So far, the most common business pattern for Generative AI has been “experimental”: choose one or two applications, try some limited and low-cost implementations, assess the results. While there have been some big partnership announcements connected with AI, major commitments have so far been rare.
Australia’s CommBank is bucking that trend – they’ve gone all in on AI and haven’t looked back.
CommBank (Commonwealth Bank of Australia) is a global public bank with over USD$800B in assets, USD$19B in annual revenue, and over 53,000 employees. In 2021, they developed a partnership with H2O.ai to expand the use of AI within their operations. More recently, they signed a letter of intent with Microsoft in March 2024 to use generative AI focused on customer experience (especially customer support), customer safety, and accelerating internal capabilities. They’ve published regularly on how they use AI, showing how it can be a powerful tool to accelerate banking and deliver incredible results for their customers.
Let’s dig in!
AI for Customer Protection and Engagement
CommBank’s vision of AI for their customers is very compelling – from CEO Matt Comyn:
“We aspire to be the trusted partner at the centre of our customers’ financial lives. To do this in an increasingly digital world, artificial intelligence is playing an even more important role in delivering personalised and relevant experiences. When these experiences drive demonstrably better outcomes for customers, this builds trust, confidence, and ultimately engagement – and the more our customers engage with us, the better we are able to anticipate their needs.”
To build this trust, a major focus for CommBank is preventing scams. In 2021, Australian customers lost more than AUS$2B to scams. Along with doubling the size of their scam prevention and protection team in recent years, CommBank is using AI to protect the 7.3M customers using their app with:
- NameCheck, which verifies that customers are transferring money to the people they intend to,
- CallerCheck, which uses the CommBank app to confirm whether a caller is a CommBank employee,
- Fraud detection through flagging unusual activity
To date, these systems have helped prevent or recover more than AUS$100M targeted at the bank’s customers.
CommBank is also using AI to enhance the customer experience in a number of other ways:
- The “BillSense” feature of the CommBank app helps customers predict and forecast cash flows,
- “Benefits finder” helps connect customers connect with unclaimed benefits and grants, to the tune of AUS$1B to date,
- AI is central to the bank’s “customer engagement engine”, which makes 53 million decisions a day,
- CommBank uses an AI system to remove abusive or offensive language in transaction messages.
Having written numerous case studies on AI for business, I find it both inspiring and refreshing to see all of the creative ways CommBank is using AI to help their customers.
AI in the Back Office
CommBank’s AI use isn’t just customer-facing, though; they also use it extensively within their business.
- Document scanning and data entry has traditionally been a very labor-intensive, low value-added activity. CommBank is using AI to scan and interpret customer documents automatically, cutting the time for data entry and analysis by 50%.
- Software engineers at CommBank were among the first in Australia to test Github Copilot, with the experiment delivering great results. 75% of their engineers found the system “very helpful”, and 1/3 of all recommendations (80k lines of code) ended up being accepted for production.
- Staff at CommBank also received early access to Copilot for Microsoft 365 (a general purpose LLM similar to ChatGPT; not specifically for code like Github Copilot). 85% of staff who used it said they preferred using it vs working without it, and 96% said they were more productive.
Those adoption numbers are terrific, and highlight how building a culture that is open to change and experimentation is very beneficial to organizational adoption of AI.
Key Takeaways on CommBank’s AI
There are two key items that stand out about CommBank’s use of AI.
- CommBank is open that they use a mix of both Generative AI and “Machine-Learning”-based AI. Generative AI is a relatively (commercially) new technology that creates original results based on its inputs. Conversely, machine learning – a long-term staple of data analytics practice – focuses on deriving insights from existing data and projecting those into the future. Systems like scam detection, cash flow forecasting, offensive text labeling, and customer insights can be done with both types of AI, although it’s frequently easier, cheaper, and more predictable with the ML version. Based on their public statements, it sounds like Generative AI specifically has been used mostly internally to date.
- CommBank has taken a very bold and strategic approach to AI, which more companies should emulate. Rather than tiptoe around the edges, CommBank recognized the potential value of AI, made commitments to enable deployment at scale, and has actively explored a wide variety of applications to offer value to the business and the customer. This is somewhat against my recent advice, but, through using a mix of Generative AI and ML-based AI methods, actively cultivating a data-focused culture, and keeping humans in the loop in early GenAI experiments, they have done a great job of both managing risk and delivering real results.
I want to come back to that quote from CommBank CEO Matt Comyn:
“When these experiences drive demonstrably better outcomes for customers, this builds trust, confidence, and ultimately engagement – and the more our customers engage with us, the better we are able to anticipate their needs.”
Building trust, engagement, and value with customer, and saving money along the way – CommBank demonstrates how AI can be a win, win, win.
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