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Dreamforce 2024: Absa ropes AI into banking challenges

At the annual Salesforce conference in San Francisco, the South African bank was showcased for the way it is navigating the complexities of AI, writes JASON BANNIER.

Absa is tackling the challenges of balancing AI-driven efficiency with personalised customer service, leveraging Salesforce’s cloud-based CRM technology.  So effective has it been in this process, that it was showcased as a case study during Dreamforce, the annual Salesforce conference in San Francisco, last week.

Dreamforce 2024 attracted more than 44,000 attendees, making it one of the biggest technology conferences of the year. Absa uses a number of Salesforce products and platforms, such as Customer 360 and Salesforce’s Financial Services Cloud.

Absa’s approach has enabled the bank to deliver more seamless, personalised experiences while maintaining a strong focus on automation and ethical data practices.

“The customer is central to everything we do,” said Lindelani Ramukumba, chief information officer of relationship banking of Absa Group, during a streamed keynote address at Dreamforce 2024. “We have always known that we always have to provide the customer with whatever they need regardless of the channels that they require.”

He outlined the bank’s approach, which spans ten critical pillars, including operational efficiency, data and analytics, ethical banking, cybersecurity, cloud computing, and infrastructure modernisation. A key component of this is ensuring that customers can engage with the bank through their preferred channels.

“You can imagine a customer that is at a farm, we will go to them at the farm. A customer that comes to our mobile channel, we can meet their needs through the mobile channel. A customer that comes via the web, or walks through the branch. So regardless of whatever which channels they prefer, whether that is to the contact centre we have, we have enabling ecosystem powered by Salesforce that enable us to meet the customer.”

Absa’s investment in Salesforce’s Customer 360 platform has played a crucial role in refining customer journeys while boosting efficiency. However, it may appear as a complex and potentially conflicting challenge to deliver exceptional customer experiences while also ensuring operational efficiency.

“Balancing delivering customer experiences that will wow the customer and obviously operational efficiency seems like two bulls at a kraal.”

Despite this, Absa has successfully placed emphasis on its Salesforce ecosystem to unify customer data through Customer 360, said Ramukumba. This helps streamline processes and automate workflows, allowing the bank to deliver both exceptional customer experiences and maintain operational efficiency, effectively balancing the two goals.

Ramukumba also spoke highly of Absa’s adoption of Salesforce’s Financial Services Cloud, describing it as a transformative move.

“Because Financial Services Cloud data model comes already with pre built in accelerator for either your insurance or your wealth management or specifically in retail banking, that has given us an accelerator in closing the gap around rather than to custom build everything ourselves, we’ve got this template we can start from, which obviously reduces the time to market doing things like portfolio management.”

As for AI and data transformation, he advised leaders to take a cautious, thoughtful approach.

“I think go slow to go fast. It’s very key that your AI strategy, even though it’s being underpinned by Salesforce, is grounded by what strategy are you trying to drive? What value are you trying to create? You are creating these capabilities for the customer. So that must be at the centre of what you’re trying to do.

“Key also is to be aware that you always have to be nimble, agile and be willing to unlearn many things. As we have seen over the past six months, the space of AI has been changing rapidly. So you have to be willing to be nimble and unlearn and learn new capabilities or new ways of doing things.

“As a bank, I think also practicing ethical AI is quite key. Governance and risk and making sure that whatever you do with this AIs the data that you work with as you train, you are very careful because you’re working with customer data.

“We always say the quality of data also matters. If you’re dealing with poor quality data, it doesn’t matter how wonderful your algorithms are, if the quality of the data you’re dealing with is only going to cause more harm.”

* Jason Bannier is a data analyst at World Wide Worx and writer for Gadget.co.za. Follow him on Twitter and Threads at @jas2bann.

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