Exploring AI’s Defense Against Business Lending Fraud: Dive into our article to discover how AI technology is combating the growing threat of fraudulent activities in business lending.
Artificial intelligence (AI) has improved the outcomes for hundreds of thousands of businesses by automating and speeding up their processes. Yet, it has also helped the criminals too, making it easier for them to commit fraud and steal money.
Nowhere has this been more keenly felt than in the banking and finance industry, where the technology has been successfully deployed in the fight against fraud, tackling everything from credit card fraud to money laundering. But one of the key areas where it is proving most effective is in detecting business lending fraud.
There’s no doubt that business lending fraud has been on the rise in recent years, increasing at an average of 14.5% year-over-year for small and mid-sized businesses in 2022, as per a LexisNexis report. But that’s just the tip of the iceberg, with many of these types of fraud going undetected or unreported.
The problem was exacerbated during the Covid-19 pandemic as businesses became increasingly stretched, with employees forced to work remotely. As a result, they have become obvious targets for scammers looking to exploit them.
Types of business lending fraud
As technology continues to evolve, so the criminals’ methods have too. There are four key areas where they are now focusing their efforts: application fraud, impersonating another business, providing incorrect information and hiding data.
Application fraud is fast becoming one of the most prevalent forms of deception. It involves a business or individual using their own details to apply for a financial product such as a loan, but when they complete the application they use false information or counterfeit documents, often to try and get a larger amount of money.
Another common tactic among fraudsters is impersonation. By using fake documentation to trick the lender into believing that they are another business, they can dupe them into lending them big sums of money.
Knowingly providing the wrong information is fraud too. This typically includes but is not limited to, the submission of misstated management information and fudged bank statements, which are hard to verify without the correct records.
But perhaps the hardest fraud to uncover of all is hiding data. By withholding key information that can be used to determine a lending decision, scammers can secure a bigger loan.
Given the complexity of these kinds of fraud and the fact that they can be committed by individuals and companies themselves or others who have stolen their identity by posing as them, it makes it even harder to identify and prevent them from happening in the first place. And so deceptive are they that the victim may never know they have been targeted or only find out when they are turned down for a loan after the fraud was perpetrated without them being aware of it.
How AI can help
Traditionally, combating this type of fraud would have required trawling through vast amounts of data manually. But now, thanks to the advent of AI, such checks can be done in a matter of minutes, both accurately and effectively.
Signs and patterns of fraud or suspicious activity can be quickly and easily detected using algorithms. That means it can, for example, pick up on whether the same person is making multiple applications on the same loan.
Drawing on historical trends, the technology can also compare different data sets and determine if any information is incorrect. It can also identify impersonation.
The fraudsters are fighting back
Despite all the positives, there are some drawbacks to using AI. The chief one is that, in the hands of the criminals, it’s being used to perpetrate fraud. As lenders continue to develop their technology, so fraudsters are using increasingly more sophisticated and clever AI tactics to find a way around it.
Then there is the problem of AI bias and discrimination. This can creep in at the machine learning programming stage, if it’s set up incorrectly by humans, thus perpetuating the bias or discrimination in its selections and findings.
These challenges aside, the benefits that AI can provide in tackling business lending fraud are far greater. They just need to make sure that they are staying one step ahead of the fraudsters in terms of the technology they use.
With the market for AI in financial fraud detection expected to grow by 57% between 2022 and 2027, peaking at $10 billion, the technology’s development and uptake are only going to increase exponentially. That’s why lenders need to harness the full power of technology in fighting business lending fraud now and into the future.
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