Tag Archives: manual review

Using Custom Inputs to Refine your Response to Fraud

Online fraud is a complex, hard to detect, and constantly evolving type of crime with serious business consequences. While many e-commerce merchants are looking for new ways to engage with customers, fraudsters are also looking for new ways to exploit them. In a way, every touchpoint you create – from buy online/pick up in store options to social click-to-buy ads, mobile shopping to loyalty rewards programs – is another opportunity for cybercriminals to bypass your fraud screening.

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Behind the Scenes: High Risk Shipping Addresses

Just like good customers, fraudsters must provide a shipping address in order to receive merchandise. But fraudsters, who need to evade detection and efficiently resell stolen goods, leave traces in the shipping addresses they use. The minFraud Network collects data on shipping addresses and uses it to identify any high risk shipping addresses associated with the transactions you submit for review.

This blog post investigates some high risk shipping addresses known to MaxMind, as well as provides some general fraud review tips for identifying them.

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How to recognize legitimate proxy use
and reduce false positives during order review

As a merchant, you’ll frequently see cases where multiple orders with different billing addresses and payment methods are placed from the same IP address, and it’s not clear whether or not this indicates fraud.

Such activity could be a sign of fraud, with a fraudster testing multiple compromised credit cards. It could also be a sign that a fraudster is using a proxy to obscure his identity. There are times though when such activity is expected and flagging such transactions as fraudulent would mean denying good orders and frustrating customers. Continue reading

Case Study: Using Historical Transaction Data to Reduce Chargebacks

The new year has arrived. With transaction history from a busy holiday season on hand, this is a great time to take a look your historical transactions with a fresh and critical eye.

Reviewing your chargeback data to identify fraud patterns is a good way to get started. In this month’s blog post, we provide a case study of an online penny auction business, which improved their bottom line by doing just that. Continue reading

How to Use Geolocation to Identify Higher Risk Transactions

In our last blog post, we discussed how you can use a risk score to automate fraud screening, saving you time and money.

In this blog post, we begin our discussion of manual review best practices.

Studies show that, in North America, one in four orders on average receive extra scrutiny through the manual review process. The goal is to prevent the expense of chargebacks and customer issued credits associated with fraud. At the same time, you need to ensure that legitimate orders are not rejected unnecessarily, and estimates suggest that this is the case with up to 10% of orders. Rejecting good orders negatively impacts the bottom line, and drives away good customers.

During manual review, fraud analysts examine data associated with an order to assess how likely it is to be fraudulent. One key area of data points to consider is that of geolocation. Continue reading

How a Risk Score Saves You Time and Money

Welcome to a new installment of MaxMind’s Best Practices Blog Series!

In discussing best practices, our focus is on efficient fraud screening methods which stop fraud while providing a positive customer experience.

Key to efficient fraud screening is automating as many decisions as possible.

In this post, we discuss the crucial role of minFraud’s riskScore to automated decision making. Continue reading