New research has revealed AI is set to reshape how Australia’s lenders process and approve loans.
A new white paper has found that lenders are significantly integrating artificial intelligence (AI) and automation into mortgage workflows to handle growing volumes, tighter regulation, and more complex credit profiles.
The Australian Lending Technology 2026 research, released by lending technology company NextGen this week, has revealed that AI is now viewed as the next major lever for operational efficiency across banks, non-banks and specialist lenders.
The independent research surveyed 132 Australian lending professionals and senior executives to uncover the challenges and opportunities defining competitive advantage in 2026.
Just over a third of respondents (36 per cent) identified AI and automation as the trend that would have the most significant impact on lending over the next two years, placing it alongside open data and regulatory change.
The strongest consensus was around back-office use cases, with 82 per cent of lenders stating that AI should deliver the most value in document processing and workflow automation.
Meanwhile, 79 per cent pointed to fraud detection and compliance monitoring as a key target.
The report also found sizeable expectations in credit and risk, with 68 per cent highlighting credit decisioning and risk scoring, and 46 per cent pointing to predictive analytics for portfolio and risk management.
From OCR to intelligent document handling
One of the most notable shifts detailed in the paper was how lenders were changing the way they handled documents and data.
Where document verification once relied heavily on optical character recognition (OCR) tools and manual checks, NextGen said lenders were now deploying AI models that could handle unstructured data with greater accuracy and speed.
It noted that instead of staff manually cross-checking income, identity, or asset information, AI could ingest a wide range of formats and extract key details in near real time.
According to the paper, credit assessment was also shifting, with AI-enhanced decision engines increasingly being used to analyse more complex financial scenarios and detect patterns.
Yet the authors stressed that the industry was still in the early stages of deployment, with most current value coming from practical, contained applications rather than fully autonomous systems.
Scaling ‘human-led’ models, not replacing them
The report said that by automating routine processes and stripping out low-value manual work, teams could then manage higher loan volumes.
This, in turn, would free up experienced staff to prioritise complex credit scenarios, nuanced customer situations, and relationship management.
Yet the research found that most organisations remained wary of going all-in on fully autonomous lending.
Human judgement was described as “still central” for complex decisions, sensitive customer conversations, and scenarios that required empathy and creativity.
Co-founder of non-bank lender Skip, Mario Emmanuel, said the focus was on scaling a “human” proposition, with smarter tools behind the scenes.
“AI empowers our Australian team with data-led insights and automations which ‘skip’ over manual data entry and enable more applications by removing easily automated tasks,” he said.
End-to-end advantage for integrated players
While many lenders are still piloting AI tools, the research showed that the greatest competitive edge would go to those that embedded AI throughout the entire mortgage life cycle.
National sales manager – broker at ING Australia, Sergio Delvescovo, said the advantage would flow to lenders that treated AI as part of a coherent technology strategy.
“It requires a unified tech stack which enables end-to-end automation, real-time insights, and personalised experiences that competitors can’t easily replicate,” Delvescovo said.
The report reinforced the human-plus-machine model.
“The winning formula combines AI’s speed and consistency for routine tasks with human expertise for relationship-building and complex problem-solving,” it outlined.
The white paper concluded that lenders who deployed AI strategically in high-volume, repetitive areas could drastically lift efficiency while redirecting human expertise.
“This balanced approach enables profitable scaling, faster SLAs and enhanced customer experiences without sacrificing the judgement and relationship skills that differentiate lenders in competitive markets,” the report reads.
[Related: ASIC urges lenders to help shape roadmap for AI innovation]
