“The AI models used in the sector can be based on data, and if we can teach the models about how to identify fraudulent events, then it has the potential to help,” Mr Tokhi said.

“From an SMSF software point of view, there are definitely patterns in the data that AI can detect and bring to the attention of accountants or auditors, but unfortunately it’s usually the case that this happens after the event has already taken place.”

Mr Tokhi said the use of technology brings with it inherent risks.

“We’ve seen things like fraudulent super funds being created to transfer money out of other entities,” he said.

“SMSFs are stricter in regard to anti-money laundering and know your client checks that are done.”

He added that within the SMSF space, the other issue that AI could provide support for is detecting early access events.

“It may not be a fraudulent event but it’s probably an illegal event that's taken place,” he said.

“AI is getting better at stopping fraud and it’s also improving in stopping any sort of money transfer that shouldn’t be taking place, whether it’s a fraudulent investment or a fraudulent super fund that has been established.”

Mr Tokhi continued that several compliance issues must be considered if an adviser or auditor implements an AI-based solution to their business.

“These compliance concerns are probably not even limited to AI. It's any technology solution that you're implementing in your business,” he said.

“Things that need to be considered by clients when they look at a business that uses these new technologies include questions around how long the company has been around? What's their privacy policy and how and where is data stored?”

He said clients should understand the principles that apply to the use of technology used by a business.

“However, with AI, there are probably more unknowns, because there’s a lot more that you don’t see,” he said.