Finance
Retired Aussies facing sad $60,000 superannuation reality impacting millions: ‘Very real’
Australians now need a record amount of superannuation to afford a comfortable retirement, and one group is still lagging significantly behind. Women are approaching retirement with tens of thousands of dollars less in superannuation than men, but there are moves that can be made now to help close the gap.
By the age of 40 to 44, men have a median super balance of $108,344, compared to women with $79,445 – a gap of nearly $30,000. This gap peaks in the 55 to 59 age range, where men have $202,584 on average and women $140,662 – a difference of more than $60,000.
AustralianSuper deputy chief executive and chief member officer Rose Kerlin told Yahoo Finance while we’ve seen some improvements over time, the super gender gap is “still very real” and becomes the most obvious as women approached retirement.
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“A big part of the gap comes down to caregiving and disparities in pay. When women take time out of the workforce or move into part-time roles to care for children or family members, their super takes a hit, and that impact compounds year after year,” she said.
This gap is particularly worrying now that a single homeowner aged 67 needs a lump sum of $630,000, up from $595,000, to achieve a comfortable retirement. Couple homeowners need a balance of $730,000 in super, which is up from $690,000.
In contrast, the latest ATO data shows men at or approaching retirement at 60 to 64 have a median balance of $219,73, while women have $163,218.
The government has flagged reforms to help address the gap. Since July last year, superannuation has been paid on government parental leave payments.
From July next year, the Low Income Superannuation Tax Offset (LISTO) income threshold will increase from $37,000 to $45,000 to align with the top of the second income-tax bracket. The maximum LISTO payment will increase from $500 to $810.
While policy reform is important, Kerlin said there were also things women could do now to feel more on top of their super and more confident about where they’re headed.
“Small actions today can help build greater confidence and security for the years ahead,” she said.
One action could be making additional contributions, even small ones, whenever possible, as this could make a big difference over time.
AustralianSuper’s modelling found that someone who made after-tax contributions of $600 annually between the ages of 35 to 39 and met the eligibility criteria for the government’s co-contribution of $300 each year could retire with $9,000 more.
First home buyer Jessica Ricci was just trying to save a little extra money through her superannuation in a federal government scheme intended to help people like her. But an error from tax authorities has left her paying more tax than the top income bracket on some super contributions – ironically having the exact opposite of the intended effect of the policy.
As a result, she’s lost out on an extra $2,250 in savings that was supposed to go to her house deposit. While the ATO pushed back over who was at fault for the mix-up, her case has highlighted an increasingly problematic blindspot when it comes taxpayers getting the short end of the stick when dealing with tax authorities.
“I’m definitely feeling a little bit helpless,” she told Yahoo Finance. “There’s not a clear path to rectify this.”
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Jess was tipping extra money into her superannuation as part of the First Home Super Saver Scheme which has been running for years and allows eligible first home buyers to take advantage of the tax benefits of their retirement savings and then pull those extra contributions out to use for a house deposit.
As part of the scheme, individuals need to apply to the ATO, which in turn requests the related money from the person’s super fund.
Over four years, Jess contributed the maximum $50,000 amount, ensuring not to exceed the $15,000 yearly cap. She did so with the expectation of claiming the benefit at the time of her house purchase, as per the rules of the scheme.
When she went to make the claim, much of the information was auto-populated by the ATO website. And after receiving her funds, and the amount being less than expected, she soon discovered that her first contribution was wrongly classified as a concessional contribution, meaning $2,250 was, in the words of an ATO official, “retained by the ATO as withholding tax”.
She has spent months going back and forth with tax officials trying to get the money she believes should be owed to her.
“They’ve all taken the same stance, which is; ‘Well, yeah, we made a mistake, but you didn’t catch it. You said that what we provided you was fine, so it’s your fault’.
“I think it’s crazy to put the onus or the burden on the average person. I think most people would rightfully assume that pre-filled data provided by the ATO would be accurate,” she said.
Most coverage of artificial intelligence in finance focuses on what these tools can do. Less attention is paid to how they perform under scrutiny, particularly in financial modeling, where small errors can carry real consequences.
After testing Anthropic’s Claude in real-world modeling scenarios, one conclusion stands out: Claude produces outputs that look credible at first glance but contain structural flaws that only an experienced professional would catch.
That gap between appearance and reliability is where risk begins.
Where AI Performs Well
Claude handled several foundational elements of financial modeling competently. It was able to:
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Build basic revenue models
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Generate standard financial statements
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Apply consistent formatting, labels and units
The outputs appeared polished and professional. In some cases, they resembled models produced by junior analysts. That is what makes them risky.
The models looked right. The structure appeared logical. Formatting signaled credibility. For a time-constrained professional, those cues can create trust before a full audit is completed.
The Errors That Hide in Plain Sight
A closer review revealed issues that would likely go unnoticed without technical expertise:
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Broken linkages between financial statements
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Hardcoded values instead of centralized assumptions
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Non-dynamic formulas and inconsistent logic across periods
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Balance sheets that did not balance
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Timing mismatches between beginning- and end-of-period values
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Circular reference issues in areas like revolving credit
These are not edge cases. They point to a broader issue. The model may function, but it is not built on a reliable or auditable foundation.
Where Best Practices Break Down
Beyond individual errors, the models often failed to follow core financial modeling principles:
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Assumptions were not clearly separated from calculations
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Error checks were largely absent
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KPIs lacked depth and industry-specific nuance
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Formula design was inconsistent or inefficient
These gaps affect more than presentation. They determine whether a model can be trusted, adapted and audited under pressure.
The Real Risk Is Overconfidence
The key distinction is not between AI and human-built models. It is between models that are understood and those that are not. When a professional builds a model, every assumption and linkage is intentional. Even limitations are typically known. With AI-generated models, that understanding is outsourced.
This creates a different kind of risk:
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The logic behind the model may not be fully clear
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The structure may not align with internal standards
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The review process may be less rigorous because the output appears complete
In practice, credibility is inferred from how the model looks, not how it was built.
Reviewing Is Not the Same as Building
There is also a practical workflow issue. Reviewing an AI-generated model is not equivalent to building one.
When reviewing:
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You are interpreting logic you did not design
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Errors can be harder to trace
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Inconsistent structure increases audit time
In some cases, it is faster to build a clean model from scratch than to fix a flawed AI-generated one.
What This Means in Practice
Financial models support decisions involving significant capital. Even small issues can cascade:
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Misstated cash flows can distort debt capacity
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Timing errors can affect liquidity assumptions
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Weak KPIs can lead to incomplete analysis
There is also a question of accountability. Regardless of how a model is created, responsibility for its output remains with the professional using it.
Where AI Fits Today
AI tools can still be useful in financial modeling. They can help:
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Speed up repetitive components
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Generate starting points for analysis
But they are not a substitute for professional judgment. Nor are they ready to operate without close oversight. For now, their role is best defined as assistive, not authoritative.
A More Practical View of AI in Finance
The conversation around AI in finance does not need more optimism or skepticism. It needs more precision. AI can produce outputs that are visually convincing and directionally correct. In financial modeling, that is not enough.
The real risk is not that AI makes mistakes. It is those mistakes that are easy to miss, especially when the output looks finished. For financial professionals, the takeaway is simple: treat AI-generated models as drafts, not decision-ready tools.
The Reserve Bank of Australia is facing an incredibly difficult call. The Board meets next week amid continued uncertainty over the war in Iran, and a week out from a Federal Budget expected to contain some big changes. Against that backdrop, it is expected to slug mortgage holders and businesses with a hike in the official cash rate.
But borrowers could – and should – be spared another blow, according to some prognosticators going against the grain. As house prices in major cities are rolling over, certain economic commentators think the RBA should stand pat.
A hike would be the third in a row, but the second since surging fuel prices took hold.
“Because that interest rate increase — or the equivalent — has already come through in higher petrol prices, I reckon they might hold the line,” said David Koch.
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The Economic Director at Compare the Market, and regular Yahoo Finance contributor, believes the bank could wait for at least some of the dust to settle and see what’s in the Federal Budget on May 12.
“They’ll be thinking about whether oil prices will stay high for longer, because if the Middle East crisis resolves itself, oil prices will drop significantly — and that would take a big chunk out of the inflation rate,” he said.
He also pointed to deteriorating conditions in the economy and historically glum consumer sentiment as factors that could reduce demand that caused inflation to tick back up this year in Australia’s productivity constrained economy.
“Consumer confidence has plunged and business confidence has fallen to almost record lows. Consumers cutting their spending is bad for the economy because small businesses start to suffer.
“And bosses not having confidence is bad for the economy too, because they won’t invest and they won’t hire people. So the Reserve Bank doesn’t want to crush consumers and businesses with another interest rate increase,” he said.
The ANZAC Day weekend brought another soft result in auction clearance rates in the country’s biggest housing markets (with Adelaide being a notable exception). In Sydney, auction clearance rates on Saturday were 49 per cent (compared to 63 per cent a year ago) and in Melbourne was 56 per cent (down from 61 per cent the same time last year), according to Domain.
Economist and former advisor to the Gillard government, Stephen Koukoulas, also believes the right move is not to hike, and says a softening housing market could play a part in a surprise decision to hold.
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