative Areas Where Python Can Be Used In:
The financial sector is, and it consists of many areas. Here we are providing you the ways of Python language application in complex FinTech field.
Banking and Online Payment: Though we are experiencing good services from online banking and online payment systems, it could be increased by using Python. Many Bank institutions are exploring more opportunities with Python. It’s a mathematical syntax of Python and other capabilities which are quite acceptable for this segment. The mathematical syntax of Python enables developers to integrate algorithms in ATM’s software easily and for faster payment processing.
Cryptocurrency Markets: If you are engaged in dealing with cryptocurrency, you might have noticed the sudden spikes and dips in cryptocurrency values. There are hundreds of self-proclaimed experts advocating for the trends that they expect to emerge. What is lacking from many of these analyses is a strong foundation of data and statistics to back up the claims. Python programming language is not the last language that can help do it, but its significant libraries and innovative and modified tools allow procuring the raw data and uncovering the stories hidden in the numbers.
Stock Trading: Python comes to rescue again from the obstruction people face while using the stock market software. With python, a developer can create the right strategies to trade quickly and provide with useful tips regarding the future of that or another market. As we already know Python’s efficiency about algorithmic statics, a software developed in Python will much comprehensively enable algorithmic trading than the software build using other languages. Python Django Developer can build stock trading applications.
Using Anaconda – A prepackaged Python data science ecosystem and dependency manager, developers can write special scripts in Python that help retrieve Bitcoin or Ethereum pricing data and analyze it. Thus, the trend has already emerged in web apps that will analyze cryptocurrency are developing with the help of the Python language.
Though, not many fintech developments happened in another programming language, thus it not possible to say any other technology would better serve the purpose. Currently, Python addresses the existing bottleneck efficiently, thus getting wide usage all around. We should wait for some more time to know whether there is another programming language for fintech start-up’s requirements.
What are your views about using Python for Fintech needs? Share with us in the comments below.
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