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Doctored bank statements, altered contracts, and AI-edited PDFs can easily pass as genuine on first inspection, particularly when brokers and lenders are working through high volumes of applications under tight deadlines.
Fraud remains a major challenge. PwC’s 2024 Global Economic Crime Survey indicates that 41 per cent of organisations worldwide experienced some form of economic crime or fraud in the past 24 months, with procurement and customer-related fraud among the most disruptive categories.
In Australia, manipulated financial documents are becoming a greater risk for SME lenders, particularly in fast-moving lending environments, where brokers and lenders are processing applications at speed. As a result, more lenders are looking at AI tools to help spot inconsistencies earlier in the credit assessment process.
From my perspective as CEO of Moneytech, AI is increasingly being used to identify anomalies that are difficult for humans to spot, particularly when large volumes of documents are involved. But this is nothing new, it’s been going on since the dawn of time, only its easier than ever now.
Fraudsters are getting smarter, but so is the technology being used to counter them. AI doesn’t replace human expertise – it enhances it, providing an additional layer of scrutiny that can help reduce risk for brokers and their SME clients.
Across the lending sector, I’m seeing more examples of AI surfacing inconsistencies in documentation that initially appear sound.
It’s not about assuming wrongdoing – it’s about identifying early indicators, so they can be properly reviewed by experienced credit teams.
In my view, brokers remain a critical part of maintaining integrity in the lending process because of their understanding of a client’s business operations and financial position.
Brokers often have a deeper understanding of how a business actually trades.
If financial documents don’t align with the way a business operates day-to-day, that can be an early signal that something needs further clarification.
The issue is particularly relevant for small and medium-sized businesses, which often lack the time or resources to independently detect fraudulent activity, especially when it involves documents tied to cash flow, supply chains, or trading agreements.
In my experience, SMEs are focused on running their businesses.
In fast-moving lending environments, it can be difficult for anyone to detect when documentation has been altered or misrepresented. Technology can help validate information more efficiently, which in turn supports greater confidence throughout the lending process.
AI-assisted analysis is also influencing how brokers engage with their clients, by highlighting irregularities in bank statements or cash flow patterns that may warrant further discussion.
Brokers consistently tell me that having clearer, more objective information improves the quality of their conversations with clients.
AI helps provide that clarity, supporting better decision making, while ensuring experienced credit teams are still making the final call.
In my experience, the most common warning signs tend to involve inconsistencies across documents, where bank statements, financial statements, and ATO records tell slightly different stories.
When brokers take the time to sense-check those details before submission, it helps reduce delays and strengthens the overall quality of the application.
As fraud tactics continue to evolve, I believe the role of AI in detection and prevention is likely to expand further. The goal is a safer, more resilient lending environment.
One thing that can't be substituted in lending, is the human "gut feel" or experience. One example is a credit manager or BDM going out to meet a company director in person and doing a tour of their premises. Walking around the warehouse and checking out how old the stock is by seeing how much dust is on the inventory cannot be replaced by AI.
The most powerful fraud prevention tool will be a combination of AI, common sense and experience. Post Covid, we have also seen a major uplift in applications where a borrower is based in one state, the broker in a different state, and the lender somewhere else which causes significantly higher fraud risk, even with the use of AI.
Moneytech is building and utilising self-developed AI tools to prevent document fraud, but there are plenty of fantastic companies building AI tools in this space such as DoxAi, Equifax, and many others which in combination with lenders, will strengthen defences against an ever-evolving landscape of fraudulent activity. Another fraud mitigant working in favour of the good guys, is direct API's.
As technology progresses, so does the ability for non-banks to directly integrate into a borrower's bank accounts, accounting software, ATO data, etc. By going direct to the source, it helps prevent manipulation of the potential borrower or referral partner providing you with AI edited documents for verification.
When technology is applied thoughtfully, it strengthens trust across the ecosystem – helping brokers and businesses feel supported, protected, and confident as they navigate increasingly complex risks.
Nick McGrath is CEO of Moneytech, a non-bank lender specialising in SME lending.
[Related: Will AI help or hinder the fight against mortgage fraud?]