Phishing, pharming, scammers, fraud--the cybersecurity scene is full of all kinds of threats, and they don't look to be on the way out anytime soon. That can easily induce anxiety, especially if you're not sure what to do to ensure you see the threats before they're actively hurting you.

This is where fraud detection using AI really shines.

Using AI in your fraud detection and prevention strategies is a sure way to protect your business while discouraging future fraudsters. But how does it work, and how are we so sure it's a good idea? Read on to learn all about it.

A rundown on fraud detection using AI

AI plays a pivotal role in various facets of business operations, showcasing its versatility. From automating routine tasks to enhancing customer service experiences, to emerging applications such as AI tweet generators for social media. AI technologies continue to revolutionize industries worldwide and fraud detection is no different.

Artificial Intelligence (AI) technology is often shrouded in mystery. We're going to get straight to the heart of how fraud detection works when you use AI by considering which components of an AI are useful in identifying fraud.

Machine learning algorithms

A more accurate name for AI-powered technologies would be machine learning-based tools. That's because what we understand as artificial ‘intelligence' is not true intelligence in the human sense.

Rather, machine learning (ML) models make up the basis of the way an AI ‘thinks'. These digital technologies work by scraping a huge data set to recognize patterns and, in the case of fraud detection, flag up patterns that are common to fraudulent activities.

So in other words, ML algorithms let AI tools pick up on instances of fraud based on how similar they are to previously-recorded cases. Also, the ‘learning' part of machine learning comes from the fact that the AI gets better at recognition the more it's used, meaning it gets ‘smarter'.

Deep learning

A more specific kind of machine learning, deep learning relies on digital networks that emulate the way humans think. It's called ‘deep' learning because it's composed of multiple layers of algorithms, and is used to let AI tools make decisions--such as flagging fraud.

In a different type of AI-powered tool, like cloud recruitment software, deep learning might enable AIs to identify and highlight the most suitable candidate for a position based on established keywords.

Tons and tons of data

Any advanced technology that relies on AI has to be fed enormous volumes of data in order to do well--and in order to keep growing, as mentioned. Although the data itself is technically external to the AI, it's impossible to operate the latter without the former, so it bears mentioning.

For example, let's say you want to train an AI to pick out real and desirable applicant tracking system features amid potentially fake or exaggerated features. You'd need data on thousands upon thousands of features to properly train the AI, or it wouldn't be reliable.

Likewise, for fraud detection, you need as much data as you can possibly get to train your AI to properly pick up on instances of fraud. This is a key aspect of how fraud detection with AI works.

Why use AI in fraud detection?

Amid cybersecurity threats like increased ransomware activity, it's no surprise that more companies are looking for effective ways to protect themselves. But what reasons drive them to specifically turn to AI in their fraud detection and prevention?

The following factors set artificial intelligence apart from human intelligence, and explain why using an artificial intelligence model to pick up on fraud is such a good idea.

It's fast

Synthetic intelligence moves at the speed of electricity, which is orders of magnitude faster than a human being can think or move. This means that, by design, an AI can pick up on fraud in a tighter time frame than any human.

In fact, where time is concerned, AI makes it possible to get instantaneous responses whenever fraud is detected. That means you can launch a real-time response.

It's efficient

An AI that's been trained to monitor economic activities gets better and more accurate at spotting suspicious and/or fraudulent activities the longer you use it.

Or, in other words, an AI will always grow in effectiveness over time. This makes it a highly efficient tool to have in the fight against fraud.

It can pick up things humans can't

When it comes to cybersecurity solutions, few tools are as useful as AI-based solutions for exactly this reason. An AI can be trained to notice discrepancies in data, or changes to patterns, that would not be noticeable to the human eye.

This also makes it a lot easier to spot fraud in its very earliest stages when you use an AI-based solution.

What kinds of fraud can AI detect?

There are many different types of fraud abound. We'll give you a quick rundown of the main ones that AI tools can pick up on and guard you against.

Fake account creation

If you're running any kind of website that asks users to set up their own accounts, you run the risk of fraudulent accounts being created, often in large batches. That includes fake bank accounts, fake social media profiles, and much more.

AIs can be trained to separate fake accounts from legitimate user accounts, which lets you stop the fake accounts from going live and being used for illicit activity.

Spam requests or messages

Fraudulent activities aren't always limited to criminal activities. Often, fraudsters send legitimate users spam messages or requests, which can be used to mine personal data or steal money later on.

When you use an AI fraud detection tool, you can train the algorithm to recognize common words and phrases in these fraudulent messages. You can then delete the offending messages or even ban the users sending them.

Data leaks

AIs are also great at protecting you from one of the biggest kinds of insider threat: data leaks.

 Your fraud detection AI can be programmed to scan each user's activity periodically, allowing them to pinpoint if and where a data leak is happening. This is massively useful for both damage control and identifying perpetrators.

Unusual activities

Not all unusual behavior automatically amounts to suspicious activity. For example, if a user suddenly starts making international calls when they never did before, this could look unusual but is not necessarily suspicious.

Where a human might struggle to separate the two, AIs can analyze and evaluate customer behavior in an instant to quickly identify any activity that shouldn't be happening.

In addition to monitoring user activity, another crucial aspect of fraud prevention involves securely disposing of decommissioned hardware. Implementing a robust hardware decommissioning process ensures that sensitive data stored on retired devices is properly erased or destroyed, minimizing the risk of data breaches or unauthorized access.

This step is integral to maintaining the security of your infrastructure and safeguarding against potential fraud.

Common examples of using AI in fraud detection

Any company that needs to convert unstructured data into its structured counterpart can benefit from the use of AI, especially in fraud detection, which relies on tons of data.

We'll focus on some realistic uses of AI-powered fraud detection systems to give you a good idea of where and how you'd deploy these tools as part of your fraud prevention strategy.

Government websites

From the federal government to the smaller and more local government agencies, every branch of a country's ruling force needs to be fully secure online. That means minimizing fraud risks and flagging up potential fraud as quickly and accurately as possible.

It also means that the government can very much benefit from using AI fraud detection tools.

Government officials may, for example, need to validate citizens' identity documents. Problems like synthetic identity fraud can interfere with this workflow unless a well-trained AI can catch these attempts and stop them from ever reaching human workers.

Online banking

Multiple common types of fraudulent behavior center around payment fraud. Whether it's about swindling people out of money or sending fake payments for real goods, financial fraud is very dangerous and unfortunately also quite common.

To combat this behavior, online banking companies can deploy AI-based tools that catch debit and credit card fraud in action.

Aside from credit card fraud detection, AIs in online banking can also help with accurately checking customers' identities so only authorized individuals can access accounts.

Furthermore, AI plays a crucial role in securing the infrastructure that supports online banking services. For instance, financial institutions utilize AI algorithms to monitor and detect suspicious activities within their hosting environments. Whether it's through dedicated servers or cloud services, such as VPS hosting, AI-driven fraud detection ensures the integrity and security of online banking platforms by swiftly identifying and mitigating potential threats.

Identity verification

Hiring new talent is essential if you want to keep your company full of fresh ideas. But if your recruitment portals are flooded with fraudulent activity, it can become dangerous to reach out to anyone or bring new hires on board.

 That's why using AI in your fraud detection plans is so helpful.

With AI incorporated directly into key tools like recruitment CRM software, you can automatically scan and verify all kinds of documents to help check people's identities. This makes it much, much harder for fraudsters to feign ID documents, which means they won't have the chance to waste your time or erode your trust.

Final thoughts

With the help of AI, you can catch a lot of fraudsters before they have the chance to do any harm. This means building stronger trust with your customers, reducing your own risk factor, and taking power away from more malicious actors.

By understanding how fraud detection using AI works, you can start reaping those benefits for yourself. That's why you should include AI in your software modernization strategy.

Bear in mind, however, that AI is not the end-all of fraud prevention. There are plenty of things it does very well--but it can't do everything. AI programs are necessarily non-human, which means they can be tricked in ways humans can't, just as much as the reverse is true.

So, to have the best defenses against fraudsters, be sure to arm yourself with all the tools you need. That means deploying AI tools alongside human experts for optimal results.

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