NAB reports that 800 adaptive models steer its ‘client intellect’

At any given moment, NAB sifts through about 1000 customer data attributes using 800 adaptive machine learning models to fuel its innovative ‘client intellect’ next-best action framework.

Jess Cuthbertson, the executive overseeing customer analytics and decision-making, unveiled the ‘client intellect’ during a keynote at the 2024 PegaWorld iNspire conference in Las Vegas earlier today.

The personalization engine was previously mentioned as in the works starting in 2022, with additional project specifics disclosed in The Australian newspaper earlier this year.

The ‘client intellect’ is supported by Pega’s customer decision hub platform.

Regarding the bank’s cloud-native strategy, Cuthbertson mentioned, “Our Pega environments were operational within three weeks of finalizing our agreement.”

The system has been operational for approximately two years and encompasses 75% of customer interactions.

“With our ‘client intellect’ initiative, we managed to cover 75% of customer interactions within less than 24 months,” she stated.

“We rolled out over 150 next best actions ranging from service alerts to sales recommendations and personalized engagements,” she added.

The actions include reminders for in-app payments, timely updates during the home loan process, and special notifications for achieving financial milestones such as reaching savings goals or reducing mortgage debt.

Cuthbertson mentioned that on average, 65% of the bank’s customers access the mobile banking app at least twice daily.

“This offers us a fantastic chance to engage with them consistently and nurture ongoing conversations,” she explained.

The bank devoted significant effort at the outset to “gaining insights from customer data,” as well as consulting frontline bankers to identify potential customer issues based on their experiences.

“With our ‘client intellect’ program, we took our time to listen to customers through data, analyze net promoter scores, complaints data, and customer journey bottlenecks to enhance our services,” Cuthbertson remarked.

“We collaborated with bankers to understand their customer interactions and needs, which we then translated into actionable solutions within the system,” she continued.

She noted that the machine learning algorithms behind the ‘client intellect’ also monitor the effectiveness of actions and customer response rates.

“We currently leverage around 1000 customer data attributes to power the ‘client intellect’ – tailoring our actions in real-time based on customer interactions,” she highlighted.

Upon activation, the bank observed a 40% increase in customer engagement, leading to more relevant engagement with customers.

“This demonstrates our improved relevance in customer interactions,” she added.

She also mentioned that the ‘client intellect’ has granted bankers more confidence and time to engage with customers effectively.

“This allows bankers to focus on what matters – engaging with customers. Regardless of their tenure, it instills consistency and confidence in initiating customer conversations,” Cuthbertson concluded.

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AndyC

Andy Curtis is an award-winning security consultant, researcher and public speaker. He has been working in the computer security industry since the early 1990s, having been employed by state and federal government, leading healthcare and banking providers across three continents. He has given talks about computer security for some of the world’s largest companies, worked with law enforcement agencies on investigations into hacking groups, and is a regular voice on TV and radio explaining IT security threats.

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