July 24, 2018
Inaugural Manual Reviews Survey Shines Light on Operational and Financial Challenges Merchants Face in Digital Economy
An accepted process is good until it becomes displaced by a shift in the market or new technology or becomes too expensive or archaic. An industry standard that is falling out of favor within the payment industry is the practice of manual reviews. Manual reviews have been a first line of defense for fraud mitigation and a standard by merchants in the payment channel for many years.
Manual reviews are a process that involves passing orders that meet certain high-risk attributes into a holding queue. These orders wait as staff attempt to verify orders through manual verification. In today’s digital economy, manual review departments, without strict guidelines, quickly become non-scalable, time-consuming and costly. And worse yet, if it is done poorly, it can damage a company’s brand, sales conversion or result in increased false positives.
A new survey, “State of CNP Manual Reviews: 2018 Report” from Kount and Paladin Group interviewed over 400 respondents primarily representing eCommerce, omni-channel, and mobile commerce markets to understand the trends and best practices of manual reviews in the card-not-present (CNP) payments environment. Key observations resulting from the survey include:
- Despite outsourcing high-risk orders, 54 percent of surveyed organizations are eventually accepting greater than 70 percent of the orders reviewed.
- 34 percent of merchants require one to three minutes for each manual review — potentially unacceptable for consumers in the digital economy.
- 48 percent of merchant respondents don’t know their average cost to review each order.
Types of Data Sources Used for Manual Reviews
The responding merchants identified the following data sources for mandating a manual review. For 82 percent of merchants surveyed, it was a simple as address matching. This is the process of simply reviewing the consistencies between billing and shipping address in conjunction with issuer-based Address Verification System (AVS) match. It’s a way to quickly gauge the potential requirement for additional manual review. Another source frequently used is email verification, which involves verification that the email address is a valid and active address. According to respondents, geolocation verification is also often relied upon and allows the user to identify the physical location of the device placing the order. Geo-location has the ability to match the billing and or shipping address. The use of automated rules in a fraud platform is also a popular data source by the responding merchants. In addition, 67 percent of respondents are using IP address lookup, which can further indicate the physical region of order placement. Trailing respectively behind these best practices is the use of card issuer and historical chargeback data to increase effectiveness of manual review.
State of CNP Fraud on Manual Review Process
For traditional merchants, there is always an acceptable amount of fraud. This “acceptable” fraud level varied based on the organization and its goods and services sold. Before eCommerce and card-not-present (CNP) transactions, most merchants simply wrote fraud off as a loss on their P&L sheet. However, as digital transactions compound the problem of fraud for many merchants, it is important that organizations understand and evaluate their fraud strategies on a regular basis. For manual reviews, it is recommended that merchants track monthly manual reviews as well as the average manual review time to completion. This allows the merchant insight into the effectiveness of the manual reviews department.
Based on the inaugural survey, Kount doesn’t believe that merchants are ready to eliminate the manual review process from their fraud mitigation arsenal. While 34 percent of respondents indicated that they would consider outright elimination of the process, 46 percent of merchants surveyed mentioned that they would never consider eliminating manual reviews altogether.
The human element is always an important factor when dealing with fraud. Today’s use of artificial intelligence (AI) and machine learning within fraud solutions do a lot of the heavy lifting as it relates to assimilating and analyzing data to capture the fraudsters and speed along the transaction process. However, just as feature engineering and the interjection of domain expertise plays a role in making the algorithms stronger and more accurate in detecting fraud, so does the review of humans to individual transactions.
Today’s digital economy is going to change many aspects of our lives – including how we are approved and denied when we purchase online goods.
To learn more about key findings and benchmarks related to the manual review process, please download the full report “State of CNP Manual Reviews: 2018 Report.”