Use cases grow for edge computing in financial services

I have been speaking about decentralising cyber security to RFA clients and prospects since the early days of the increased popularity of public cloud, the increase of collaboration tools and of course the requirement for staff to be as mobile as possible when fundraising – of course this has been accelerated due to the pandemic when, very quickly, multiple devices across multiple decentralised locations became central to firms working networks, essentially creating multiple satellite offices for every firm. This development in our way of working has helped drive the conversation around edge computing which is starting to come to fruition as benefits, use case scenarios and ROI become clearer.

Edge computing is a distributed IT architecture, where data is processed at the ‘edge’ of the network as close to the data source as possible, as opposed to being centrally processed via a traditional cloud model. Very closely associated with cloud computing, edge computing is the next iteration of data management which focusses on speed, volume, and security, the very basic principle being that the less distance data must travel, the quicker it can be processed. This is an obvious next step in technology for manufacturing and industrial firms – think healthcare, education, and supply chains – but the business use case for the financial industry is also gathering pace.

From a cyber security perspective, edge computing could really start to reduce the risk of attack. Running Managed Detection and Response, using machine learning and AI-enabled analytics at the edge could increase the ability to mitigate attacks across whole networks as vulnerabilities would be less accessible. Edge computing allows for data monitoring on a smaller scale and with a more immediate response, significantly reducing need to send large scale data sets to the central cloud.

I talk a lot about data in terms of procedure and process, access, and control. Edge computing can be used to deliver low-latency analytics in a way that makes it much clearer to the manager, investor and regulator exactly where their data is held and that it is secure at all points in a firms data strategy, not just in storage and at the end point, but also in ‘transit’ too.

There is an immediate benefit for trading too of course, where often still servers are located in the same building as the exchange itself to minimise latency between order and purchase. This co-location of servers with the relevant exchanges had provided a greater latency reduction than any other solution, but trades often require communication between locations, meaning co-location does not remain competitive and becomes redundant. Edge computing will reduce latency by processing data locally at the edge of the network, increasing data processing times. Edge will also reduce third party costs for firms as not needing to position servers and exchanges in the same space means real estate needs in central trading locations like London, New York and Luxemburg are reduced.

RFA are first adopters of new technologies, and our in-house R&D team has seen its focus on data strategy and management increase significantly over recent years. The advent of edge computing as a useable solution is another exciting step forward in distributed working and decentralised data and security that can improve speed of data transfer, security of data in transit and at the end point and open more opportunities for innovation and development in our industry.