The benefits of machine learning (ML) are well known – hence why it is becoming so popular. But can it also help businesses in ad fraud prevention?
Nowadays, a lot of companies rely on machine learning to save money. For example, Netflix has saved nearly $1 billion because of its machine learning algorithm, which helps personalize content recommendations to its users. Interestingly, AI can also prevent 86 percent of security threats and cyber-attacks.
As such, it’s clear that ML and artificial intelligence (AI) can solve many of the world’s complex issues – and that includes ad fraud prevention.
Types of ad fraud
Criminals have found numerous methods and techniques to rob companies’ marketing budgets. Here are some of the commons types of ad fraud:
- Click spamming
- SDK Spoofing
- Ad stacking
- Click injection
- Domain spoofing
- Bots and emulators
- Device farms
- Pixel stuffing
Since it is manifest in so many different ways, detecting fraud is extremely difficult. Consequently, only applications that use machine learning or artificial intelligence have the capability for ad fraud prevention.
What is artificial intelligence
“Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.” – Larry Page
Artificial intelligence is how machines such as digital computer systems or computer-controlled robots simulate human intelligence processes. ‘AI’ refers to any project that focuses on developing systems with human intellectual processes attributes. These systems are able to learn from past data, reason, discover meaning and generalize various concepts, thus having the power to solve some of the most complex problems known to humanity.
What is machine learning
“Machine intelligence is the last invention humanity will ever need to make.”
– Nick Bostrom
Rightly said by Nick Bostrom, machine learning is solving some of the most complex problems in the world. At the same time, in the US, machine learning (ML) is also responsible for many jobs becoming extinct. In a nutshell, it is helping humanity by doing tasks we are used to doing more efficiently.
ML is a sub-discipline of computer science or artificial intelligence (AI). Today, many industries now successfully and safely rely on machine learning to reduce human intervention and increase efficiency.
Using this form of AI, software applications can become remarkably precise at predicting outcomes. All it takes is the right information. Machine learning requires historical data as input, and it processes this information to generate accurate outcomes or output values.
ML not only helps companies learn about current trends in the market but is also quite successful at recognizing data patterns. Given this, it can, unsurprisingly, also be instrumental in ad fraud prevention.
Having established what ML is, the following will show you how machine learning can help detect and prevent ad fraud.
1. Proactive and accurate
In 2022, the total cost of ad fraud was a whopping $81 billion, a figure that is expected to increase to $100 billion by the end of this year. Ad fraud is growing, and the only way to detect and prevent it is through machine learning.
Since ML uses complex algorithms to study past data, it is very good at analyzing and assessing vast amounts of information. Not only does ML study data from the past, but it uses it to recognize patterns and identify the trends that fraudsters are following to trick advertisers and ad networks. Since it requires rapid processing, this task is quite difficult for humans to perform in a short period, making this type of AI ideal for the job.
When they invest in machine learning, companies can also cut spending on human resources. The best part about ML is its ability to learn new trends. And since it is extremely adaptable, it can significantly help prevent ad fraud prevention. Moreover, machine learning is not only good at identifying and preventing ad fraud efficiently and accurately, but it’s also fast and scalable.
Today, companies are using ML to detect fraud in the digital advertising industry. Having undertaken periods in which machine learning has been employed to assess and analyze data, its algorithms have become extremely precise in detecting ad fraud, thus saving companies a lot of money.
2. Identifies fraud quickly
Tasks that humans do require a lot of time and effort, but machine learning is different. Applications that run on machine learning autonomously can detect and identify all kinds of fraud faster.
What might take days for humans to analyze ML can complete in seconds. Some machine learning systems are also able to provide real-time results, saving time and effort. Machines that require human intervention cannot work independently. Instead, they need humans to provide instructions before they can fetch the desired results. In contrast, ML applications can identify new fraud methods before they become widespread.
While these applications can process vast amounts of data faster, they are also not biased – unlike humans. What’s more, they are also able to self-train themselves so that they are able to detect new fraud patterns using the existing data.
3. Is cost-effective
Hiring humans to detect and prevent fraud is not only time-consuming but expensive. On top of this, their analysis might not be accurate. In comparison, machine learning is not only efficient but is also precise in detecting and preventing fraud.
Since ML can process large quantities of data in milliseconds, it can check data in real-time too.
Through this, marketers have total control over their campaigns and are better poised to make important decisions. Investing in ML is always the right thing for businesses to do, as it gives them the power they need to detect and prevent ad fraud.
4. Conducts a contextual analysis of data
Machine learning is contextual as it mainly bases its decisions on the characteristics and circumstances of transactions. Conversely, rules-based anti-fraud solutions are usually static and generalize normal behavior to get to conclusions.
Machine learning, on the other hand, is sympathetic, as it checks the conditions or parameters of every transaction before giving an outcome. This allows machine learning applications to catch fraud patterns easily – and therefore more instances of fraud – easily. In comparison, rules-based programs are not as flexible when identifying changes that occur in traffic behavior and are, therefore, not as efficient.
5. Continuously evolving
Machine learning applications evolve over time and, as they process more data, are able to identify fraud patterns and behavior precisely. Like for like, humans are just not as consistent.
In consequence, adopting ML is the only real way to effectively detect and prevent ad fraud today. Unlike their human counterparts, machine learning can adapt to changes and identify new ad models and patterns.
Ad fraud costs companies billions of dollars. Machine learning (ML) is a branch of artificial intelligence (AI) that enables computer systems to think and process information like humans. And right now, it is helping industries solve some of the most complex problems conceivable.
But does machine learning help in ad fraud prevention? This article will answer this question and explain how ML can help detect and prevent ad fraud, saving companies time and money.