It won’t be a surprise to anyone that the explosion in connected devices continues. Based on research by Ericsson,
it is predicted that by 2022 there will be 29 billion connected devices. These devices will range from connected cards, meters, wearables, home devices, building controls and consumer electronics. These devices, or “things” reside in the Internet of Things
(IoT). Each of these “things” generate data, and they typically generate it in large volumes. Across industries, these “things” are often based far from a data centre or a cloud, resulting in needing to send data back to a central location to be collected
and analysed. If action needs to be taken, direction is then sent back to the “thing”. To enable immediate action to be taken on critical data, the distance between the “thing” and the computing needs to be reduced. This is where edge computing comes in. The
edge is a place that isn’t a data centre or a cloud, such as a manufacturing plant, an office campus, an oil rig, or a retail banking branch.
Many would argue that Retail Banking has been using edge computing for some time already. Whether it is ATM’s, branch based processing systems or mobile branches, they have all encompassed what we would now considering to be elements of edge computing. What
has significantly changed though is the cost associated with managing this, as well as being able to deploy enterprise data centre grade equipment at the edge. This coupled with other advances in technology, especially in the domain of AI, provides new opportunities
for retail banks to utilise the edge to improve customer and colleague experience.
Location based services
The use of location based services, specifically via beacon technology, enables retail branches to bridge the gap between the digital
banking world (mobile banking applications) and the physical banking world (the retail branch). By successfully bridging these two worlds, retail banks can:
- Offer targeted campaign messaging to customers when they enter a branch. Potentially linking in activity the Bank has seen on other channels (i.e. a customer researching mortgages online) to prompt the customer to see a mortgage advisor whilst they are
in the branch
- Help customers navigate larger branches, by using indoor “wayfinding” technology to display maps of the branch and help customers find the services they want.
- Utilise proximity based beacons to be able to push content to customers based on where they are in a branch. As an example, if a customer is stood next to a set of mortgage posters, push an electronic mortgage leaflet to their device.
- Enable customers who have opted in or been identified by the bank to be pro-actively welcomed to the branch. This could be high-net worth customers, or potentially customers with special accessibility needs.
- Understand how customers are utilising the branch space; what routes do they take around the branch? How long do the “dwell” in certain areas? This information can help branch planners ensure the space is optimised to drive the desired outcomes.
Natural Language Processing
The ability to capture and analyse conversations at the edge can help retail banks improve the customer experience whilst also ensuring regulatory compliance. By utilising Natural Language Processing (NLP), a field of AI designed to understand spoken language,
retail banks can accurately transcribe sales conversations between a branch colleague and a customer, and then undertake sentiment and other analysis to understand the quality of the conversation – both from a regulatory standpoint (were mandatory phrases
read, did the customer understand etc), as well as from a softer brand perspective.
Video Analytics
Video data captured and analysed at the edge (i.e. in a retail bank branch) can help extract critical insights, help speed up reaction times and ultimately drive better business decisions. Adjacent industries such as retail shopping malls etc have been
doing exactly this for many years. By leveraging modern CCTV surveillance systems, which are often already deployed in branches, retail banks can utilise AI enabled video analytics at the edge to:
- Understand how customers are utilising the branch space; what routes do they take around the branch? How long do the “dwell” in certain areas? This information can help branch planners ensure the space is optimised to drive the desired outcomes.
- Understand sentiment of customers, by utilising facial expression analysis. Are customers happy, sad, annoyed etc. This could be in relation to general branch experience, when queuing or when looking at an advertisement within the branch space.
- Improve security by identifying known fraudsters or suspicious items or behaviour. Video analytics solutions can help identify suspicious behaviour (such as repeat loitering)
To conclude, whilst the edge isn’t new to retail banking, now’s the time for banks to leverage the changes in retail consumer expectations and focus on how advances in technology can help them get the edge on customer experience in the physical world.