Edge Computing in Financial Services

Banks and financial institutions want to provide quality services and bring in more customers. The competition presented by each financial institution requires the other to offer something unique, and what better way to do this than through the use of new technology. Application programming interface (API), blockchain, and artificial intelligence (AI) are changing the industry and unlocking the potential for tailored customer experiences, hyper-personalization, and back-end support for any business model.

Financial institutions now deal with large volumes of data which would normally be impossible to process and which they would fail to use for improving back-end office operations and customer experiences. The term edge computing refers to a numerical computation framework bringing data computing and storage nearer to where it’s needed in order to improve processing time and save bandwidth. Edge computing is different from traditional cloud computing, which involves the processing of data located in storage facilities that are more remote, such as far off data centers.

A classic example of edge computing is with autonomous vehicles. A driverless car needs countless sensors to operate and ensure the safety of passengers. With typical cloud computing, it takes too long for data to transfer between the source and the data center. Even a split second could result in an accident, making speed and latency of data a critical element in the success of the technology. The ability to process data closer to the source is essential for the future of autonomous vehicles.

The image below represents how the edge sits as a layer between machines and traditional cloud data centers.


There are several use cases in financial services where edge computing is set to have an impact.

Customer Experience

The main focus is on data and how close it is to the customer. Mr. Stephen Fabel, Director of Canonical company, the creator of Ubuntu, states that the introduction of edge computing brings forth a new concept. ‘It enables use cases such as robotics computer vision and machine learning to impact the end-user either directly or indirectly by enhancing the experiences individuals are already accustomed to, like in-store or in-bank offerings’. He further presents the idea of BYOD (Bring Your Own Device) banking, which is different from previous banking experience data as the new model is closer to the customer. Ravi Naik, the Chief Information Officer at Seagate Technology, concurs by saying that if the key focus is security and how data is delivered, the financial sector has made a breakthrough in the industry. ‘As financial institutions transform their business models, there is an increased need to adopt distributed data models’.

Banks use edge computing as a way of deploying a more personalised customer experience. For example, facial recognition technology or virtual tellers, that previously were impossible due to latency and speed issues, are now plausible developments. As a customer walks into a branch, an infrastructure that works close to the ‘edge’ could instantly provide relevant loan offers, recognising their face and delivering information to staff.

Technology such as HSBC’s Pepper benefits from better data processing capability to interface with customers. The IoT-based robot creates a unique banking experience for customers, that is now enhanced as data comes closer to the edge.


Data Security

Financial institutions process a massive amount of data every day. For example, banks process secure CCTV data, thousands of ATMs in different cities, and records of personal transactions over the banking network. Traditionally a case or claim of fraud reported by a customer is only sorted afterwards, with the client already being at the receiving end of their financial loss. In the case of edge computing, this is different: video feedback of the client’s complaint is taken and analysed instantly with little to no need for human intervention. For a fraudster trying to tamper with an edge-computing-armed ATM, items on the screen are rendered unresponsive, and the machine will most likely shut down immediately on further attempts.

One of the most critical issues in financial institutions and especially banks, is how secure customer data is. With edge computing, banks can answer questions over consumer data security more straightforwardly. The answer is simple, as the technology processes data close to the source and thus eliminates the need to upload data to the public cloud. In this case, the data does not go through the risk of interception in transfer channels used by cloud computing applications. The inherent risks of regulations like GDPR and CCPA are more natural to navigate within an edge computing infrastructure. The closer to the source the data remains, the fewer places there are for cyber attackers to penetrate.

Operations Scaling

As mentioned earlier, the use of new technologies presents a challenge of how to handle large volumes of data. Edge computing is a solution allowing for easy management of data near the source. In this case, it will enable financial institutions to scale their level of operations. An example of this is that with the introduction of cloud computing, banks are installing systems enabling its staff to interact with customers in rather personalised ways directly. This does not necessarily mean that the centralised use of data storage will be scrapped. Instead, the amount of data processing performed through centralised usage will be minimised. In a 2019 report, respondents said that 30% of their IT budgets would be spent on edge cloud computing over the next three years, with the remainder still going towards cloud investment. That said, Gartner predicts that by 2025, three-quarters of enterprise-generated data will be created and processed at the edge, outside of a traditional data center.

Edge computing also presents the idea of continuous operations. This means that even when disconnected, a financial institution will always be in service with minimal downtime. For example, computer vision will be operable in branches, reducing the reliance on human staff and on-site assets.

Customer Behaviour Analysis

In a highly competitive market, financial institutions always seek to monitor customer behaviour. It allows them to understand more fully the customers’ needs and what needs to be improved. In this respect, the rise of edge computing in finance now extends to IoT devices such as mobile applications which are now used to access mobile banking services.

AI-powered video analytics in branches could look at how customers use physical space. Facial expression analysis can help optimise the branch to guide the customer through improving their experience at the same time.

Senior research director at Gartner, Santhosh Rao, says that ‘as the volume and velocity of data increases, so too does the inefficiency of streaming all this information to a cloud or data center for processing’. Pursuing edge computing allows for the rapid deployment of projects the 21st-century-consumer demands.

5G and Edge Computing in Finance

5G and edge computing are two interlinked technologies. Both will work together in handling and processing large volumes of data, especially over the next few years. Unlike 4G, 5G boasts of a speed that is ten times faster. Teaming this with mobile edge-computing services reduces latency by bringing new computing capabilities to the network, and closer to the end-user.

The Risk to Edge Computing

As with any evolving technology, there are associated risks that can slow down adoption. The major one with edge computing is security. Extending your infrastructure footprint to edge computing provides a new surface for attackers. Coupled with the speed of transfer that 5G promises, those in the finance industry are understandably nervous about making personal data too available.

It is also hard to quantify any return on investment from edge computing. With some projects being high-cost, there will be challenges in trying to deliver a financial benefit. Edge computing will help to fast track innovative projects, but assigning revenue to it directly is tough. Financial institutions need to see edge computing as an enabler for other initiatives, rather than a profitable deployment in its own right.


Advanced technology has played a vital role in the development of the financial industry. From the use of AI to APIs, customer experience is becoming better every day. Perhaps, one of the most important things to note is that edge computing is here to stay. As more and more technologies continue to emerge, edge computing will keep growing. Financial institutions must embrace the latest technologies if they want to grow themselves.

Disclaimer: The author of this text, Jean Chalopin, is a global business leader with a background encompassing banking, biotech and entertainment. Mr. Chalopin is Chairman of Deltec International Group,

The co-author of this text, Robin Trehan, has a bachelor’s degree in economics, a master’s in international business and finance, and an MBA in electronic business. Mr. Trehan is a Senior VP at Deltec International Group,

The views, thoughts, and opinions expressed in this text are solely the views of the authors, and do not necessarily reflect those of Deltec International Group, its subsidiaries, and/or its employees.