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 best way to do this than through the use of new and advanced technologies. Technologies like 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 that would be impossible to process, usually without any effect on back-end office operations and customer experience. The term edge computing refers to a numerical computation framework that brings data computing and storage nearer to where it’s required to improve processing time and save bandwidth. Edge computing is different from traditional cloud computing, which involves the processing of data from 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.
Source: https://innovationatwork.ieee.org/real-life-edge-computing-use-cases/
There are several use cases in financial services where edge computing looks set to have an impact.
Customer Experience
With edge computing, 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 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 that if the critical 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 can use edge computing as a way of deploying a more personalized 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, recognizing 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 unq=ique banking experience for customers, that is now enhanced as data comes closer to the edge.
Source: https://finovate.com/pepper-power-hsbc-brings-robot-retail-banking-to-finovatefall/
Security of data
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 claims of fraud reported by a customer is only sorted afterward with the client already being at the receiving end of financial loss. In the case of edge computing, this is different; video feedback is taken and analyzed 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 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.
Scaling of operations
As mentioned earlier, the use of new technologies presents a challenge of how to handle large volumes of data. Edge computing is a solution that allows for easy management of data near the source. In this case, it will enable financial institutions to scale their level of operations as they can now handle large volumes of data. An example of this is that with the introduction of cloud computing, banks are installing a system that allows its staff to interact with customers in a rather personalized way directly. This does not necessarily mean that the centralized use of data storage will be scrapped. Instead, the amount of data processing performed through centralized usage will be minimized. 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.
Edge computing allows financial institutions to become leaner. Technology, like computer vision, will be operable in branches, reducing the reliance on human staff and on-site assets.
Analysis of customer behavior
In a highly competitive market, financial institutions always seek to monitor customer behavior. It allows them to understand better 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 that can now be used to access mobile banking services and provide a more straightforward way to access banking and financial services.
AI-powered video analytics in branches could look at how customers use physical space. Facial expression analysis can help optimize 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 that 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 process 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 compute capabilities to the network and closer to the end-user.
Current networks pose a challenge to the realization of full potential by companies and organizations. For example, enterprise customers often reach you for your services through the internet. These include small retailers, factories, and large warehouses in different regions. The diversity in locations may require the need for distributed computing and, in this case, may require the purchase of expensive equipment, for those located in, say, a high-temperature environment. With edge computing, clients do not need to buy, install, or manage this type of infrastructure. Instead, communication service providers are a cheaper alternative as they reduce the customer’s burden by including edge technologies and micro-cloud computing capabilities in their services. The expenses that could be used in the purchase are instead injected in other sectors of the customer’s business and more revenue generated. This is the power of 5G combined with edge Technology.
The risk of 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.
Summary
Advanced technologies have played a 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. Further, we do expect that growing financial institutions will embrace even more technologies as a way to improve their operations and customer relations.