The Growing Threat of Online Fraud and How to Stay Ahead with AI-Driven Detection

Online fraud is an important problem for modern businesses. All businesses that have operations on the Internet have a certain level of risk. While new methods emerge, so do ways to prevent them. 

Anti-viruses and fraud protection have been around for decades, but they’ve been further enhanced with the rise of artificial intelligence. With more than 800,000 complaints in 2023, it’s obvious why paying attention to detection and prevention is important.

This article explores some of the notable online fraud types, as well as the importance of AI-driven tools for preventing them. 

How AI and machine learning enhance fraud detection

AI and machine learning can significantly enhance fraud detection, as such software learns as it operates. AI tools are able to adapt to new types of fraudulent activities if fed enough information on transactions and scam accounts.

When a new user creates an account, there’s a likelihood that they’re involved in criminal activities or money laundering. Checking their credentials manually against PEP lists can be resource-intensive. On the other hand, sanctions screening software can automate this process and make it more efficient. 

Such software can help you be compliant with relevant data and anti-money laundering regulations. AI helps with behavior analysis as it monitors user behavior and detects anomalies in real time. 

For example, suspicious activity could be making large, sudden transactions or logging in from multiple locations across the globe. Of course, AI isn’t infallible, so once an activity is flagged as suspicious, the human team can take over.

This is a significant advantage compared to traditional fraud prevention systems, as the process is quicker and more accurate. AI-powered NLP tools can help customers and employees as well. They can identify phishing emails, scam messages, and fraudulent communications by analyzing language patterns and intent. 

For example, Google has already automated that emails with the phrase “Nigerian prince” are sent to spam because of the scam that happened commonly a few years back. 

Benefits of AI-driven fraud prevention systems

One of the key benefits of AI-driven fraud prevention is that it provides real-time protection. Modern businesses implement financial fraud prevention software that combines machine learning algorithms with behavioral analytics to stop threats at multiple touchpoints. This prevents fraudulent activities before they even occur. Because the AI constantly learns and adapts, the chances of false positives are reduced.

This is a significant upgrade compared to the traditional systems. Since AI tools can work without requiring humans to interfere too much, they’re saving time and resources for the experts who are working for the company, allowing them to focus more on deep work. 

The automation also means that your operations will be more scalable. Proper AI tools can help you prevent fraud regardless of whether you have 100 or 10000 transactions daily. Besides the simple recognition of fraudulent activities, AI can trigger automatic actions, such as blocking a transaction or requiring additional verification, without manual oversight. In this context, integrating adverse media screening software can further strengthen your system by identifying potential risks linked to suspicious entities.

The reduction of false positives and the automation of certain processes, like authentication, makes the customer’s experience more positive as well. Furthermore, the use of the latest AI-driven prevention systems can help you get a competitive edge. 

Common types of online fraud

While there are dozens of different fraud types, we’ve decided to cover the ones that are most notable and common. Each of them can be countered with the proper prevention method and protocol. A strong data security posture management strategy is also important to detect and reduce risks before fraud occurs.

Phishing attacks

If you’ve been using banking applications or fintech services, you’ve likely seen notices about phishing attacks. These notices will mention how legitimate businesses won’t ever ask for your credentials, nor would they ask you for financial information.

Phishing includes contacting a victim, which can be an employee or a customer, with the intention of leading them toward a fake website. Once the victim tries to log in to a fake website, their credentials or payment information will be stolen. This highlights the importance of employee training in identifying and avoiding phishing threats before any damage is done.

This type of attack can be conducted through emails, SMS, or posts on social media. There are a few red flags that can help you recognize phishing attacks. If you receive an email, you should check its authenticity and domain. 

Furthermore, the email will likely have poor visual design. The same can be applied to the website that you visit if you’re brave enough to click the link. 

The website will be poorly designed, and an important difference compared to the real website is that it won’t have an activated SSL. This protocol encrypts traffic between the user and the website, and it can be checked on the left of the URL bar. 

Identity theft

While pretty self-explanatory, identity theft involves the hacker impersonating someone else. They can use their accounts and personal information to create accounts on other platforms or for personal gains. 

Businesses should protect their employees and customers from identity theft by implementing technical measures like multi-factor authentication. Furthermore, advanced know-your-customer verification can prevent hackers from creating accounts with stolen credentials.

For example, a fraudster uses a leaked database of users to create accounts on other websites. While they might use an email and password, it’s unlikely that they’ll be able to pass the biometric and ID verification. 

Payment fraud (credit card fraud, chargeback fraud)

This type of forgery is quite problematic, and it can lead to lost funds for both customers and the business. Credit card fraud is when a fraudster steals someone’s financial information, such as a credit card, and uses it to make unauthorized payments. 

They can be the ones that directly stole someone’s credit card, or they might have purchased the data from the dark web. Regardless of the source, this can be prevented with multi-factor authentication during the payment process. If credit card forgery succeeds, the victim might blame your business for allowing the payment, which can lead to legal repercussions. 

Another common form of payment scams is called chargeback. This type happens once a scam customer orders an item but later disputes the transaction. Chargeback fraud can be used for money laundering or financial gain through refunding items that have already arrived without returning them. 

Synthetic identity 

This is one of the great examples of AI helping with scams instead of preventing them. Synthetic identity fraud means that a fraudster uses an identity that doesn’t exist in order to create accounts or for financial gain.

AI can help in this process by generating photographs of the identity and documents or helping with creating their personal information. Sometimes, real data on individuals can be used to make the synthetic identity appear more real. 

Fraudsters use these synthetic identities to apply for credit, open bank accounts, or conduct other fraudulent activities. Since synthetic identities do not belong to real individuals, detecting and preventing this type of fraud is particularly challenging. 

Traditional fraud detection methods

Even in the early days of the internet, fraud existed, and the need for prevention strategies was present. Traditional detection includes tools that use predefined rules to flag suspicious transactions. Today, businesses rely on advanced fraud detection software to identify and prevent fraudulent activities in real time.”

A good example would be preventing a transaction from a location that doesn’t correlate with the user’s home address. While this can prevent some fraudulent transactions, it can also lead to false positives. 

Hackers can adapt to these rules. On the other hand, a legitimate user who might be traveling can have their account blocked. Some of the downsides of this system can be made up for through manual reviewing. 

Some organizations rely on their teams to manually review individuals who create accounts and make transactions. This process can be quite detailed and successful in preventing wrongdoers from making accounts or making fraudulent transactions.

However, the process itself is quite tedious as individuals will have to review hundreds of actions daily. This process will become impossible as the business scales. Furthermore, humans are prone to error, which can compromise the process. 

AI-driven detection is the future of fraud prevention

Wrongdoers will always find new ways of committing fraud. Thankfully, ways to recognize and control these processes will follow along. AI has significantly improved the cybersecurity landscape by streamlining detection, screening, and prevention processes.

Methods of prevention, traditional and innovative, are quite important for online businesses. While no single method can prevent all possible threats, implementing defenses against the problems you’re most exposed to is essential.

Hopefully, this article has helped you understand why AI-driven detection is important, and how to deter fraud types like phishing, identity theft, payment fraud, and others.