Behind this AI is the woman shaping its future: Meet Lee Hatton, UBank

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Like our children—we build artificial intelligence (AI) in our own image. All is inherited: our bias, inclinations, habits, good and bad intentions are transposed into 1s and 0s, and then absorbed by these synthetic-thought thinking machines.

AI is better for it.

It’s true: companies leading the way in artificial intelligence have come to realise the most effective AI casts a very human shadow. Imprinted on AI are the creator’s fingerprints—human touches teaching AI to be more like us as well as interact better with humans—and this is a profound source of competitive advantage. It is human-centred AI, focused on engaging customer experiences that gives way to more profitable business outcomes.

To these ends, it should not be one walk of life that AI models its cognitive perspective or frame of reference. AI must be designed by a choir of eclectic voices, spanning diverse backgrounds across race, creed, colour, gender, sexual orientation, and belief system.

This team of AI architects must especially include women, who according to multiple studies, make up well less than 25 per cent of the data science and machine learning community.

And yet, there’s a growing movement of women leading major advancements or novel applications of AI. IBM has recently launched its inaugural IBM Women Leaders in AI in recognition of women advancing their companies journey to AI across diverse industries around the world. In this blog post, I highlight one of these leaders.

From bank teller to bank CEO: Lee Hatton, UBank

“From the way you answer the phone, to the music that people listen to on hold, to the digital experience, every single little piece counts.” – Lee Hatton, CEO, UBank

UBank CEO, Lee Hatton

Long before she was on a mission to disrupt financial services as CEO of Australia’s leading digital bank, UBank, Lee Hatton was a university student earning her way through school as a bank teller in New Zealand.

In the years leading up to her remarkable rise, Hatton was unknowingly sharpening her understanding of the average bank customer —an experience that would later define her approach to AI.

Hatton talked about the influence that period of experiencing customers every single day had on her as she cut her teeth on the front lines of financial services. She learned what customer experience means to real customers on the ground.

“I’ve been able to translate that as I have grown my career over the years, to always know that it’s about the person that’s sitting in front of you, or standing in front of you and that their experience is completely unique,” said Hatton.

Alongside this down-to-earth approach to customer experience, Hatton also harboured a love for evolving technology.

Smart investments and well-taken opportunities skyrocketed Hatton up to the top of strategy-making in financial institutions. This put her on the path to cutting edge tech as AI and data science continued to transform banks over the last two decades. But her early penchant for innovation as well as her client-first approach to the banking experience remained intact:

“Now see the technology that can personalise things so much for individuals, I just feel so excited about the technology [not only] being able to empower people, but humans being able to empathise, and care, and bring that extra element to customers every day.”

After becoming UBank’s CEO, Hatton’s obsession with customer experience and technology culminated in a hackathon with IBM. In 12 short weeks, an internal search tool to answer customer queries and based on IBM Watson Assistant and Watson Discovery was live.

RoboBrain and an accompanying conversational assistant called RoboChat were ready to serve clients and UBank employees.

Two halves of the same RoboBrain

“Every week at UBank as part of our executive team, we spend at least an hour listening to customer calls, or reading through RoboChat, or really looking at the customer experience.” Lee Hatton, Ubank

Rejecting the assertion of buying technology for technology’s sake, UBank ensured that there was a practical reason or tangible goal that benefited the customer before integrating new technology. Lee Hatton and her team identified the home loan process, which often proved a sticking point to would-be home buyers due to its complexity and cumbersomeness. This was a key customer experience problem that Watson Assistant and Watson Discovery could help overcome.

The results were remarkable for the customer experience. Since going live, RoboBrain and RoboChat has helped answer 50,000 client questions and increased the likelihood of successfully applying for a home loan application by 15 per cent. Hatton observed speed, efficiency, and delight as three immediate improvements:

“Something that used to take us 30 seconds takes us two seconds to achieve. It makes the customer feel great because it’s efficient. It makes our team feel great because they answer the question quickly, and they feel like geniuses,” said Hatton.

The takeaway: Not only does UBank have the capabilities of IBM Watson to thank for these impressive results, but the other half of the equation as well: the human factor. Handcrafted AI, built for humans by humans, means the employees get smarter, the clients get better service, and the bank continues to advance forward an innovative customer experience.

The AI built for everyone: A team effort between UBank and IBM

“Understanding AI, learning about what it can do, not being intimidated by it, knowing that it’s limitless, is just so critical. But the information can’t just be held by the few” – Lee Hatton, UBank

To build an AI that serves everyone, without bias, dissolving the gender barrier is a necessity. It is also our shared responsibility. Only through AI built with consideration of bias, the importance of inclusivity, and one that reflects the best of its creators can we truly build an AI deserving of the title: “great.”

IBM is committed to this mission, and I would encourage you to make the pledge to Be Equal.

Accelerate your journey to AI with a prescriptive approach. Visit ibm.com/data-ai to learn about how IBM’s ladder to AI helps you modernise, collect, organise, analyse and infuse all your data.

Author: Thomas LaMonte, Content Marketing Director, IBM Data and AI, IBM