Category Archives: Online Fraud Prevention

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.

What is the riskScore?

The riskScore is the starting point for fraud detection best practices. It indicates the likelihood that a given transaction is fraudulent, and so should be calculated for each e-commerce transaction.

The riskScore is generated by submitting information about the transaction for analysis. Possible inputs include IP address, shipping address, email MD5 hash, and the IIN (Issuer Identification Number, also commonly referred to as BIN); it’s best to provide as many inputs as possible. The minFraud service then checks these inputs against a vast history of transaction data and returns the riskScore.

How do I use the riskScore, once I have it?

The beauty of a risk score is that it enables you to use your manual review resources wisely. You can automatically accept orders which receive a low riskScore, automatically reject orders which receive a high riskScore, and manually review all other transactions.

What’s the magic number at which I should do manual review?

It’s important to choose an appropriate risk score threshold. If it is too low, you will reject orders which would have otherwise contributed to your revenue; if it is too high, you run the risk of incurring chargebacks unnecessarily.

We recommend upfront research so that you find the risk score that matches the specifics of your business. Take a look at your historical data on chargebacks; what was the riskScore associated with these transactions? Keep track of decisions made during manual review and the riskScore associated with each. Use historical data to identify trends and adjust your riskScore threshold accordingly. And of course factor in your personal tolerance for risk.

So how does a riskScore save me time and money?

Use the riskScore to automate processing of low and high risk transactions. Save your manual review resources for transactions that need closer scrutiny. Save money, reduce chargebacks, all while you maximize conversions.

MaxMind Speaking at MRC. March 24, 2015 – Mark Your Calendar!

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MaxMind, the industry-leading provider of IP intelligence and online fraud detection tools, has been invited to present at the 2015 Merchant Risk Council (MRC) eCommerce Payments & Risk Conference in Las Vegas. Our co-presenters will include two of the world’s most prominent eCommerce companies: Orbitz, a leader in the online travel industry, and Western Union, a global money transfer giant. MRC’s own Global Director of Programs and Marketing will bring his extensive industry experience to the presentation as well. Whitepages Pro, one of the major providers of contact information in North America, will moderate our lively presentation.

cropped-cropped-maxmind_logo.png   Western Union  Orbitz  White Pages Pro

Manual Review Best Practices
Learnings from Peak Buying Times in 2014

We invite you to attend this panel discussion to learn more about best practices for preparing for, executing and evaluating your manual review processes. You’ll benefit by hearing specific examples of unique situations and fraud trends that caused online merchants to alter their tools or procedures. You’ll also have the chance to review some questionable transactions and engage in discussion about whether to approve or reject them.

Mark Your Calendar!
March 24, 2015
1:30 p.m. – 2:15 p.m. PT
Aria Resort, Las Vegas

We hope to see you at the Presentation or just stop by booth #422 and say, “Hello!”

Contact us today at to schedule a meeting during the event. We look forward to seeing you at MRC’s 2015 eCommerce Payments & Risk Conference – the largest professional development and networking event for eCommerce payments and fraud professionals in the Americas.

What Happens in Vegas … can stop online fraud!

Jenn Sessler, MaxMind’s Director, Business Development, answers questions at MRC 2014.

Proxy detection – why fraudsters give proxies a bad name

When it comes to fraud detection, finding proxies is a big topic. But why? Fraud detection begins with thinking intelligently about the IP address associated with a transaction. Where is that IP address, and how does that location relate to other transaction data? Whereas most IP addresses inspire confidence, those associated with a proxy generate suspicion.

Let’s take a closer look at proxy detection. Continue reading

“AVS” and “CVV” Declines – Maximize Conversion AND Fraud Protection

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Welcome to our first installment of MaxMind’s Best Practices Blog Series!

In this post, we discuss using the minFraud Service in conjunction with your AVS and CVV declined transactions in order to help you increase your conversion rate and stop more fraud.
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MaxMind Speaking at MRC. March 20, 2014 – Mark Your Calendar!

MaxMind, the industry-leading provider of IP intelligence and online fraud detection tools, has been invited to present at the 2014 Merchant Risk Council (MRC) eCommerce Payments & Risk Conference in Las Vegas. We are excited to be joined by a top Risk Analyst from our merchant partner, Shopify, the leading commerce platform that allows anyone to easily sell online, at their retail location, and everywhere in between. Continue reading

Why should I use the minFraud service’s ‘riskScore’ instead of ‘score’?

The ‘riskScore’ is the most actionable piece of data returned by MaxMind’s minFraud service. The ‘riskScore’ simplifies the accept/reject/review decision for online orders, helping merchants to prevent fraud and reduce time spent on manual review. This blog post will explain why minFraud service users should use the ‘riskScore’ instead of the ‘score’ to catch fraud.

Prior to February 2007, before the ‘riskScore’ was introduced, the only risk estimation element the minFraud service returned was the ‘score’ value. The ‘score’ ranges from 0-10 and is calculated by a static risk model formula that uses previously observed risk factors. This return value is deprecated and the risk model behind it is no longer updated. The actual formula used to calculate the ‘score’ can be found here.
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