3 Best Practices for Retailers Retaining E-Commerce Fraud

Businesses generate huge revenues from selling their commodities online. However, their annual revenues are affected by the fraudster. These criminals design sophisticated ways that can’t be detected easily.E-Commerce Fraud. Their goal is to steal from retailers through charge-back fraud or obtain their customers’ personal data.

They have improved tactics that help them enjoy better incentives like discounts and promotions. Although retailers have established eCommerce fraud prevention best practices, they have failed to detect criminal activities. These criminals are taking advantage of advanced technology to compromise the retailers’ systems.

Thus, as a retailer, you should invest in digital platform fraud prevention tools and implement fraud detection oriented strategies. These are systems that review data generated from customers’ interaction with your eCommerce platform simultaneously and establish whether the person is a genuine customer.

Continue reading the article for some of the best practices that can help you stop fraud as you increase your revenue.

1. Create Fraud Warning Signs alert

You can cross-reference your customers’ identity that you obtain online with the personal details they provided when they registered the account.

It will help your security team detect any inconsistency in the account that indicates fraudulent activities taking place. Some of the common fraudulent activities that the team can observe are listed below.

Payment Fraud. Criminals use a stolen credit card to pay for their purchases. Such a transaction leads to fraud charge-backs to the retailers.

Therefore, a retailer can mitigate fraud by installing applications that flag suspicious activity. They should focus on the customer’s shipping address, IP address, and the value of the purchased item.

Card Testing Fraud. Impostors may make several purchases of lower amounts on the retailer’s eCommerce platform to test the stolen card and verify details. These transactions may go unnoticed by the retailer as compared to larger purchases.

However, the retailer’s system should detect several transactions that are made from a single card and the number of card rejections. These are an indication of card testing fraud.

A retailer can prevent this by enforcing AVS and CW checks and flagging all orders that have AVS and CW mismatch.

Further, the system should highlight all purchases that don’t match the customer’s purchasing habits and typical geolocation.

Promo Abuse. Fraudsters may abuse retail promotions by creating several accounts with a view of getting more discounts. To stop these activities, the eCommerce retailer can the number of accounts a single customer can have.

The security team should also monitor activities of all new accounts to ascertain they are genuine and demand account verification before claiming a gift or discount.

Charge-Back. A customer may complete the purchase online but reject that transaction after some time.

However, a retailer can ascertain the validity of the order by considering the history of customer’s orders, the company’s refund policy, in addition to the shipping information provided when completing the transaction.

Thus, a charge-back can be prevented by flagging repeat purchase disputes that are closely linked to a given account or shipping address. 

2. Build All-inclusive Customer Profiles

Customers create an audit trail when they access their accounts on your website. Therefore, the eCommerce platform is able to access their personal information and compare it with the digital details being originating from their device.

They provide data such as name, username, password, address, and phone number, when they create an account and the details are the standard forms of authentication.

Digital identity is made up of IP address, type of device, and geolocation. You can create an all-inclusive profile by implementing device intelligence that reviews customers’ personal and online data automatically.

The system should be able to pair the two identities to create an all-inclusive customer profile that flags fraudulent activities, especially when the two identities don’t match.

 

Read More: 7 Apps that Can Help Improve Cybersecurity in Your Business

3. Implement Fraud Prevention and Detection Technologies

The retailer should incorporate fraud prevention measures into a strategy. These tools have the capacity to learn and discover unusual customer behaviour with a view of stopping them before they progress to fraud. There are several recommendations that the retailer can use.

Information from Third Party. You can rely on information generated from third parties like IP address, and email information to ascertain whether the person making purchases is your customers or a criminal. This is useful when your internal systems can’t adequately identify fraudulent activities.

Rules Engine. The security team can create rules that restrict higher than normal orders from a single IP address or request to ship goods to a different location than the usual destination that the customer use.

Device Intelligence. This technology reviews customers’ data like their connections, type of device they are using to log in and time they visit the website.

Machine Learning. These algorithms can help you avoid manual reviews when implementing information security systems.

As a result of advancements in technology, machine learning is now the main decision-making organ. The rules engine can only process limited data, yet larger eCommerce retailers serve many customers spread across the world.

Therefore, machine learning is able to survey a considerable amount of data simultaneously.

Behavioral Data. You can use behavioural analytics to study when customers visit your website, the time they spend on the page, and what interests them the most. The data is useful when formulating a security policy to distinguish criminals from legitimate customers. 

Summary

A retailer can stop eCommerce fraud by monitoring customer’s behaviour when they visit the website. The analysis is in real-time, thus, they can detect impostors before they commit fraud. Failure to establish fraud prevention measures can contribute to a loss of significant amounts of revenue through cyber-attacks.

Therefore, the security team should use information such as customers’ data to identify inconsistencies in their accounts. You should monitor closely new accounts that are created during promotions and the number of card authorization declines for these are signs of fraudulent activities.

The mismatch of identities shows a different person is accessing the customer account. You can implement fraud prevention technologies like machine learning, and device intelligence to detect fraudulent activities. Therefore, it is possible to prevent eCommerce frauds like charge-back by identifying and mitigating them through all-inclusive customer profiles. 

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