Perspectives

Edge computing: Purpose to potential

Edge computing, cloud, and AI combined have the power to change the way how people interact with data and technology. But alongside the potentials, the consequences of a poorly planned and executed edge deployment can be severe. Getting this right requires careful consideration of the impact on an organisation’s existing risk and control frameworks to ensure a safe and secure deployment while balancing innovation, speed and control.
 

What is edge computing?

Edge computing refers to the decentralisation of computing that moves data processing from the core infrastructure, where computing processing traditionally occurs, closer to the person or item creating the data.1

Edge computing is the logical evolution of the leading cloud computing model. The use of edge devices that store and process data locally, rather than relying on on-premise data centre or more traditional cloud computing, enables faster decision making. Additionally, real-time processing at the edge makes data more relevant and actionable, helping to deliver better customer outcomes.

For example, edge computing allows banks to process customer data quickly and effectively, using real-time advanced analytics to better understand customers. This provides the ability to personalise customer offerings and offer additional value-added services most relevant to the customer, improving overall outcomes.

Enterprises are beginning to develop use cases combining cloud-based IoT solutions with edge computing, powered by the increasing availability of superfast 5G internet connectivity, to accelerate data analysis to make better and faster decisions2.
 

Use case of edge computing for financial institutions

Early iterations of edge computing have been used by financial institutions for many years, most notably through mobile banking apps, which have become an important part of the global banking ecosystem. By incorporating elements of edge computing within an edge device (such as a smartphone or gateway device) that collects data from other endpoints and applies real-time processing and analytics, mobile banking apps have made banking more accessible, inclusive and faster to an increasingly global audience as well as providing an enhanced customer experience through personalisation.

Edge computing can be utilised to help banks leverage data analytics to create a more memorable customer experience by creating personalised and relevant content delivered through their preferred digital channels.

For example, by leveraging anonymised location services data and technology, banks can understand areas of interest to their customers and partner with these businesses (e.g. restaurants, hotels, retails etc.) to provide exclusive offers to their customers. This can be done through in-app push notifications when their customers are in the close vicinity of participating businesses, informing them of special offers they can take advantage of.

This is just one of the ways organisations can use edge computing to keep their customers engaged and encourage use of their product and services.


Safe adoption of edge computing – areas to consider

While edge computing can offer solid benefits, it can also introduce complex challenges including considerations for data privacy (e.g. GDPR, CCPA and other data privacy-related requirements), security, resilience and third-party management.

To help manage these challenges and ensure safe and secure deployment of edge computing solutions, organisations should define an overall adoption strategy and consider each use case in turn. This entails considering the impact of this technology on organisations’ existing risk and control environment to determine whether it remains fit for purpose.

Organisations need to ensure that governance and control requirements for edge computing solutions are commensurate to the level of risk, to avoid stifling innovation and curtailing the benefits of this technology, whilst maintaining control. A key first step is therefore to define a set of criteria that can be used to consistently assess the level of risk associated with an edge computing use.

Some of the key risk considerations that should form part of the risk assessment include:
 

Risk consideration

Points to consider

Data
  • What type(s) of data will our solution collect and process?
  • Will we be processing personal data?
  • Where will the data be stored long term (e.g. a non-EU data centre)?

Security
  • Does each edge node have the same level of security, redundancy and service visibility?
  • What are the impacts and risks of the edge infrastructure?

Use case
  • Do we have experience with this type of use case / technology?
  • If yes, is there a history of significant errors and what were the root causes?
  • If the use case is a regulated activity, service or product and has the regulator been appropriately engaged i.e. regulatory sandbox?
  • How quickly do we need to be able to process the data?
  • Where is the ‘edge’? Is there external connectivity (e.g. to customers) or only internal (e.g. to corporate devices)?

Third parties
  • Are we using any third parties to design, deliver or run the solution?
  • What data (if any) will these third parties have access to?
  • Do we have a key dependency of a third party?
  • Have we established that the arrangement with third party falls under material outsourcing?
  • If yes, are we complying with the regulatory obligations such as notification and reporting requirements?

Resiliency
  • How quickly do we need to be able to recover the service?
  • Do we have a single point of failure?
  • Do we have a fallback plan in the event of service loss?

Regulation
  • Are we complying with the various regulations such as the proposed Digital Operational Resilience Act (DORA) or data related regulations in all the geographies where we operate?
  • Do we have adequate internal governance framework, strategy alignment and third-party monitoring in place for the edge technology?
  • Do we have appropriate processes and controls to ensure that all risks are identified, analysed, measured, monitored, managed, and reported within the limits of the firm’s risk appetite?

Conclusion

Whilst edge computing offers many potential benefits across a range of use cases, its full potential will only be realised if organisations are able to appropriately navigate key challenges outlined above.

To discuss further please contact us as below, or visit our Digital Risk hub for more information.

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1 https://finovate.com/5-ways-edge-computing-can-benefit-banks
2 In Deloitte’s survey, more than 80% of networking executives believe that advanced connectivity is very or extremely important to their ability to capitalize on advanced technologies such as AI, edge computing, and data analytics.

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