‘Innovation at our core’: ASX fintechs leverage AI to further disrupt banking sector

ASX fintechs says their ability to adapt and innovate places them at forefront of adopting cutting-edge tech like AI
MONEYME says generative AI creates a substantial advantage for companies with the right technology to harness its capabilities
Wisr says looking after its customers as AI is adopted within the organisation is paramount

In a rapid evolution of the financial landscape, ASX fintechs are reshaping traditional banking norms, carving a niche by offering innovative, convenient financial solutions and leveraging advanced technologies including artificial intelligence (AI).

Traditional banking, once synonymous with brick-and-mortar institutions, is facing an unprecedented challenge as fintech disruptors gain prominence, change the way people engage with financial services and bring cutting-edge solutions to the forefront.

The rise of AI and its adoption by fintechs is further transforming banking and financial services, challenging conventional norms and setting new standards for efficiency, accessibility, and customer-centricity.

So just what does AI, the hottest topic in tech right now, mean for the future of ASX fintechs? We caught up with three players to find out.

MONEYME (ASX:MME)

Managing director and CEO Clayton Howes says generative AI creates a substantial advantage for companies with the right technology to harness its capabilities and the opportunity for enhanced efficiency and elevated customer experiences is highly relevant to the fintech industry.

“It completely changes the game for how we can build digital experiences,” he says.

Howes says in the past MME has delivered customisation through automated, predetermined workflows but generative AI goes beyond mere customisation to deliver true personalisation.

“Using intelligence, we can create dynamic, personalised workflows that adapt to the customer in real-time, marking the next evolution post-digitalisation,” he says.

“In terms of customer service, responses to customer inquiries can be crafted in mere seconds, and personalised.”

He says predictive responses are more than just a time-saver and can ensure accuracy and consistency in language.

“This can, for example, help bridge the language gap for offshore customer service agents.”

Howes says the agility of fintechs positions companies like MME as frontrunners in embracing innovations like AI.

“Compared to traditional banks and incumbents, we have innovation at our core,” he says.

“The ability to swiftly adapt to new technology is ingrained in our DNA, allowing us to move fast.”

Howes says its proprietary technology systems enable a testing environment that fosters in-house creativity.

“We are not encumbered by the limitations of third-party platforms or tied up in lengthy, multi-year projects to transform banking.”

Howes says the ethical considerations of AI is crucial for any sector, and for financial services in particular, due to the information for which they have access.

He says as AI evolves rapidly with diverse applications, a regulated code of practice is warranted to ensure transparency and protect consumers.

“Establishing clear information policies and applications to govern the use of data is essential to ensure that customer vulnerabilities are not identified and exploited for financial gains,” he says.

“Customers should also be made aware when they are interacting with AI, striking a balance between innovation and ethical responsibility.”

Furthermore, Howes says one of the big concerns of the application of AI in financial services is that it will perpetuate or increase subconscious and institutional biases.

“This is particularly important when we consider customer service, credit decisioning, and data analysis,” he says.

“We are a Certified B Corp, with ethical and ESG principles considered in all of our operations so we are carefully considering this in the way we implement AI.

Howes says it’s also important to note that AI is not about replacing jobs.

“We believe it should be used to enable individuals to engage in more meaningful tasks,” he says.

Wisr (ASX:WZR)

Non-bank lender WZR also believes AI has a role to play in the fintech industry but says it is taking a slow and steady approach to its adoption.

CEO Andrew Goodwin says for WZR, which centres its business around financial wellness for its customers, including education, empowerment and different lending options says looking after its customers as AI is adopted within the organisation is paramount.

“Our first priority is the safety of our customers and company data,”

“We have an internal sandbox process to assess, explore and test generative AI and AI discoveries safely.”

He says employees from across all business units are researching and looking at AI.

“It enables us to consider how we could use AI, review what’s already fit for purpose in the market, how customers view AI and test different hypotheses with identified business outcomes and risks,” he says.

“We see future possibilities in risk assessment, serviceability and day-to-day business efficiencies.”

Harmoney Corp (ASX:HMY)

HMY is a consumer-direct personal lender in Australia and New Zealand, offering fast unsecured personal loans at competitive rates, all accessible entirely online.

At the core of HMY’s operations lies its trademarked digital lending platform, Stellare, which can swiftly process, authorise, and finance the majority of loan requests within a day.

HMY says Stellare revolutionises the conventional credit evaluation model by introducing a predictive behavioural analytics engine, driven by machine learning.

The platform scrutinises extensive, firsthand consumer data, enabling automated credit decisions and more precise risk-adjusted pricing, surpassing the industry’s traditional credit scoring methodology.

CEO and managing director David Stevens told Stockhead right from the outset Harmoney was founded with AI and machine learning at its core.

“It helps us to fairly assess customers’ financials instantly and fully online,” he says.

“The AI assessment of credit worthiness reduces unintentional human bias in the process, which can increase access to credit products for some people.”

Stevens says there’s a big paradigm shift between what it means to be a software development team today, even if you use AI and machine learning in your platforms and what it means to use the next generation of generative AI and large language models (LLMs) such as ChatGPT.

“It means a different approach to governance, different technical skills, different partnerships, different risks – but for the companies that are able to move quickly and innovate it also opens up a huge set of new opportunities and capabilities to deliver new products to our customers,” he says.

“If you think of it as just a new technology to add to your stack, I don’t think you’ll be particularly successful – or at least it will be relatively superficial.

“That head start is going to help companies like ours, and will be difficult for legacy organisations to transform.”

He says HMY is also building new experiences with generative AI that help customers check for errors during loan applications, speeding up the process and reducing declines due to mistakes.

“It’s important that companies set themselves up with great partnerships, but as we’ve seen in the OpenAI situation over the last few days the landscape will change rapidly over the next few years so real agility will be critical,” he says.

“AI tools and generative AI will help us offer more personalised experiences at scale, without the overheads and costs associated with legacy financial institutions.”