Edge Computing in Financial Services

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Edge computing framed in a circle

It seems only yesterday that everybody was rushing to jump up on the cloud bandwagon. Now, with the arrival of 5G, which relies on edge computing services and is responsible for igniting the Internet of Things (IoT), companies are rethinking their IT frameworks once again.

Edge computing is poised to become the central technology for supporting data processing in the coming years. In a nutshell, it will allow for smart objects to process their own data without it needing to sync back and forth with the cloud.

But how does it work? Let’s find out more!

What is edge computing?

The textbook definition? A decentralized IT architecture in which data processing takes place locally (either on a server or on the device itself) instead of relying on a data center that is far away. The immediate result is known as low latency, or the experience of minimal delay thanks to the request being finalized closer to the end user.

Another way to understand edge computing is by breaking down each of the terms. The word “edge” means something is happening at the border or limit of, in this case, the cloud. “Computing” indicates the kind of process that is taking place. So, data is being computed at the edge of the cloud, meaning it’s not mixed in with all the other data being stored and is closer to its source.

Let’s imagine the cloud as an actual cloud in the sky, and the moisture that form around it as data. What if, instead of letting the cloud absorb everything all the time – resulting in a storm, or too much information – we placed boxes around it that capture the moisture (or data)?

These boxes process data to ensure only what is truly necessary makes it into the cloud. The result is reducing the distance between requests, devices, and the cloud resources, and reducing bottlenecks present in today’s internet systems (such as bandwidth).

And there’s more: while IoT devices may appear more vulnerable to attacks than a robust, all-encompassing cloud, the mere division of information into smaller pockets makes it easier for cybersecurity teams to simply shut down one part of the system if there is ever an attack.

What is edge computing used for?

Back in 2019, the volume of data created worldwide was expected to reach 41 zettabytes (a zettabyte equals around a billion terabytes) by the end of 2019. However, BBVA estimates this will be 10,000 times greater by 2025.

In layman’s terms: that’s a lot of cloud storage space.

Due to its efficiency, the usage of edge computing technology is particularly useful in applications that use high amounts of data while also demanding a fast response time. Examples include facial recognition, augmented reality, gaming and automation systems.

And let’s not forget self-driving cars, a great example of how critical edge computing can be. These cars rely on many different programs and algorithms to run at the same time, demanding instantaneous responses and processing while communicating with databases. Of course, edge computing is the only way to realistically process and feed those answers back to the car’s devices as of today.

So, when we talk about 5G and the IoT, we’re not only talking about robotic arms and smart homes. We’re talking automated cars and airplanes, processing enormous amounts of data (around 4 terabytes and 70 terabytes per hour, respectively). If we have to wait for this high amount of data to be processed by a cloud and sent back, these vehicles would not be able to respond and adjust fast enough.

From here stems the idea of processing data locally, within the smart object itself. The same rule applies, for example, to data being received at a local call center or through a bank branch. Why upload everything to the cloud when you could process it first and then only transfer what’s necessary?

Mobile edge computing

It’s the same concept, only referring specifically to mobile devices and cellular networks. Also known as MEC or Multi-Access Edge Computing, it provides processing and resources closer to the end users within a mobile network. It’s worth mentioning 5G again here, since its implementation and widespread use will rely immensely on mobile edge computing capabilities.

The benefits of edge computing

Think of what happens when you have a slow-loading website. For one, it’ll perform poorly on search engines given that page speed is a critical ranking factor nowadays. But even if customers are able to find your page, they won’t want to return. Edge computing tackles this problem, as we’ve mentioned before, by making local data processing possible, thus resulting in increased speed, lower latency, and ultimately a faster loading website.

Another way in which edge computing can benefit financial services is by helping institutions comply with regulations. Not all data is international, and global access is harder to control when information is up on the cloud. To comply with regulations, customer data often cannot leave a certain country or region. With edge computing, companies can store information outside of the cloud but while still having it belong to the company’s data ecosystem.

When it comes to reducing costs, edge computing can help by limiting data expenditure on your network, which translates into less upkeep and resources.

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