Edge finds use cases in retail and branch banking transformation

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In this RadioFinance session, we will discuss how deploying distributed cloud technologies at the edge of the network is redefining data agility for real-time insights. It will also highlight challenges and opportunities of utilising edge solutions to digitally transform the financial services industry at scale.

Technology practitioners and experts; Colin Dinn, Vietcombank; Supriyanto Supriyanto, PT. Pegadaian; Andreas Spanner, Red Hat; Michele Pelino, Forrester; and Brandon Koh, Intel; discussed what success looks like for financial services organisations looking to implement edge computing in their various IT environments, encompassing core systems, enterprise networks, IT operations and frontend customer engagement and experience.

In the financial services industry, edge computing could be a game changer that redefines the integration of internet of things (IoT) edge devices, low data latency and smart analytics to produce real-time insights and outcomes. It promises to reduce operational costs, mitigate system risks, improve network productivity and efficiency as well as transform the digital capabilities of institutions as well as engagement with their customers.

Pelino commented that the evolution of network computing to edge computing tracks the arc of a pendulum that has swung between decentralised and centralised architecture and processing. Today, edge computing seeks to optimise local operations while maintaining global or enterprise level efficiency, through a hybrid deployment of IoT devices and solutions for local workloads and cloud for enterprise workloads.

However, without a holistic strategy, institutions could end up implementing incompatible or fragmented edge solutions that may not be optimised for “workload affinity”. She and Spanner warned that the application of edge technology in finance is still nascent and there is no standard definition, best practice or benchmark for successful implementation, and institutions risk “undifferentiated” heavy lifting, without the necessary benefits or results.

Dinn emphasised that distributed network architecture and processing is not new but agreed that edge computing adds a new level of computing capability in form of IoT edge devices, solutions as well as advanced analytics enabled by artificial intelligence (AI) and machine learning (ML). He highlighted that a decentralised and open architecture creates a bigger "attack" surface for cybercrime that presents security concerns. 

Supriyanto shared the benefits of edge computing; increased network productivity, response time and improved customer experience. Pegadaian, the pawn and financial services subsidiary of Bank Rakyat Indonesia, implemented the edge-enabled software-designed wide area network (SD-WAN) as part of a network and branch transformation, to optimise connectivity and local operations of its 4,000 plus strong network of conventional and micro branches across Indonesia.

Spanner, responding to Dinn’s concerns over security, stressed the importance of consistent operating model and appropriate system solution. However, it is the choice of partner with the open system design and implementation experience and who can deliver "differentiated" outcomes that matters. “The lowest common denominator is really that consistent operating model from core to edge, to cloud,” he said.

Koh said with edge computing, “there are multiple types of business insights that can happen”, including content that can be distributed through high-definition media interface (HDMI) and content delivery network (CDN). Similarly, AI can also be delivered and run in a centralised or decentralised manner. “In some AI use cases, it makes sense to be implemented on edge computing,” he said.

Pelino and Koh also warned about the risk of solution fragmentation that may reduce the efficiency and efficacy of edge deployment and that institutions must address the issue of "workload affinity". Koh added that low data latency is critical to meeting the user experience and customer expectation of the future and will drive the adoption of edge computing, especially in digital transformation of retail and branch banking.

The following are the key discussion areas:

  • Insights of Asia Pacific financial institutions on edge computing environments, market trends and implementation steps
  • Power of modern edge architecture to enable low data latency to enable real-time insights and outcomes
  • Financial institutions’ priorities in optimising data and analytics for insight-driven business
  • Best practices and opportunities in deploying IoT-enabled edge use cases in the financial services industry
  • Overcoming challenges in implementing distributed cloud infrastructure

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