AI Transformation and Data Governance in Fintech

Our recent FinTech Friday webinar provided a useful platform to share and consider significant insights into the current relationship between artificial intelligence and financial technology.

In case you missed this edition of our monthly webinar series, please enjoy this summary of some key points of the conversation. Our guests shared with Tim Aman, BDO's Global Fintech leader, their analysis of how the efficiency, precision, scalability and personalisation offered by AI can benefit the fintech and financial services sectors globally. With a focus on the foundational value of data integrity, the discussion also included an Australian perspective on fintech uses of AI, regulatory issues and change management strategies for managing the interplay between AI and the financial sector.

Underlying the conversation was the understanding that AI makes it increasingly difficult for customers using financial products to untangle where technology and financial services begin and end. Financial services are being intertwined with technology, as exemplified by the Apple Card in the U.S. We anticipate this will only continue, with AI expected to contribute at least $15 trillion to the global economy by 2030.

Why AI

In the fintech space, AI can be defined as any suite of tools that simplifies teaching a computer to do smart things and in a human-centred manner, said Michael Bottala, Director of Strategic Insights at Mindbridge AI.

“There are so many opportunities to take on a really complex situation and simplify it for somebody - and being able to do that on a continual basis,” he said. “The capabilities continue to expand. We’re starting to see it, you know, really take over from a business perspective more.”

AI transformation has several strategic objectives, many falling under one of two umbrellas. First, there’s the way AI can guide fintech service providers with internal, operational processes. Separately - and still very related - there are many ways AI can benefit customers as they utilise financial services.


From a business perspective, AI can be of great benefit as a source of advanced and predictive analytics essential for decision-making. In the fintech sector, specifically, AI can be applied to:

  • Credit scoring and direct lending
  • Fraud detection
  • Predictive analytics
  • Market research and sentiment analysis
  • Insurance
  • Regulatory compliance

In the Australian context, robotic process automation (RPA), in particular, is driving solutions that replace iterative manual tasks previously requiring time-consuming processing. Implementing RPA is a boon for efficiency and effectiveness.

Blockchain, a remote digital register enabling various payment processes, is also supporting a lot of automation, he added. Open banking allows fintech service providers and banks to share customer information for a more level playing field.


Quite simply, AI has made life easier for customers, who have access to their bank and their superannuation funds in the palm of their hands to use as they see fit.

Via machine learning, AI enables financial services providers to create a personalised experience, be it by way of logging in to an account with facial or voice recognition as well as the elimination of overdraft charges. In the past, Bottala said, banks would charge $20 overdraft fees when a transaction drew an account into the red. Now, thanks to the power of predictive analytics, AI can recognise that a customer will be paid via direct deposit shortly and that the account will be back in the black in short order: No need to levy a fine when the problem will sort itself.

Change management

When traditional financial services decide they want to incorporate AI into the way they do business - internally or by creating a product set for customers - it’s essential to work with a strong change management focus. Kock advocated for a focus that begins with the end goal as the starting point. Managers will need to work collaboratively from the top down through the organisation to break down silos and create a more user-friendly, end-focused experience better connecting with the customer even through to the back end.

“For a project to be successful at the end of the day, if you don't have that sponsorship right - at the top - You typically are not going to get very far,” he said.

Data governance

Given the volume of data needed to make AI usable, a strong sense of ethics as well as careful consideration of privacy considerations and regulatory compliance are paramount for success.

“AI operates like a human, so in a lot of ways AI should be regulated like a human, because it tries to take on that similar thought pattern,” Bottala said. “We’re still at the very early end of things where we’re trying to see how it’s impacting different areas and respond accordingly. We’re a little more reactive at this point”.

In Australia, where the Australian Privacy Principles govern the space, key considerations include the integrity of data as well as the responsibility of organisations to take steps to protect information. 

There are myriad more ways to think about the fintech sector and AI. For more about the ever-evolving fintech space, please consider joining future Fintech Fridays webinars.