Tag Archives: chargeback prevention

MaxMind’s Paladin Report is now available

Deciding on the right fraud prevention and IP intelligence provider can be a daunting task. With worldwide internet usage projected to grow every year, your choice matters now more than ever. So, make an informed, educated one with MaxMind’s Paladin Report.

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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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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

Manual Review Best Practices:
Get More Data for a More Informed Decision

Thus far, our Best Practices Series has discussed how you can use the data provided by the minFraud service for better decision making during manual review.

But actionable data from minFraud starts with the inputs you include with each query.

The minFraud service requires that each query include the IP address associated with the transaction at a minimum; as best practices, MaxMind recommends you send as many data points as possible.

The more data points you provide, the better the riskScore and the more information you make available to your fraud analysts as part of the manual review process. 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