Expertise: Fintech

A Few Words about the Future of Fintech

Today, the financial industry seeks to automate daily processes and deliver more personalized financial products and services. In collaboration with IT companies, financial organizations are digitally transforming the traditional financial landscape to achieve better quality and reduce costs.

Our development and BA teams will help you integrate state-of-the-art IT solutions into your business processes. Based on extensive experience in the banking and investment sectors, our engineers can develop online banking systems, trading platforms, environments for the development and testing of trading robots, and many other financial applications.

The use of Big data and Machine learning is crucial for the personalization of customer service. Banks that fail to implement these technologies run the risk of losing their competitiveness in the second half of the 2020s.
Big data and Machine learning provide the basis for building various neural network-based trading strategies for investment companies.

Fintech
Fintech
6.6%
Gartner forecasts worldwide banking and securities IT spending can grow by 6.6% to reach $547.82 bln in 2021
85.5%
Of Americans used mobile
banking in 2020
82%
Of financial organizations plan to increase collaboration with fintech companies in the next 3-5 years.

What our expertise in Fintech allows us to do?

Platforms for Financial organizations

Full functional solutions for Financial organizations require deep knowledge of financial domains in combination with cloud and mobile technologies reached by AI and Data Science. Digital Transformation based on FINMATEX Platform Implementation in Financial Organization.

Big data and Machine learning

Banks and financial institutions have enormous amounts of customer data. However, they are using only a small portion of it. They need smart solutions that would allow them to automatically process this data. That's where AI comes into play. AI-powered systems can help modern banks to:

  • identify patterns of customer behavior and atypical transactions,
  • identify patterns and divide customers into different groups,
  • better understand customers’ risk profiles,
  • understand, predict and help customers achieve their financial goals,
  • provide personalized recommendations for the company's products and more.

The use of Big data and Machine learning is crucial for the personalization of customer service. Banks that fail to implement these technologies run the risk of losing their competitiveness in the second half of the 2020s.

Big data and Machine learning provide the basis for building various neural network-based trading strategies for investment companies.

Robo-advising and algorithmic trading

Trading automation has helped reduce the number of market failures and make it harder to find them. Quants carefully search for hidden patterns between assets and events, set up increasingly complex neural networks, and apply sophisticated mathematical tools to maximize profits. Over the past 12 years, the boom in the stock market has increased the popularity of robo-advisory platforms that provide millions of customers with automated, personalized investment recommendations and help reduce the cost of service fees.

Our engineers, BAs, and AI specialists develop solutions that allow creating an environment for options trading and arbitrage operations automation, create modules for robo-advising, deliver solutions based on neural networks that help build a successful investment portfolio based on the specified criteria of the investment term, risks, and profitability.

Chatbots

Chatbots are a new highly personalized communication channel. And thanks to the development of AI, they are becoming even smarter, more responsive, and user-friendly. Through voice and text messages, chatbots provide users with personal investment recommendations, allow them to create asset purchase orders, and more.

There are two ways to build a chatbot:
1
Train a chatbot to recognize user commands based on voice and/or text. Such bots are used to process clients’ requests.
2
Write chatbot scripts that provide various directions for the conversation with users. Such chatbots are used in consulting — they survey clients and generate a response based on the obtained answers.

In finance, chatbots are used for account management, in the financial marketplace and for financial consulting.

Chatbots
Computer vision

Computer vision

This technology is increasingly being used by banks and other customer-facing financial companies. It helps improve customer service and free up staff for more significant tasks, allows you to collect more information about customers, and reduces the risk of fraud.

Financial organizations apply computer vision for:

  • Client Face Recognition. It can be implemented both in offices and ATMs. Coupled with the analysis of other client biometric data, it reduces the time for KYC verification.
  • Automated KYC.
  • Customer traffic monitoring and queue management.
  • Emotions recognition — analyzes customer emotions in real time and generates conversational scripts based on them.

Softarex has been developing Computer Vision-based solutions for various sectors of the economy for years and will gladly assist you in implementing this technology in the business processes of your financial institution.

Security

When developing software for financial institutions, we pay great attention to information security and data protection. We follow the requirements of the SOC 2 security standard. Our solutions undergo a security check using specialized tools and systems for vulnerability analysis. Read more >>

Security