Banks and other financial institutions are actively using Python to solve the arising challenges of pricing, risk management, regulation, compliance, analytics, and data with the help of a great variety of supporting libraries. Fintech industry usually requests clear and strict data that’s why it’s important to use programming languages with a lower error rate. From UppLabs experience, there are several best Python libraries for Fintech development that we would like to share with you today.

Python is becoming famous and popular for its easier syntax and for being faster to program in comparison to other traditional languages, such as Java or C++. Python is also proved to be an ideal programming language for the financial industry. 

Requirements for fintech projects

You may sometimes not notice that Fintech is present almost in every sphere of our live. Fintech’s benefits include flexibility (the ability to respond immediately to changes in market demand), innovations, and the ability to attract customers who like to use technologies. Fintech services are used by those who prefer speed, convenience, and ease of use of the service.

Due to the interrelated global trends and possible financial risks that banks can face, the innovations enable large organizations to process high data volumes more efficiently and rationally. In this regard before starting a fintech business, you need to know the basic fintech regulations and main security practices:

  • The regulators are constantly reviewing the rules, expanding them, and responding to threats from both organized crime and the growing threat of global terrorist networks, many of which have become stronger and more complex in recent years;
  • Integrated networks and an increase in the number of cross-border operations have created gaps in the infrastructure of banks, increasing their vulnerability; 
  • The work of banks is affected by the wider use of economic sanctions for individuals due to foreign policy;
  • Regulatory authorities are wary of potential threats, and their increased expectations entail the creation of demanding regulatory conditions for banks and financial institutions;
  • Fintech companies need to use all possible modern technologies and AI to protect the financial markets, for detecting and counteracting cyberattacks before they cause harm and faster data recovery;
  • The fintech projects need to be fulfilled in compliance with internal and external requirements and standards and conduct according to multiple jurisdictions.

Technologies used in Fintech development

For Fintech founders, selecting programming languages and frameworks that are a fit for the needs of their Fintech companies should be prioritized. The main programming language that is leading now (2020) in Fintech projects is Java. It is followed by Python, Go, and PHP

In Blockchain projects, the most used languages are: Go, Python, Java, Ruby (Ruby on Rails), Scala (Akka), C ++ (.NET), C # (. NET). For the development of smart contracts, developers prefer to use the Solidity language (for the Ethereum platform). We researched the list of technologies that are currently used for the main fintech businesses all over the world and discovered that regarding the choice of the right technology, it’s essential to find the one that will be the foundation of your project. The technology stack has to fit all the project criteria and meet the demands of the project’s goal. Each programming language is great for a specific purpose, so it’s important to make sure to define a clear understanding of what the project is going to be like.

Looking at the high level of dependability, Java is highly unlikely to lose its top place as the most preferred programming language by the financial institutions. On the other hand, FinTech requires concrete programming features that can get better managed with Python than Java or any other programming language.

Why Python?

We choose Python because it is suitable for developing any projects on different platforms. It can be found on the web, on mobile devices, in applications, solutions related to machine learning (neural networks and artificial intelligence), and even as an embedded system. 

More reasons to use Python for our projects:

  • Python has many ready libraries for solving various problems.
  • The simple syntax of the Python language helps the developer test complex algorithms with a minimum waste of time for project implementation.
  • There are many useful resources about Python where a programmer can get help and advice at any stage of the development.
  • Python helps combine different types of data. Moreover, Python is especially convenient for those developers who write most of the code using the IDE.

Python is considered to be an ideal choice for the financial industry. It’s popular in the investment banking and hedge fund industries, many banks are using Python to solve problems regarding pricing, trade management, and risk management platforms. Python also offers answers to the most challenges of the financial industry while dealing with analytics, regulations, compliance, and data, as it offers a great variety of supporting libraries.

Python advantages:

  • It’s simple and clear
  • It reduces software development costs and time to market
  • It offers greater collaboration
  • It has a large number of open-space financial libraries (SciPy, NumPy, pandas, pyalgotrade, pyrisk, zipline, quantecon.py, pyfolio, pybitcointools, finmarketpy, scikit-learn, ffn, pynance) 
  • It leads to lower error rates and less bug-hunting

Best Python libraries for Fintech applications and platforms

As we mentioned above, one of Python’s advantages is a great variety of available libraries and tools. Python is considered to be a key language for mathematical programming. This means it suits perfectly for financial institutions, the sphere that requires calculations, data and order in numbers. In this regard, Python offers many financial and fintech libraries and here we collected some of the best Python libraries used by Fintech companies: 

  • NumPy (essential package for scientific computing),
  • pyalgotrade (algorithmic trading library that supports paper-trading and live-trading),
  • pybitcointools (Bitcoin-themed Python ECC library),
  • SciPy (free and opensource library for scientific and technical computing),
  • pandas (flexible and easy to use data analysis and manipulation tool),
  • pyfolio (library for performance and risk analysis of financial portfolios),
  • quantecon.py (open source computational tools for economics, econometrics, and decision making),
  • scikit-learn (library that uses machine learning algorithms and predictive data analysis),
  • ffn (financial function library for quantitative finance),
  • finmarketpy (library for analyzing market data and backtesting trading strategies using a simple to use API),
  • pynance (open-source software for retrieving, analyzing, and visualizing data from stock and derivatives markets),
  • zipline (Pythonic algorithmic trading library),
  • pypi (functionality that is required to work with EBICS, SEPA and other financial technologies),
  • QuantEcon (code library for quantitative economic modeling),
  • qfrm (set of analytical tools to measure, manage, and visualize identified risks of financial derivatives and portfolios).

Fintech startups based on Python 

Here we have selected some of the most popular fintech companies that chose Python technologies and its libraries and became successful:

  1. Zopa. The largest peer-to-peer company with 75,000+ active investors who have lent over £3 billion to borrowers. It provides ISA investment choices to a wide range of peer-to-peer lenders and offers investment products. The company used Python as a key language in their technology stack. 
  1. Robinhood is a startup from California that in 2014 created an app allowing regular people buy and sell stocks usually afforded to the rich people without trading fees. The company helps clients to learn to invest in the stock market and build their portfolios. The company now costs $5.6 billion and lists Python in its tech stack and requires “intimate familiarity” with this language in their Job listings.  
  1. Thought Machine gives their clients the service they look for. With this purpose the company created Vault OS – a microservice API architecture platform that uses Python technology, using cloud infrastructure and blockchain to create a bank operating system that allows banks to maintain a ledger. 
  1. Revolut is a UK digital challenger bank that offers free international money transfers as well as free global spending at the interbank charge rate. Customers can open an immediate account and get a multi-currency card with an app. They can also exchange 25 currencies within their app, send free international money transfers, and spend abroad with no fees in over 130 currencies with a contactless MasterCard or Visa. And all this possible because of the Data Scientists and Python Engineers.
  1. Affirm provides accountable services to clients allowing shoppers to pay for purchases across multiple months with transparent fees built into every payment and increase conversion at less than the cost of credit cards. For their secure solutions, the engineers use Pyhon. 

Fintech Development in UppLabs

Over the last 5 years, we at UppLabs mastered the latest Fintech technologies and gained experience in creating reliable, secure, and sophisticated Fintech solutions and products:

  • Money transactions platform engineering
    Our fintech payment ecosystem is transparent and multifunctional.
  • Online trading and exchange platform engineering
    We create online e-trading platforms that offer real-time solutions with various trading fintech opportunities.
  • AI-based Fintech solutions
    We are ready to use AI-based solutions to collect and process huge volumes of data aggregated by Fintech companies.
  • Payment systems integration and optimization
    We automate your accounting and ERP creating the best fintech services and apps.
  • Existing services maintenance and modernization.
    Our portfolio includes the use of modern architecture that guarantees easy maintenance and easy integration with the best fintech services.

If you need IT consulting on Fintech – ask UppLabs!

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