Introduction
Every day, e-commerce fraudsters take advantage of the anonymity provided by the Internet to commit increasingly sophisticated financial crimes that are siphoning billions of dollars away from legitimate businesses and consumers.No matter how much effort you put into your e-commerce business, there’s always the chance that something will go wrong.
Even the most diligent and hardworking entrepreneurs can be victims of fraud—but that doesn’t mean you have to lose money from every instance of fraud committed against your business. Artificial intelligence (AI) can help businesses deal with e-commerce fraud in several ways.
With an effective fraud detection system in place, you can catch these instances before they cost you a dime, whether it be through canceled or fraudulent orders or unauthorized credit card transactions.
In today’s crowded e-commerce landscape, merchants often find themselves being outmatched by fraudulent transactions that harm their bottom line and customer experience. As online shopping becomes more popular every year, so do online scams.
That’s why it’s become increasingly important to use artificial intelligence to minimize e-commerce fraud, the most prevalent form of fraud in all industries today, in order to ensure your business remains secure while increasing sales conversion rates and building trust with customers over time. Here are some of the ways artificial intelligence can help detect e-commerce fraud and keep your company protected.
What is e-commerce Fraud?
E-commerce fraud is any type of fraudulent activity that takes place on an online platform. This can include things like identity theft, false advertising, phishing scams, and more. While there are many different types of e-commerce fraud, they all have one thing in common: they seek to take advantage of unsuspecting victims.
The following guide will help you choose an artificial intelligence solution that meets your needs and helps to minimize the impact of fraud on your business.
Why Cyber Criminals Execute e-commerce Fraud?
There’s a reason why cybercriminals will go through great lengths to execute e-commerce fraud. The chances of getting caught are slim, the potential payout is high, and it’s possible for them to work from anywhere in the world with an internet connection.
It’s no wonder why we need new ways to fight back against these scammers who try every day to steal money from innocent people and businesses alike. That’s where artificial intelligence comes into play.
How Artificial Intelligence (AI) helps to detect and prevent Frauds
Artificial intelligence (AI) has been used to detect a number of these forms of fraud over the years, but only recently has it become a powerful tool for preventing fraud as well.
For example, AI has been used by companies such as eBay and Alibaba to fight against counterfeit products and deter criminal activities like online trafficking. It’s also able to monitor the various activities on an individual’s account or other personal information.
In this article, we examine how AI is impacting fraud detection, look at some examples of AI-enabled solutions, and discuss the benefits AI can provide in this area.
1.Setting the Scene
E-commerce fraud is a big problem. A report published in July 2022 states online payment fraud is going to exceed 343 bn USD for the next 5 years. And that number is only expected to grow. So how can you protect your business? One way is by using artificial intelligence (AI). AI uses machine learning to predict which transactions are likely fraudulent. The three most common methods of AI used for e-commerce fraud detection are:
I. Anomaly detection
II. Rule induction
III. Supervised machine learning.
2.AI vs. Humans
When it comes to fraud detection, artificial intelligence has some advantages over humans. AI can process large amounts of data quickly and accurately, identify patterns that humans might miss, and make decisions without emotion or bias.
That said, there are still some things that AI can’t do as well as humans. For example, AI can’t yet understand the nuances of human language, which can be important in identifying fraudulent behavior. Humans also have a better ability to intuit if something doesn’t seem right. These skills will become more valuable as AI continues to improve its capabilities in fraud detection, so both humans and machines will continue to play an important role.
3.Machine Learning
One of the most popular types of AI to use in this context is machine learning. Machine learning algorithms learn from data, and can identify patterns in e-commerce transactions that indicate potential e-commerce fraud – such as people purchasing large quantities of items from many different stores on one credit card.
The machine learning algorithm analyses transactions, detects anomalies and flags them for human analysis. For example, if a customer buys 20 new laptops every day for the past month using a single credit card, that transaction would likely be flagged for review by a human operator who could then decide whether or not it should be blocked.
When an operator reviews a flagged transaction and decides it’s legitimate, they add information about the incident to the system so it will recognize similar future incidents.
4.Training an AI System
You can train an AI system to detect e-commerce fraud in a few different ways.
-One is to use labeled data, which is data that has been specifically tagged as fraudulent or not.
-Another way is to use unsupervised learning, which is where the AI system looks for patterns on its own.
-Finally, you can also use a combination of both labeled and unlabeled data.
The idea behind this method is that if there are enough examples of how to identify fraudulent transactions in your database, the machine will learn by itself what’s normal and what’s unusual.Once you’ve trained your AI system, it’ll be able to generate predictions with high confidence levels.
AI systems are becoming more powerful by the day, so it may soon be possible for companies to create their own personal AIs (using deep learning) just for one problem domain like detecting e-commerce fraud.
5.Implementing a System
In order to detect e-commerce fraud, you need to have a system in place that can identify it. AI can help by analyzing data and identifying patterns that may be indicative of fraud. By implementing such a system, you can help protect your business from fraudulent activity.
Artificial intelligence will help with this task as well because it will be able to analyze the data in much more detail than humans can, as well as find connections or relationships between certain aspects of the data that humans might not see.
By implementing a strong e-commerce fraud detection system, you can help to make your business more resistant to fraudulent activity. As a result, you’ll see fewer chargebacks and disputes, allowing you to protect your reputation and grow your business.
6.Using Big Data Analytics To Combat Fraud
Organizations are using big data analytics to detect e-commerce fraud in a number of ways. One common method is to look for outliers in behavior.
For example, if someone normally only purchases a few items at a time and suddenly starts buying in bulk, that could be an indication that they are using stolen credit cards.
Another way to detect fraud is through text analytics, which can help identify patterns in customer complaints or product reviews that may be indicative of fraud. The types of phrases used in these texts are different from those typically found on legitimate websites, such as misspellings and poor grammar.
Companies can also use artificial intelligence to help them analyze the purchase habits of their customers. When the company notices a significant change in the individual’s normal purchasing pattern, it could trigger an investigation into potential fraud.
7.What’s Next For e-Commerce?
The global e-commerce fraud rate is currently estimated to be around 1.47%. This number is expected to rise as e-commerce continues to grow. So, what can be done to combat this problem? AI provides a promising solution.
As we’ve mentioned before, AI relies on machine learning and uses data that has been collected to learn patterns and detect anomalies in the future (i.e., after the data has been collected).
To do this effectively, it needs large datasets of both fraudulent and non-fraudulent transactions so that it can learn which factors are present in the fraudulent transactions.
Conclusion
In conclusion, AI can be a powerful tool in the fight against e-commerce fraud. By automating the detection process, AI can help save businesses time and money, while also reducing the chances of false positives. Additionally, AI can help identify patterns in data that may be indicative of fraud, and can even be used to prevent e-commerce fraud before it happens.
Image Credits: https://pixabay.com/
