Emerging Technologies and Their Potential to Transform Transaction Banking

With technology developments occurring at a rapid rate, Christopher Mager of BNY Mellon Treasury Services, discusses some of the key innovations that are impacting transaction banking, and how knowledge is king when it comes to harnessing new capabilities.

Many forces are driving significant change in transaction banking – from regulation, to the rise of the millennials in the workforce, and increasing globalisation and connectivity. Yet, one force in particular is having a disproportionate effect on the financial services industry: technology. 

The emergence of fintechs is contributing to the speed of technological change in banking, with a surge of new tech savvy start-ups entering aspects of the banking space with designs on transforming existing processes. Although initially viewed as threats to banks, fintechs have come to realise that banking is one of the most entrenched of all industries. Banks have developed exceptional skills in areas including client relationship management and operating efficiently at scale while managing appropriate operational, audit and regulatory controls. Subsequently, with the value and strengths of both parties firmly established, banks and fintechs have increasingly begun to collaborate in what some refer to as a ‘fintegration’ approach.

Whether strategies involve banks on their own, banking partnerships or partnerships with fintechs, what is clear is that, as an industry, we are being presented with opportunities like never before to innovate and transform the businesses we operate – by leveraging the array of emerging technologies that is increasingly at our fingertips.

Understanding new technologies

Navigating and optimising the technology landscape is easier said than done, however. With a multitude of new capabilities coming to the fore, if banks are to use technology to enhance the client experience and optimise their offerings, it is paramount that they understand what these new developments are, what potential benefits they can bring, and what deployment challenges there may be. Let us therefore examine a sampling of some of the key technologies being deployed in transaction banking – and their potential to transform cash and trade services.

APIs

Application programming interfaces (APIs) are tools for building application software, which can simplify programming, make solution development more efficient and streamline communication, interaction and integration between software components. 

APIs are widely being used in a number of industries and the likelihood is that many of us have come across APIs in some form without even realising. APIs are creating opportunities to define new business models, such as Airbnb and Uber, with Uber, for example, leveraging APIs to engage with Google Maps for driver navigation. Such businesses are unlikely to be able to innovate and continue to modernise at the pace that they are without APIs.

APIs are playing a significant role in shaping the banking industry. This trend is being further fuelled by open banking and PSD2 regulations, with APIs being used for quick enablement and the provision of information to approved third parties. 

APIs can also create partnership ‘hubs’ to formulate customised value-added products and services. BNY Mellon has been developing a robust digital ecosystem that puts API access front and centre, enabling clients to reuse and remix data according to their needs. 

RPA

Robotic process automation (RPA) – the software automation of routine and repetitive tasks – is increasingly being explored as a way to enhance current processes. When we think of robots, we tend to think of robots that physically move. But software robots – defined as ‘an application of technology for processing a transaction, manipulating data, triggering responses and communicating with other digital systems’ [1] – can create opportunities to deliver increased efficiency, cost savings, error reduction and ease of deployment in transaction banking.

Indeed, many applications of RPA involve data entry, with robotic tools able to improve speed and accuracy and operate round-the-clock, thereby providing 24/7, 365 access and support for data around the world. It can also help with the ongoing journey of digitisation, which provides the benefits of effective audit trails for compliance purposes. Furthermore, RPA enables human operators to focus on higher-value tasks, such as client relationship management, including providing client insights.

AI and machine learning

Artificial intelligence (AI) and machine learning take RPA a step further by utilising data to gather insights, detect patterns and trends, and make recommendations based on experience. It involves the process of structured learning; with the application being ‘taught’ where to get the data, what the structure and format of the data is, and the process it needs to follow. It can then operate and perform its task. The application cannot make decisions itself, but it becomes smarter by observing and ‘learning from’ how the operator uses the recommendations it makes. The application of technology can subsequently help the operator become more efficient and make more informed decisions with better data.

AI is being explored by numerous institutions, including BNY Mellon, to enhance existing regulatory processes such as OFAC scanning, where it could ultimately help to reduce the number of false positives identified in the process. AI is also driving the use of chatbots and virtual assistants. Amazon’s Alexa and Bank of America’s Erica, for instance, leverage AI to perform their tasks within boundaries but within a flexible manner in order to provide an enhanced service to users.

A complex landscape

These are just some of the emerging technologies that could potentially revolutionise banking processes. And while there is anticipation and excitement around such innovations, each technology development presents challenges to banks when it comes to application, which means there is understandable uncertainty with respect to how – or whether – to incorporate them into innovation strategies. These challenges can include interoperability with existing infrastructure, the scalability of the solution, how they can add value to clients, risk, regulation and compliance, as well as returns on investment.  

A common challenge, of course, is the nascency of, and the industry’s lack of familiarity with, such innovations; they are not thoroughly understood and established in the market. While not covered in this article, distributed ledger technology is an example of a still nascent technology – that, while holding potentially significant efficiency and resiliency benefits, is still challenged by lack of standards, interoperability, adoption, and regulatory clarity. 

In the case of APIs, as another example, standards are still being developed – resulting in uncertainty – and the support infrastructure is not well understood.

With respect to RPA and AI, a key challenge is defining the requirements needed to implement such applications. The data has to be structured and the process they perform very defined for them to perform effectively. Subsequently, banks may need to revisit and reengineer certain processes and how data is governed.

There is also some uncertainty around how AI could impact people’s future roles in the workplace. But applying AI to high-value activities through what is known as ‘artificial general intelligence’ – i.e., the ability to contextualise information and apply common sense and reasoning – is still many years away from reality. It is also important to understand that while machines may be suited to certain tasks, AI is not a panacea. The most effective way forward is therefore to establish an understanding of where AI can add value, and deliver optimised services through combining the capabilities of both humans and technology.

Of course, even equipped with an understanding of developments and the challenges that need to be overcome to deliver enhanced solutions, investing in new innovative technology capabilities can be a challenge in itself. Yet, through correspondent banking partnerships – non-compete local-global bank alliances that marry the experience and strengths of both parties – local banks can leverage the technology capabilities of global banks, without the need for significant investment. 

Importantly, this also extends to include support and guidance with respect to emerging technologies. The technology landscape is very much a work in progress in transaction banking – many concepts are at a very early stage, and not all new concepts will necessarily succeed. With so many developments occurring in rapid succession, it is only by being equipped with the knowledge and understanding of the evolution taking place that banks can optimise new possibilities, and provide new solutions that cater to the increasingly tech-fuelled needs of clients.