“Most cases of fraud relate to exaggerating income or selective declaration of existing debt for example, rather than organised crime.
"Building societies’ mortgage teams are well trained in spotting these types of fraud and will deal with them accordingly."
Moreover, mortgage specialists have become adept at spotting red flags, several of which are outlined in the info box, below.
The key starting point, according to advisers, is to "question the plausibility" of every application. If there is anything that looks slightly out of place or makes the adviser pause, this should be investigated.
According to Phillips, one of the biggest dangers is that brokers end up "too close to a case, too embroiled or just too busy to really interrogate the information or the documents being provided. It doesn’t help if a client drip feeds documents or tries to rush the process.”
In those cases, it is advisable to take a step back or pass it to a colleague to have a second, or third, pair of eyes on the application.
Avoiding being rushed and making sure there is time to do things thoroughly is also crucial.
Rise of AI
However, the use of AI to both create and combat fraud is on the rise and may become more pronounced in the next few years.
Digital identity platform Signicat produced a report earlier this year that highlighted the growth of AI-driven fraud. "The Battle Against AI-Driven Identity Fraud" report found that AI-driven fraud now constitutes 42.5 per cent of all detected fraud attempts in the financial and payments sector.
It also found that an estimated 29 per cent of those attempts are considered successful.
While AI-related mortgage fraud had not been put on the radar among advisers FT Adviser has spoken to, they do believe using technology can help identify potentially fraudulent documentation.
For example, as Hollingworth indicates, fraudulent payslips may look authentic but some scrutiny may uncover elements that do not add up, and an AI model could be trained to help spot the oddity.
He says: "A recent starter in a big company but occupying employee number 10 could be one flag, or implausibly round numbers throughout a payslip could help identify areas that require more investigation."
Using technology to help identify these sort of inconsistencies could highlight areas that require further investigation.
However as Morton states, the human is always the best defence in the battle against fraud. She says: "While machine learning or AI can certainly play a part in identifying mortgage fraud, real people are essential to the fraud prevention process.”
According to Phillips: “There is an opportunity to use innovations such as AI to help spot and prevent fraudulent cases, especially as AI becomes even more sophisticated.
