How Lending fraud can be stopped by AI

By Srikanth
7 Min Read
How Lending fraud can be stopped by AI 1

Business lending fraud is on the increase. Banks, credit unions and digital lenders have reported a 14.5% average year-over-year increase in small and mid-sized business lending fraud in 2022, according to LexisNexis.


Among the main types of business lending fraud are: providing incorrect information, hiding data, impersonating another business and application fraud. These frauds are perpetrated either by individuals or businesses under their own names or criminals who have stolen their identity and are trying to pass themselves off as that company.

As scammers become increasingly more sophisticated in their methods, so fraud becomes harder to detect. Indeed, the victim may know nothing about it until their credit application is rejected because of the fraudulent activity that has been carried out under their name.

The consequences of becoming a victim of business lending fraud can be devastating. Not only can they adversely impact a person or company financially and operationally, but also in terms of the reputational damage caused.

The four main fraud types

One of the most common frauds is impersonating another business. This can be done by stealing or assuming their identity. So realistic have these guises become that lenders often can’t tell that they are fake.

Deliberately hiding data from the lender is a big problem as they can’t make an accurate lending decision. There could be data held back that adversely affects the amount of money they can borrow. It’s also extremely hard to uncover as the lender doesn’t know what information is being withheld.

Supplying the lender with misstated management information and edited bank statements is another tactic favoured by fraudsters. By making their financial situation seem better than it really is, they can falsely obtain a larger loan amount. Only by verifying it against the correct records can the lender, therefore, expose them.

A person or entity may use counterfeit documents or false information in their application with similar intent. To indicate that they turn over more than they do, they may, for example, provide fake account statements. This can only be detected by matching it against the true records.

As lenders have become increasingly stretched due to the sheer volume of loan applications that they have to process every year, so they have also become more exposed to these types of fraud. Added to that is the risk of human error when handling the application.

How AI can help

But there is help at hand. Artificial intelligence (AI) has already made big strides in the fight against fraud in banking and finance, particularly in the areas of money laundering and credit card fraud, and now it’s coming into its own in the lending industry.

AI uses algorithms to quickly and accurately check all the relevant data in the credit application for patterns that may indicate fraudulent or suspicious activity, such as multiple applications for the same loan from the same person or IP address, or if a business has been impersonated. Also, by using historical trends, it can compare different data sets and sense-check if the information used is correct.

The technology can be used at every step of the lending process too. It can identify potential borrowers that are likely to default by examining their credit history and other finances, as well as checking in real-time existing loans for signs of fraud or delinquency.

AI has been successfully applied in the lending decision-making process, enabling users to get a decision on their loan application almost instantly. This is just the next step in the technology’s evolution.

AI’s challenges

But AI also requires humans to double-check its findings to make sure that it’s correct. Then there are the potential problems with AI bias and discrimination shaped by its machine learning programming by humans.

Another issue is that the technology itself is now being widely adopted by criminals as a means of avoiding detection. Just as it can be used to check data, it can also be easily utilised to manipulate it.

This requires lenders to ensure that their AI is as up-to-date and effective as possible to detect and prevent fraud. To achieve this, they need to invest in the technology and partner with the fintech experts who will provide it.

AI’s use in combating fraud is only going to become more widespread in the future. That’s borne out by the fact that more than 50% of financial institutions plan to roll out AI solutions to detect unknown fraud cases.

The primary role of lenders is to provide access to credit for those businesses and individuals that need it. But, at the same time, they also need to make sure that they’re stopping any fraudulent loan activity, which is where AI can make all the difference.

Chirag Shah, founder and CEO of Nucleus Commerical Finance and has over 20 years of experience in the financial services industry and a deep understanding of the needs of UK SMEs.

In 2011, he founded Nucleus, a leading alternative finance provider, to offer flexible and tailored solutions for SMEs across various sectors and stages of growth. With an understanding of the challenges that UK SMEs face in the current economic climate, Chirag launched Pulse in October 2022, a free-to-use service that helps businesses and accountants gain insights into financial performance with AI-powered data visualisation and personalised dashboards. Chirag is not only committed to driving growth and innovation in the UK business ecosystem, but he’s also helping SMEs better understand their data to boost their profitability and guide them towards success.

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