In the world of online transactions, fraud prevention has become one of the most crucial aspects of e-commerce. As fraudsters adopt increasingly sophisticated tactics, merchants need equally advanced tools to protect their businesses. Among these tools, User Score stands out as a valuable feature that helps merchants better understand the level of risk associated with individual users. By combining technology, data and machine learning, it provides insights into whether a buyer can be trusted or if they represent a potential threat.
What is User Score?
User Score is a risk measurement ranging from 1 to 100 that reflects how trustworthy or risky a user is.
- Low scores → indicates a genuine and reliable customer with consistent behaviour.
- High scores → suggests possible fraud, suspicious activity or even a compromised account.
This scoring system helps merchants quickly identify the level of risk linked to each buyer. In doing so, it provides a clear guide for deciding whether to approve, review or reject an order.
Differences Between User Score and Fraud Score
Although they sound similar, User Score and Fraud Score serve different purposes in fraud detection:
Fraud Score: Evaluates the elements of an order transaction. It examines details such as billing and shipping addresses, payment method, device fingerprint and IP geolocation. Fraud Score provides a comprehensive assessment of how risky a particular transaction is.
User Score: Concentrates on the individual behind the purchase instead of only the order information. It evaluates the buyer’s identity, behavior patterns, and overall profile built across different transactions.
In other words, Fraud Score looks at the transaction, while User Score looks at the person behind it. Both perspectives are critical for effective fraud prevention.
Importance of User Score
User Score plays an important role in helping merchants understand the broader context of their buyers. While Fraud Score gives a transactional risk evaluation, User Score goes deeper by assessing the user’s trustworthiness over time. Some of the key benefits of using User Score include:
- Identifying impostors or compromised accounts: Even if a transaction seems legitimate, the User Score may highlight suspicious user behavior that indicates account takeover.
- Building user trust profiles: Merchants can distinguish between reliable returning customers and potentially risky buyers.
- Complementing Fraud Score: When used together, both scores provide merchants with a stronger and more comprehensive fraud prevention strategy. Fraud Score remains the main factor for making transaction decisions, while User Score complements it by offering an additional layer of insight into the buyer’s identity and behavioral consistency.
Together, these insights empower businesses to combat fraud more effectively while minimizing false declines for genuine customers.
How User Score is Calculated
User Score is generated through a proprietary algorithm that works hand in hand with advanced machine learning technology. The process begins by assigning a preliminary score derived from a variety of key indicators.
These factors may include whether the individual is a first-time buyer, whether they have a verified phone number attached to their account or whether they are logging in and placing orders from multiple devices. Each of these elements helps paint a clearer picture of the user’s reliability and potential risk level.
Over time, the system refines the score as more behavioural and transactional data becomes available, allowing it to adapt and improve accuracy in detecting suspicious activity.
Where to View the User Score
The User Score is only available for merchants subscribed to the Medium or higher plan. Merchants can view the it by following steps below:
- Log in to your FraudLabs Pro Merchant Area.
- Go to Transactions page and select one of the transaction.
- In the Transaction Details page, go to Order Details and select the user icon beside the email address.
- A modal box which consists of User Transaction Overview will be shown. Under Summary tab, the user score can be found in the User Score section.
This dashboard enables them to monitor user behaviour, review historical activities, and make informed decisions, such as adding a buyer’s email address to the Watchlist. With this level of visibility, merchants gain actionable intelligence about the individual behind the order, rather than relying solely on transaction details. For more information, you can visit What is User Transaction Overview article.
New Validation Rules for User Score
To further strengthen fraud detection capabilities, new validation rules have been introduced:
- User Score Greater Than: Merchants can automatically flag or reject orders when the User Score exceeds a certain threshold. For example, if User Score > X, the system can automatically reject the transaction.
- User Score Less Than: Merchants can automatically approve orders when the User Score is below a certain threshold. For example, if User Score < X, the order may bypass manual review.
These validation rules provide merchants with flexible options to balance fraud prevention and customer experience. Merchants can add these rules by login to the Rules Management page.
Conclusion
User Score is an essential innovation in fraud detection that shifts the focus from purely transactional analysis to user-centric risk assessment. By measuring the risk of the individual behind the order, User Score gives merchants deeper insights into whether a buyer is trustworthy or potentially fraudulent.
When combined with Fraud Score, merchants gain a powerful two-layer defense system, evaluating both the transaction and the user. With machine learning technology, continuous updates and customizable validation rules, User Score equips merchants with the tools they need to fight fraud effectively while safeguarding legitimate customer relationships.
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