As the global eCommerce market grows and fraudster methodology evolves, new fraud management approaches and tools are being introduced at a fast pace. Trying to stay on top of developments in the eCommerce fraud prevention landscape can be overwhelming and time consuming. Riskified is proud to present the eCommerce Fraud Solution Buyer’s Kit, a comprehensive series of resources designed to guide executives, decision makers, and procurement professionals through the process of assessing current fraud management performance and understanding which available approaches and solutions can best meet their needs.
- CNP Fraud Lexicon: includes commonly used fraud terms, precise definitions of KPI terms, and explanation of industry jargon.
- Assessing Current Performance: includes an explanation of which metrics and KPIs are important, who in the organization has this data, and how to benchmark your performance
- Choosing a Third Party Solution: includes key considerations for procurement, selecting a good fit your organization and how to assess third party vendors.
- Approaches to Fraud Prevention: includes an overview of the various approaches, pros and cons of every approach, and resources for optimal performance.
Fraud detection is a science, and mastering the subtleties of the field necessitates an intimacy with terms and vocabulary. Whether you’re searching for a third-party fraud solution, evaluating the performance of your in-house team, or just getting acquainted with the ins and outs of CNP fraud, you’re likely encountering industry jargon, which can be difficult to decipher. With this in mind, we’ve created this lexicon as a guide for merchants, to elucidate some of the most commonly used fraud terminology.
- Account Takeover (aka ATO)
- Anomaly Detection (aka Outlier Detection)
- Approval Rate AVS (Address Verification System)
- AVS Match / Partial Match / Mismatch
This term generally refers to the field of data analysis that measures users’ behavior on web or mobile platforms. Riskified uses this term to refer to analysis conducted on data generated directly from merchants’ eCommerce sites and mobile shopping apps using our Storefront Beacon. A twenty minute shopping session can contain thousands of data points, and when these browsing patterns are analysed and cross-checked against millions of other shopping sessions, they become an excellent indicator of the order’s fraud risk.
Short for software robots, this term is used to describe tools designed to carry out repetitive tasks automatically. Tech savvy fraudsters may deploy bots to target eCommerce websites, by creating fake accounts and placing orders using stolencredit card details. Riskified’s systems detect bot activity through order linking and anomaly detection.
CNP (Card Not Present) Fraud
A CNP transaction is one where the merchant is unable to physically examine the credit card, usually when a purchase is conducted via digital channels or over the phone. CNP fraud refers to a CNP transaction conducted without the cardholder’s permission. Typically, CNP fraud is perpetrated by criminal elements using stolen credit card details (often acquired on the dark web). Common forms of CNP fraud include account takeover fraud, package rerouting fraud, and friendly fraud (including so-called liar buyers).
The Dark Web is a subset of the Deep Web (Internet content which is not indexed by search engines) that cannot be accessed without specific software or authorization. Although some Dark Web activity is legal, the anonymity it affords makes it a haven for illicit activity. Stolen credit card details sold on the Dark Web include not only the full card number, but also AVS, CVV, and full billing address.
When a customer files a fraud-related chargeback, claiming unauthorized card usage, despite the fact that they actually purchased the item. This can happen for several reasons. It can be the result of an honest mistake, like a child using a credit card to place an order without the parents’ knowledge, or a shopper not recognizing the transaction on their credit card bill. It may be a circumstantial case of chargeback policy abuse which wasn’t premeditated and is unlikely to repeat itself. For instance, a customer books a hotel room for a trip that is subsequently cancelled. The customer reports unauthorized card usage to avoid paying for a booking that he or she did not benefit from. Finally, friendly fraud can occur as part of a deliberate, malicious plan on the customer’s part (aka Liar Buyer).
The IP (Internet Protocol) address is a number assigned to every device that communicates over a computer network. One function of the IP address is that it indicates the geographic location of the computer network. Riskified’s Storefront Beacon collects IP address data for every online transaction reviewed for fraud directly via the retailer’s eCommerce site or mobile shopping app. The IP address can help reveal the customer’s location and is taken account along with other data points when determining the potential risk of the transaction. Fraudsters often use proxy servers in an attempt to conceal their IP address (and true location).
This term refers to records of physical addresses, phone numbers, IP addresses, emails, or credit cards that merchants have identified as being associated with legitimate customers. Merchants may choose to automatically approve orders containing whitelisted data as a way to reduce review turnaround times. The downside of relying on positive lists is that, if details of a previously “whitelisted” credit card are stolen and used by a fraudster, the merchant will immediately approve the order, without reviewing it for fraud
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