Macquarie Bank works cognitive automation harder

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Macquarie Bank works cognitive automation harder

As more use cases for the technology emerge.

Macquarie Bank is uncovering more use cases internally for cognitive automation technology, including the removal of administrative work from customer-facing staff to preserve their time for more meaningful interactions.

Chief data officer Ashwin Sinha told FST Media’s Future of Financial Services summit that the pandemic had seen banks refocused on customer and partner wellbeing.

This is leading some, such as Macquarie Bank, to automate as much background work as possible that would otherwise draw time away from that wellbeing focus. 

“Since the start of the COVID-19 pandemic, we have been very focused on the welfare and wellbeing of our employees and our clients,” Sinha said.

“We’ve swiftly implemented a number of initiatives to make sure that our employees and clients are taken care of.

This includes our work on ‘payment pause’, which is related to how we look at clients who are facing financial hardship, equipping our staff to have difficult conversations with clients who are facing financial hardships, while taking care of staff health and safety.”

Sinha predicted automation would become “front of mind” for most banks as a way to meet increasingly high user expectations.

“For us, automation is about fundamentally making use of technology, data and digital to drive any of the manual activities in an automated manner without human intervention,” he said.

Within Macquarie Bank, the focus is on cognitive automation, which essentially uses data and advanced analytics to constantly improve the way an automated process works.

“The bot can learn from a whole range of historical data, and a whole range of diverse patterns on how it should be responding in a certain situation,” Sinha said. 

For example, Sinha said, two customers could outwardly have the same reason for calling Macquarie Bank, but variables in their individual situations could warrant vastly different treatment.

Macquarie Bank wants to use machine learning to recognise these intricacies in a customer’s situation and put them on a path to resolution faster.

Four implementation zones

Macquarie Bank is applying cognitive automation in the workplace, contact centre, and to specific wellbeing and fraud prevention use cases.

In the workplace, Sinha predicted that a new level of automation is needed.

“More and more workplaces are going to become digital, so if you think about it, all the physical documents and forms are going to move to digital-only interfaces,” he said.

“That is going to make the data available and accessible in quite an easy form for a whole range of analysis, which is going to help us in improving the employee experience, as well as improving the client experience and helping service them a lot better.”

In the contact centre, cognitive automation is anticipated to take over administrative work and even call triaging, meaning agents are free to deal with challenging conversations.

“There has been a lot of work already done in this space over the last few years with respect to automation, and that work is going to keep going,” Sinha said. 

“What is going to become more relevant with respect to contact centre is that centres will become one of the key channels to have meaningful conversations with customers, and that is how we see it at Macquarie Bank. 

“Whenever we have an opportunity for human interaction, we need to make sure that it is authentic, very meaningful and that we are deeply connecting with each other.

“To do that, we'll have to create capacity with our contact centre agents to have those conversations, and a lot of the routine tasks which they do could be easily automated using aspects of cognitive automation.

“[It will help us] look at why a client is calling us with regular frequency, how are we going to respond to their needs, and whether we can digitise some of those processes so that our agents can have much more meaningful and deeper conversation with the clients and help them in different situations.”

Specifically on the wellbeing front, Sinha noted the work occurring across the finance sector “looking at the financial wellbeing of clients”.

“That is [occurring] by making information available to them based on their own transactions, which is related to how they are spending, their income, and where they are spending most, so that they can manage their cash flow and financial position better,” he said.

What is going to become increasingly relevant is how we monitor and measure that wellbeing and how we continuously make that sort of information and insight available to different players, and look at different aspects of automation to take routine tasks away.”

Sinha only briefly touched upon fraud - traditionally a strong use case for big data and analytics technology.

He said cognitive automation would help Macquarie Bank to “really expand the capabilities which we have in the fraud space in terms of responding to a whole range of different fraud scenarios.” 

“What it is also going to do is create a need for real-time response,” he added.

Sinha said that the use cases were by “no means a very comprehensive list” of how far cognitive automation could be driven into the bank’s environment.

“This is just indicative of the areas we are focused on and what I think is going to be relevant and front of mind for most of the banks when they start thinking about cognitive automation,” he said. 

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