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Fintech Market Research Trends

SIS International

Executive Summary:

The FinTech industry is one of the most developing and growing markets in recent years. Under the collective name FinTech (which still lacks a clear definition even within the industry), financial services are understood within the framework of the Digital Market Outlook; digital infrastructures allowing the establishment of new types of agreements and procedures in the classic areas of banking such as lending, investment strategies and payments.

We discuss FinTech Market Research trends.  We decided to split FinTech trends into 3 categories (General, Customers, Technology). Please see below FinTech trends associated with particular category:

  • Microservices
  • Fintech-as-a-Service
  • Embedded Finance
  • Cryptocurrencies
  • Digital payments
  • Fintech as a new bank
  • Artificial Intelligence and Machine Learning

Fintech Trends in detail:

Microservices

Microservices are unique solutions that have a huge impact on the Fintech industry. They give the flexibility to develop innovative, groundbreaking technology and agility to adapt to changing circumstances and competitive forces. Microservices offer a completely different technology proposition. They are independent applications developed, deployed, and maintained separately to deliver on specific business requirements. These microservices help solve common, complex issues like speed and scalability while also supporting continuous testing and continuous delivery.

Why?


  • Microservice adoption is on the rise due to its potential to keep services more competitive, relevant, in-demand, and highly responsive to the variations of the market.
  • Financial institutions are focusing on adopting modernized IT architecture for their fintech apps to deliver faster product launches, easier compliances, instant payments, and maximized agility.
  • Fintech companies and banks are tapping on the benefits of microservices as they realized the difficulty to modify their digital services with a legacy system.

Effects


  • Increased scalability – reduced costs and low security risks
  • Better reusability – Microservices supports reusability by building composable, modular services.
  • Quicker time to market – Due to its modular nature, microservice facilitates faster development.
  • Simplified Debugging and Maintenance
  • Resilience – Since microservice involves small, independent modules, a failure of one single microservice doesn’t affect the entire application.
  • High-Quality – Microservice facilitates working in focused modules. This helps in overall quality improvement of the application.

Fintech-as-a-Service

Fintechs technologies are a desirable solution for many traditional lending companies looking to leverage advanced business functionalities and financial processes. Many Fintech startups are looking forward to selling their technology platforms as a service to corporations in the field. These FaaS platforms integrate seamlessly with any existing back-office of traditional banks and provide for non-banks a cost-effective and fast way to launch various financial products and services.

Why?


  • SaaS model has become one of the most popular and effective solutions on the market. In each industry customers and businesses see the potential of this solution in terms of increasing revenues and stability.
  • There is a gap between today’s thriving, tech-forward business community and the legacy financial systems. Fintech-as-a-Service is a perfect solution that can help the finance industry to reduce the gap and use technology to scale businesses.

Effects


  • Encourge banks to leverage their current capabilities in new ways
  • Helps reduce the digitalization gap between Fintech and banks
  • Sub-branches of the banking and Fintech industry are developing faster and more efficiently. New payment solutions, new methods of identity verification (KYC), better Anti-Money Laundering are only some of the areas where there will be huge innovation and improvement.

Embedded Finance

There will be strong growth in embedded finance (e.g., buy now and pay later programs, embedded insurance options) and banking-as-a-service offerings and in related partnerships. Indeed, a Boston Consulting Group (BCG) survey across 15 countries published in May found that a hefty 44 percent of 18-to-34-year-olds had enrolled in online or mobile banking for the first time during the COVID-19 crisis.

Why?


  • The companies’ embrace of embedded finance—banking-like services offered by nonbanks—aims to retain customers and increase their so-called lifetime value.
  • To meet the rising demand for embedded finance, financial institutions are increasingly offering banking as a service (BaaS)—bundled offerings, often white-labeled or cobranded services, that nonbanks can use to serve their customers.

Effects


  • Customers expect integrated experiences. Fintech and banks will be cooperating with various partners to meet their expectations.
  • New business models and sources of revenue. Particularly advantageous are sources that have scalable business models and fixed IT investments (e.g., distribution models).
  • Adoption of technology capabilities. With the acceleration of digitization, including automation and APIs, Fintech can scale BaaS faster, putting embedded finance within reach for more companies considering it.

Cryptocurrencies

Cryptocurrencies like Bitcoin and Ethereum have indeed proven resilient. Investor interest, both retail and institutional, in digital currencies has risen dramatically in recent months. Many early investors who were eager to make gains from the “cryptocurrency craze” have since moved on to other ventures, leaving a smaller group of stalwart HODL-ers behind. But there are still reasons to believe that the cryptocurrency industry has some fight in it left.

Why?


  • Cryptocurrencies have dominated the investment market in recent years. Bitcoin or Dogecoin is on the news every day, Musk’s tweets are only increasing the popularity of this area.
  • Several new developments such as increased institutional interest, pending ETF approval, and the popularity of stable coins suggest a continued positive trend.

Effects


  • A lot of people want to become anonymous, especially in social media times. Cryptocurrencies are the chance of increasing privacy and keeping our data safe.
  • Cryptocurrency market is highly attractive in terms of investments. Decreasing interest on saving accounts and low ROI from stocks and bonds only increase demand for alternative investments like cryptocurrencies.
  • Goverments are putting cryptocurrencies in the spotlight. China has already introduced its first digital currency.

Digital Payments

There has been a rise in the demand for new forms of digital payments which are much more secure and reliable. This has been able to transform payments into an open ecosystem where various parties like FinTechs, banks, payment firms etc are trying to evolve the digital payment system by introducing new technologies. The government, on their part, are trying to come up with certain regulations in order to reduce the ecosystem threats.

We were able to notice a massive growth in the digital payment transactions in the span of 4 to 5 years but with the pandemic the growth was motivated by the need for cashless and contactless payments. Thus Non-cash transactions are seen to be on a robust growth path.

Why?


  • COVID-19 has reinforced the trend of digital adoption in payments and retail commerce, across payment types and demographics.
  • The digital growth picture is not entirely rosy, however—consumer trust has eroded slightly and although consumers are turning to digital payments in increasing numbers, it is not clear whether all recent behavior shifts will prove to be permanent.

Effects


  • Omnichannel is crucial to meets customer expectations. While digital payments penetration has largely stabilized, omnichannel adoption has grown markedly.
  • Online payments are soaring. Contactless card awareness and adoption have roughly doubled in 2020 in the USA.
  • Customers don’t want to use cash. Cards – both swipe and contactless – are gaining share, while cash usage has massively declined in brick-and-mortar stores.

Fintech as a new bank

Fintechs technologies are a desirable solution for many traditional lending companies looking to leverage advanced business functionalities and financial processes. Many Fintech startups are looking forward to selling their technology platforms as a service to corporations in the field. These FaaS platforms integrate seamlessly with any existing back-office of traditional banks and provide for non-banks a cost-effective and fast way to launch various financial products and services.

Why?


  • In the last decade customer behaviors and expectations have changed dramatically. The way they do shopping, buy food, or use services are moved into digital. However, a lot of banks could not keep up with this change and that’s why Fintech gained a significant portion of the market.
  • Fintech offers innovative and user-friendly solutions which are faster and cheaper. Moreover, Fintech can quickly adapt to new market trends and challenges.

Effects


  • Fintech will become banks and try to be direct competitors for large banks (e.g. Revolut or N26).
  • Banks will need to adapt their services and products to current customers’ expectations. Due to this, digitalization in banks is essential to be competitive in the market.
  • Fintech and banks will cooperate more often and offer a unique solution for the clients (like Tink start-up which uses open banking technology to help customers).

Artificial Intelligence and Machine Learning

Both brick-and-mortar banks and fintech companies are adopting AI solutions at increasing rates. Partly, this may have been spurred on by the pandemic, but it’s a trend we’re increasingly seeing. AI and machine learning solutions are being applied in many business areas, from customer service chatbots to fraud detection, to analyzing the right financial products for a client.

Why?


  • AI and Machine Learning are helping in many complicated processes in finance. Managing assets, evaluating levels of risk, calculating credit scores, and even approving loans are using algorithms to improve efficiency and increase revenues.
  • Due to a large amount of data finance is an attractive field for machine learning as it tends to be more accurate in drawing insights and making predictions when large volumes of data are fed into the system.

Effects


  • Better fraud detection and prevention. Machine learning works by scanning through large data sets to detect unique activities or anomalies and flags them for further investigation by security teams.
  • Robo-advisors which help with portoflio management. Robo-advisors require low account minimums and are usually cheaper than human portfolio managers.
  • Improved process of lending money or providing insurance.

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