Financial services organizations and edge computing

As an emerging paradigm, edge computing can aid financial institutions in swiftly analyzing information closer to the point of generation. Edge computing refers to the use of processing power derived from the edge of networks and devices closer to the end user. The biggest benefits of edge computing are bandwidth savings and reduced latency, or the time it takes data to travel. 

The financial services industry already uses edge computing to create hyper-personalized customer experiences, secure proprietary information, reduce operational costs and adhere to international data governance standards. But with the global edge computing market at about $11.2 billion as of October 2022, and forecasts projecting it will reach $274 billion by 2025, according to Statista, there will be significant room for growth. Banks and other financial institutions should explore more ways to integrate edge computing capabilities if they want to stay on the front lines of innovation.

To evolve, financial institutions often seek ways to serve and better understand their customers. Through modern technology, they can possess the speed and flexibility necessary to transform their business by quickly assessing creditworthiness with machine learning or using artificial intelligence-driven trading systems that analyze massive amounts of data in milliseconds. Reducing last-mile latency in high-frequency trading, minimizing fraud and risk, and providing smarter recommendations are all ways edge computing can improve performance and lower costs.

As the state of the economy remains uncertain, it is crucial that companies assess how these applications can provide value today and in the future.

Financial transactions—at the cutting edge

Financial services is one of the most highly regulated industries, and moving money globally is one of the most significant challenges banks face. A bank transfer must go through several intermediaries before reaching its destination. Banks also incur costs when they send large amounts of data to the cloud. That large amount of sensitive customer information makes the industry highly attractive to hackers and more susceptible to breaches.

Edge computing can play a role in keeping that data within an organization’s boundaries and national borders. Using processing mechanisms closer to the locations they are serving can reduce the amount of data sent to the cloud, thus facilitating the transfer of data more swiftly and efficiently to all parties involved in a given transaction.

Here’s a common example: Imagine walking into a crowded bank, and there’s a long line. While you wait, you can use a mobile app to communicate your needs and upload your information, which gets processed by edge servers and sent to the banking staff. By the time you meet with bank staff, they have all the information necessary to assist you, including recommendations for products or services that best suit your needs based on the responses submitted via the mobile app.

Edge computing combined with AI and Internet of Things devices, such as smartphones, will allow customers to control their financial data, get documentation in real time, and view their transactions, even offline. All because key information is stored on their device’s local network. Along with devices that collect and process data locally, edge computing components include edge devices, nodes, servers, gateways, and sometimes public or private clouds. This infrastructure enables stable and fast performance, which is where edge computing excels.

The benefit of edge computing and having processing, storage and applications closer to the edge is the ability to add more devices and data inside the organization without worrying about bandwidth, performance or latency problems. The banking industry is said to benefit the most from edge computing in the near future. Institutions are deploying virtual tellers and secure authentication processes to accelerate opening an account and gaining entry into the financial system.

Other services that can be streamlined with edge computing are sales transactions, customer complaints, local decision-making in real time, and connecting device sensors or event data to security protocol.

Security and scalability

In the past, most edge computing happened in hospitals, factories and retail locations. Today, we are seeing financial institutions address consumers’ expectations for the quick and immediate transfer of information.

Highlighted by the growing interest in 5G edge computing applications and private cellular networks, companies are evaluating the adoption of private networks enabled by distributed edge computing architectures and AI-driven applications. 5G combined with edge computing capabilities will increase speed and scalability.

Edge computing can also help satisfy increased interest in heightened security protocols. There are fraud detection tools that leverage machine learning and edge computing to analyze behavior, track location and determine purchasing habits which will quickly detect unusual activity for fraud prevention.

The pandemic spurred a wave of digital investment, creating a huge opportunity for hackers and threats. Subsequently, security jumped up the priority list for many leadership teams. Financial institutions have increased security and technology use by leveraging edge computing for fraud detection and prevention, on-premise advanced data analytics, and ensuring international data standards are upheld. Some institutions are even considering using real-time facial recognition for fraud detection by augmenting ATMs or closed-circuit TV footage using the software to detect potential fraud risks.

Alongside security investments, companies continue to invest in cost-saving technologies. In a recent Gartner study, 400 midsize enterprises collaborated to map the adoption of emerging technology, and 58% noted a plan to deploy edge computing to address concerns such as latency, bandwidth, data privacy and autonomy in the working environment. According to an International Data Corporation survey, 42% of businesses say the most challenging aspect of edge deployments is putting together an entire edge solution.

Taking action

Here are some key considerations for financial services institutions embarking on integrating edge computing solutions:

• Align your edge solution with use cases to ensure smoother strategic adoption.
• Consider the costs associated with deploying and managing an edge computing environment. Costs can easily exceed a project’s financial benefit if not properly planned.
• Consult with your information technology infrastructure teams to ensure the edge solution you want to deploy can be easily managed and updated for new capabilities as they become available and standards evolve.

Whether accessing and harnessing data locally, processing through various converged edge systems, streamlining via device sensors or enabling applications at the edge through mobile connections, edge computing is changing how we connect to each other and our information. Financial services organizations, in particular, need to assess what this means not only for their customers but for their growth plans for the future.