2025 Forecast: How Fintech Will Revolutionise Banking and Payments

The industry of finances and banking has long been hesitant about undergoing digital transformation. Yet, with the intrusion of technology in all other industries and aspects of our lives, it became impossible to follow the old school legacy practices and, at the same time, remain customer-centric and competitive. This, in turn, led to the rapid development of fintech technologies that are designed to facilitate the operations of banks and financial institutions and help them serve their clients in a better and more efficient manner.

There are several interesting fintech trends that have already been taking place and are expected to come in full force in 2025 and in the upcoming years – read about them below.

Serving the underserved

It’s no surprise that many people do not receive sufficient banking services, starting from not having a bank account to being a predefined untrustworthy borrower. A report by the World Bank states that more than 1.7 billion people are invisible to the formal financial system. Thus, the fintech industry is going to address this issue and come up with solutions that will provide the required financial and banking services to certain groups of people.

Uber Money is an excellent example of this initiative. Considering that Uber drivers are the representatives of a gig economy and do not have a stable and fixed income within a certain period of time, they have specific economic needs. So when the company did research, it found out that many drivers go negative on their bank accounts about six times per month, have issues with sending the earned money to their home country, or cannot save money in an efficient manner. Hence, at the end of last year, Uber announced the Uber Money fintech initiative aimed at closing these gaps and helping drivers manage their earnings in a more efficient manner. Some of the features of Uber Money are:

• Immediate access to the earnings right after the trip with no need to wait for the weekly payment,
• Introduction of Uber debit account with certain cash-backs,
• Introduction of Uber Wallet which will allow managing money in one place,
• Enablement of international money transfers through the driver’s app,

These are just some of the features that Uber is going to bring to its drivers and this clearly shows that the company is well-aware of the rise of the gig economy and is doing its best to keep up with it.

Another good example is the use of Machine Learning technology to design sophisticated credit scoring solutions. The main idea behind such systems is that they are 100% non-biased and tend to give more accurate results than legacy scoring systems. In this way, lending will become available to those groups of people that used to be underserved before: people of color, non-married, young people, etc. Because Machine Learning is able to identify hidden dependencies and patterns in the data, it will be able to effectively evaluate a borrower and its creditworthiness. 

The rise of the gig economy and the growing independence of one’s financial solvency from the demographic factors serve as a perfect opportunity for the fintech companies to occupy this niche and take the lead in serving the underserved demographic cut.

Case study from SoftTeco: Sadad payment solution

IT development company SoftTeco partnered with Sadad, a company founded in Bahrain, in order to create a convenient mobile payment solution. The main idea was to design a user-friendly application that would allow its users to perform the majority of financial transactions (i.e. mobile invoice payment) via their smartphone, without the need to open a bank account. A user simply has to go to the physical Sadad kiosk and use it to add cash to their Sadad e-wallet. After that, the Sadad app grants access to multiple operations and transactions.

This project is a good example of providing banking services to the unbanked. Sadad launched its app mainly in Bahrain and Philippines where almost everyone has a smartphone but a really small number of people have a bank account. With the introduction of the Sadad payment app, these people now got access to multiple financial operations that can be performed via the mobile phone and that were unavailable before.

Transition to mobile

While Millenials and baby-boomers are still OK with going to the physical bank branches and paying with physical money, Gen Zers somewhat oppose this idea and expect financial services to be digitized. So in order to serve the needs of this really big population, companies need to come up with corresponding solutions such as mobile wallets, online services, and virtual personal assistants. 

The value for mobile payments set for 2023 was $2.98 trillion and is expected to keep growing in the future. As for the contactless payments, the expected number for 2024 is $1.9 trillion . Judging from this data, it can be said that digital financial operations gradually replace physical ones and we can expect more and more banking and financial services to be digitized in the future. As well, mobile will most probably become the single point of interaction between the users and the financial establishments and this is one more thing that companies should keep in mind.

Use of innovative technologies

Some of the biggest bottlenecks for the financial companies have always been the amount of paperwork and mundane processes and a massive amount of clients’ queries that demand immediate processing. All this takes too much time and resources and stops the company from development and growth. Therefore, this is another niche for fintech companies to occupy and offer efficient solutions based on innovative technologies.

One of the examples is the introduction of Robotic Process Automation (or RPA, for short) to a company’s processes. This technology automates legacy processes and can be applied to any task, which makes RPA an incredibly efficient and cross-functional tool. 

Robotic Process Automation is basically the use of robots in a variety of tasks, like local policy issuance processes. By using RPA technology, a company can significantly minimize the possibility of a human error, free the employees from mundane tasks and allow them to focus on more complex issues instead, and also provide a better customer experience by speeding up and optimizing the quality of services.

One more innovation that banks started adopting is the use of chatbots and virtual assistants. Usually, when a user visits a bank’s website or needs to perform a certain operation, it might take too much time, the website seems too confusing or the user feels insecure because he does not know much about the way the bank functions. Chatbots and virtual assistants are designed to resolve these problems by providing immediate assistance, performing particular tasks and navigating the user through the financial intricacies. This, in turn, greatly improves the customer experience and educates users about the financial operations, their own account, baning procedures, etc.

Better risk management

Banks and financial companies use legacy systems to assess one’s creditworthiness. However, these systems often tend to be biased and leave a massive share of borrowers behind. In order to make the lending process less risky and more accurate, companies started using solutions powered by machine learning. Such platforms identify the most trustworthy borrowers, reduce non-performing loans, and increase loan portfolio. Thus, by adopting such a system, a bank will not only benefit itself but will also increase the number of clients.

Another popular solution offered by fintech companies is financial forecasting based on machine learning. These forecasting models use machine learning technology to process massive data sets and make accurate forecasts based on this data. Not only does this approach minimizes the number of errors but it also tends to provide financial specialists with more accurate results than their colleagues make. As well, ML-based forecasting takes away such tasks as data compiling and reconciling, thus, enabling the specialists to pay attention to more important issues such as the research and understanding of key business events, microeconomic and macroeconomic factors, research of operational drivers, etc.

Focus on cybersecurity

Adoption of technology is great but cyber threats are the reverse side of the coin. In 2025, companies will need to leverage their cybersecurity practices and focus not only on efficiently eliminating the risks but also mitigating and predicting them.

One of the primary things that companies will have to pay attention to is the use of Artificial Intelligence to fight cyber threats and timely identify them. And because threat actors deploy AI as well, companies have to strive harder in order to protect sensitive data.

Another emerging trend that is related to cybersecurity is the transition to cloud environments and the use of business applications that mimic cloud environments. By using such applications, companies will be able to gain more control over their data and manage it in a more efficient and secure manner.

Finally, companies need to pay attention to the vulnerability of IoT devices. There are numerous ways how hackers can gain access over them so it’s critical to come up with efficient ways of protecting the devices and the stored and processed data.

Side note: compliance with regulations

While all the emerging fintech trends are aimed at facilitating and optimizing the processes of banks and financial institutions, there is one thing for the fintech companies to keep in mind. This is the compliance with all the necessary regulations such as  GDPR, Open Banking and PSD2 directive, or specific local regulations. So if a fintech company wants to roll out an innovative solution, it has to make sure that the product 100% meets all the legislative requirements. 

Otherwise, 2025 seems to be a great year for fintech companies to come up with game-changing solutions that will allow banks and financial institutions to make their services more customer-centric and user-friendly while automating and optimizing a number of internal processes.