Moneytech says strong governance and human oversight are key to unlocking the full potential of AI in SME Lending
AI adoption in SME lending is accelerating, and with it comes a renewed focus on how technology can drive efficiency while strengthening trust. As automation becomes more embedded in credit processes, lenders are balancing innovation with transparency – particularly in a regulated environment where outcomes must be clearly understood and justified.
Moneytech, one of Australia’s leading non-bank lenders to SMEs, says the next phase of AI in lending is about combining innovation with governance frameworks that enable responsible scale. The objective, according to the lender, is to use AI to streamline internal processes, improve turnaround times and create clearer outcomes for brokers and their SME clients.
Explainable AI allows lenders to see which variables are influencing a credit outcome and how those variables shape the final recommendation. That visibility means understanding what’s driving a result and being able to question it if needed. It may involve recognising how changes in revenue, cash flow trends or sector exposure influence a recommendation, rather than simply accepting a model’s output at face value.
Nick McGrath, CEO of Moneytech, said AI presents a significant opportunity to simplify internal processes and improve service levels, provided governance and explainability are embedded from the outset.
“AI is reshaping the way we lend, and we see significant opportunity in using it to reduce manual processing and improve efficiency,” McGrath said. “We’re already seeing how automation can reduce manual workload and highlight trends earlier in the assessment process. But to unlock that potential, explainability and strong oversight need to be built in from the start.”
For brokers, explainable AI offers clearer insight into how applications are assessed, helping them guide clients with greater confidence and reduce unnecessary back-and-forth during approvals.
McGrath said the real strength of AI lies not in automation, but in the structure it brings to decision-making. While lenders are increasingly using AI to assess financials more efficiently, he believes long-term success will come from adopting the technology thoughtfully rather than aggressively.
“AI should enhance human judgement, not replace it,” he said. “When models are transparent, brokers feel more confident, customers know what to expect, and regulators can see the right controls are in place.
“In credit decisioning, an AI model isn’t useful unless you can understand the drivers behind its recommendations. Explainability allows us to ensure those drivers reflect SME trading cycles, cash-flow behaviour and sector dynamics, while enabling ongoing monitoring of model performance,” he added.
Regulatory guidance in Australia is reinforcing this direction. ASIC’s 2024 report Beware the Gap1 emphasises governance and oversight in AI use, while the National AI Centre’s 2025 guidance highlights explainability and accountability as core principles.2
Over the next 12 months, Moneytech will prioritise AI applications in high-volume document assessment and structured data interpretation – including bank statement analysis, ATO documentation review and invoice verification – areas where automation can improve consistency and turnaround times while remaining subject to review.
“These are practical applications that help us improve efficiency and service levels for brokers and customers,” McGrath said. “The competitive edge won’t come from adopting AI the fastest – it will come from building systems that regulators, brokers and customers can trust.
“In lending, trust is everything. It’s not about moving fast for the sake of it – it’s about using technology responsibly and building long-term confidence,” he concluded.