Macquarie Group, the Sydney-headquartered financial services multinational, is ramping up stress testing across its growing exposure to software businesses as artificial intelligence reshapes technology markets.
The group, one of Australia’s most internationally active finance firms known globally for its banking, asset management and infrastructure investing operations, is taking a more forensic approach to assessing software-as-a-service risk inside its balance sheet and private credit book, as uncertainty over AI’s impact spreads through global markets.
Shemara Wikramanayake, Macquarie’s chief executive, told investors recently that “a quarter of Macquarie’s balance sheet investments and private credit loans involved software-as-a-service businesses,” a sector now facing sharp valuation pressure as investors question whether increasingly sophisticated AI platforms could erode revenue growth.
“Currently, we don’t see any big issues, but the percentage that’s exposed to [software as a service] that could be replaced by AI and particularly seats-based revenue, we think, is small,” Wikramanayake analysed.
For QA and software testing teams across banking and financial services, the comments underline how stress testing is no longer limited to traditional credit or market risk, but increasingly extends into software business models, platform dependency, and AI-driven disruption scenarios.
Macquarie was “forensically looking” at its exposures and what could play out over the next seven years, Wikramanayake said, according to the Australian Financial Review.
“We do cash flow lending … we look at the resilience of those cash flows,” the bank’s boss said.
The group’s private credit book has continued to expand, increasing by 12 per cent since the end of September to reach $29 billion by year end, adding further urgency to the need for deeper portfolio stress testing as software risk becomes harder to model historically.
Andrew Cassidy, Macquarie’s chief risk officer, reportedly said the firm was focused on assessing software company business models and “more rigorously stress testing its portfolio.”
“As part of that stress testing process, we will look at different components of our credit book and our equity book, different sectors, different products, we will stress those in a more severe fashion than we’ve ever seen in the historical data,” Cassidy explained.
Software valuations
The renewed scrutiny comes as AI developments have unsettled software valuations globally, with platforms such as Anthropic’s Claude accelerating investor concern that AI could compress margins and disrupt entrenched SaaS revenue models.
Macquarie Capital head Michael Silverton said the bank’s exposure was concentrated in enterprise software embedded in regulated and specialised industries including insurance broking, education and services.
“We’re clearly watching this closely because the headlines are coming every day,” Silverton said, adding he was confident loan loss rates would “hold as they have historically”.
Market observers cautioned against assuming widespread impairments. Atlas Funds Management’s Hugh Dive said the shift in sentiment had been abrupt.
“This particular area has gone from a darling to a bit of a concern to the market in about five days,” Dive said, though he added: “It’s hard to make the case that all these companies are in a lot of trouble.”
Firetrail Investments portfolio manager Scott Olsson reportedly said the breadth of AI disruption risk remains unclear.
“At the moment, it’s still quite unclear what type of software exposure it is because there’s obviously a wide spectrum of businesses that can be disrupted by AI and ones that have a larger moat,” he said.
Macquarie’s comments, reported by the Australian Financial Review, come alongside a broadly positive quarterly update, with higher profits across its four divisions and improved income in its commodities and global markets business.
But for financial services QA, testing and resilience teams, the bank’s sharper focus on software exposures highlights a wider industry shift: AI disruption is increasingly being treated not just as a technology story, but as a balance-sheet stress testing problem, one that demands more severe scenarios than historical data has ever provided.
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