WEDNESDAY, OCTOBER 21, 2026|No. 19540
Business · Banking · AI

Rising use of AI in home loan applications prompts fraud concerns

New data indicates that nearly one in five Australian borrowers have utilized generative AI to alter financial documentation for home loan applications.

Financial institutions are facing new challenges as AI tools make document forgery more accessible to loan applicants.
Financial institutions are facing new challenges as AI tools make document forgery more accessible to loan applicants.
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AI fraud in loan applications surges after RBA interest rate hikes

Generative AI has opened the door to a swift increase in liar loans and homebuyers squashed by higher interest rates are committing some of the highest rates of loan fraud.

Exclusive national polling has revealed nearly one in five Aussie borrowers, or about 18 per cent, have used artificial intelligence to create or alter documents for a home loan application.

The national poll commissioned by comparison platform OurTop10 found that bank statements topped the list of documents being altered, accounting for 10 per cent of application forgery.

This was followed by employment documents (9 per cent) and pay slips or proof of income (6 per cent).

A further 3 per cent said they had used AI to create or alter a competing lender’s interest rate offer. Respondents could select multiple options.

OurTop10 director Mansour Soltani said mortgage fraud was becoming more widespread because generative AI tools made it easier to create convincing false documents.

“Higher interest rates are reducing borrowing capacity, particularly for first-home buyers, and leaving some existing borrowers stuck in mortgage prison because they no longer qualify for a refinance,” he said.

“Some alter their paperwork to inflate their income or understate their expenses, seeing it as a way around those hurdles and a chance to ‘beat the banks’.

“The issue is that AI tools are evolving faster than lenders’ ability to detect false documents.

“As the technology improves, fabricated paperwork could become harder to spot, even for trained staff and bank verification systems.”

Younger Australians were more likely to report using AI to create or alter documents for a home loan application or negotiation, with 56 per cent of Gen Z and 36 per cent of Millennials claiming they had done it.

Bank statements or financial records were the most commonly cited documents among both groups, accounting for 33 per cent of Gen Z and 23 per cent of Millennial false documents.

This was followed by employment documents (19 per cent and 17 per cent, respectively) and pay slips or proof of income (19 per cent and 11 per cent).

“Younger generations may be more comfortable using AI in their day-to-day lives. That familiarity could make some feel more confident using it to alter mortgage paperwork, without fully thinking through the consequences,” Mr Soltani said.

“Borrowers need to understand that deliberately submitting forged documents to mislead a lender can lead to criminal charges.”

Overall, 82 per cent of Australians said they had never used AI to create or alter any loan application or inquiry documents.

“It highlights the case for secure data sharing between the ATO and banks, with the borrower’s consent, Mr Soltani said.

“That would give lenders an independent government source to verify declared income and help them make more informed credit decisions.”

The issue has attracted debate across financial institutions and regulators.

ASIC chair Joe Longo recently spoke to a parliamentary committee regarding traditional document-based underwriting in major banks, stating it remained a vulnerability.

Mr Longo warned that AI-assisted document fraud has become a “real emerging issue for the banks,” particularly as altered pay slips and statements become internally consistent and indistinguishable from genuine enterprise exports during manual reviews.

It’s worth noting that AI, despite its increasingly realistic-looking outputs, does create certain traps where document forgers can easily get caught, leading to criminal charges.

AI tools frequently make slight calculation errors across complex forms that do not match running balances or fail to match itemised transactions.

Many commercial PDF editors and image generators also leave digital metadata footprints indicating software generation.

PAN's pipeline reviewed approximately 1 open sources for this article. No human editor reviewed this article before publication.

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