Fraud Prevention with ML in eCommerce – How to Protect Your Business with Innovative Fraud Detection Tools
E-commerce has kept active shoppers from going crazy during quarantine, and at the same time motivated hackers and fraudsters to come out of the shadows and start stealing shamelessly. Apparently, the old ways of protecting online businesses from illegal attacks no longer work.
That is, eCommerce merchants must look for new ways to protect their data and finances from fraudsters. Could AI and ML-based eCommerce fraud prevention tools be a lifeline in this case? Let’s find out how they work and what opportunities they can offer to modern online business.
How Is AI Used in eCommerce?
Artificial intelligence and machine learning are becoming universal technologies. Their skillful use can add value to virtually all types of business, and e-commerce is no exception. There are a lot of ways to utilize AI and ML for this industry. Here are just a few applications of these technologies in e-commerce.
Demand Prediction And Price Optimization
The capabilities of artificial intelligence go far beyond human ones. With the ability to analyze a huge stream of historical and current data, AI algorithms can predict fluctuations in demand for a particular product, as well as suggest optimal pricing strategies.
A recommendation engine is not only a way to personalize content according to user behavior and needs. It’s also a great way to boost your sales. For example, 35% of Amazon’s revenue was generated by the AI-based recommendation engine.
The recommendation engine is only one of the things that contributed to the personalized user experience. With an AI-powered content management tools (for example, Optin Monster) it is possible to perosnalize and customize content on the web pages of the stores according to the user’s interests and preferences.
What is more, the capabilities of AI and ML are not limited to entertaining users with personalized content and suitable offers. They are powerful technologies to analyze huge data streams in real-time and detect anomalies that can potentially be fraudulent attempts. Digital space has opened up a lot of opportunities for fraudsters, hackers, and other criminals whose activities are potentially harmful to businesses and private users. That is why this issue deserves to be discussed in more detail.
What Is Fraud in E-Commerce?
According to the research by EKN, E-commerce, online, web-connected device (i.e. Internet of Things) related fraud is defined as any type of false or illegal transaction, payment or identity-related fraud or personal data theft completed by a cyber-criminal leading to losses in terms of consumer confidence, margin, brand equity, sales, chargebacks or losses incurred by merchants/retailers, suppliers or the financial institution.
Since the field of e-commerce is wide enough and includes all types of businesses that involve online transactions, scammers have enough targets to aim and hit. The infographic below depicts industries that have been particularly vulnerable to eCommerce fraud.
Also, below we have collected statistics that prove that eCommerce credit card fraud is one of the key problems for merchants, plus many of them ignore eCommerce fraud solutions, thereby exposing their business and customers to real risks.
What Are the Three Types of Fraud in E-Commerce?
eCommerce credit card fraud is just one type of fraud that has been successfully carried out online. Credit card fraud is by far the most common type of online fraud, but there are other ways as well. Here are the main ones.
Identity theft is a way to gain access to all financial data and calmly perform any transactions under the guise of a legitimate card or account holder. What is more, millennials who happily share all their data on social networks, thereby helping scammers paint their true online portraits, are the most frequent victims of this type of scam.
This is a very old trick that still works today. Its essence is to lure the user into a fraudulent analog of a well-known site and force him to enter financial information. Further, this information is used in any way at the discretion of the scammers – they either blackmail the victim or simply empty the bank card.
This type of fraud involves theft or interception of access to financial accounts. In simple words, this is a fraudster’s invasion of a bank or eCommerce account to steal or spend money.
Modern E-Commerce Fraud Prevention Capabilities
So, here are eCommerce fraud prevention best practices which are quite reliable but still need some innovative approaches to make them even more secure.
- PCI-DSS means the security protocol that all online merchants must follow to ensure the security of financial transactions on their websites.
- AVS stands for Adress Verification System. This is a standard eCommerce fraud prevention system that is used for a card-not-present transaction.
- CVV is a familiar three-digit code on the back of the card, which is not written anywhere else except on the plastic card itself.
- Geolocation by IP address. This prevention measure is needed to make sure that the online order and the payment are made from the one location.
- Anonymous proxy servers are the trick that is often used by fraudsters. To date, only AI and ML-powered eCommerce fraud solutions can identify whether a ceratin customer is using a proxy.
- Security services. These are additional apps improving online security, for example, McAfee Secure.
- 3D secure. This is an additional security layer when a customer should finalize the deal by entering the password known only to him and the bank.
How to Prevent E-Commerce Fraud With Modern Tools?
- Enabling secure login credentials for customers. For example, this approach is already used by Payoneer. The company offers to generate a strong and random password to protect an account and avoid password guessing.
- Use of 3D secure protocol. As we have said, this approach allows the user to once more time to confirm the intention to make a purchase.
- Combine machine learning with human intervention. Surely, the AI and ML systems should work under human control. What is more, using their analytical features, business owners may get a lot of unexpected insights into their future strategies.
- Use New fraud detection tools. The most innovative technologies use biometrical data to confirm the identity, intention, or payment.
How Does Fraud Detection Software Work?
It is both simple and difficult to explain how these smart systems work. In a nutshell, every piece of software works because of specifically trained machine learning model inside. Machine learning models can operate according to three main algorithms.
- Clustering involves organizing data into specific subgroups. For example, this approach is used for credit card fraud detection. Credit card transactions are classified in different groups according to the level of the risk.
- Anomaly detection. This is a fairly simple algorithm when the system is able to draw logical conclusions according to the specified parameters. For example, to make a conclusion about the legitimacy or illegality of a financial transaction taking into account geolocation by IP address.
- Random forests. This is the machine learning algorithm according to which a system should make a decision after analyzing several true or false parameters.
How Much Does It Cost to Implement an ML Fraud Detection Solution?
The cost of creating e-commerce fraud solutions for your business and introducing them into your processes will always be individual. The price will depend on the complexity of the solution itself, the required functionality, the features of the machine learning model, and the amount of data that is needed to teach the model to recognize fraudulent attempts and separate them from legitimate actions.
What is more, at the time of deciding to implement an anti-fraudulent AI application, you must have enough behavioral insights so that the system can study the behavior of your customers and learn to distinguish their patterns from fraudulent attempts.
If earlier eCommerce fraud prevention tools were so expensive that only world market leaders could afford them, now the situation is starting to change. The technology has already been tested and researched, which means that its price begins to gradually decline. Right now, AI and machine learning anti-scam systems are available to midsize businesses, so don’t miss out on this opportunity to protect your data, finances, and reputation!