Author:
Rafael Lourenco is Executive Vice President and Partner at ClearSale, a card-not-present fraud prevention operation that helps retailers increase sales and eliminate chargebacks before they happen. The company's proprietary technology and an in-house staff of seasoned analysts provide an end-to-end outsourced fraud detection solution for online retailers to achieve industry-high approval rates while virtually eliminating false positives. Follow on LinkedIn, Facebook, Twitter @ClearSaleUS, or visit https://www.clear.sale.
This article will:
• provide an overview of fraud on a global scale
• dive into some of the more critical regional trends and characteristics that eCommerce merchants should understand
• tell merchants the best way to manage fraud, no matter what changes the future brings
In the world of eCommerce, fraud is the great unifier. Everybody, from the smallest Etsy crafter to Amazon themselves, struggles with fraud risks. Facing that common enemy, even competing companies will eagerly share horror stories and best practices.
But that doesn't mean their problems manifest in the same way.
A company's fraud threat may vary depending on their region. An online bike shop in San Diego, for example, may face a different fraud landscape than an online bike shop in Rotterdam. Payment systems differ; laws vary; even social attitudes are different.
These factors equate to a need for eCommerce merchants to understand the fraud landscape in their region and any other region in which they hope to conduct business.
The Global E-Commerce Fraud Landscape
If companies have felt like fraud attempts have been intensifying lately, they're not wrong. A recent Nexis Lexis report revealed the average number of successful fraud attempts has increased by 43% - 48% for mid-to-large e-commerce retailers.
What's worse? The cost of fraud has gone up. Every $1 in fraud now costs retailers $3.36, compared with $3.13 in 2019.
Alarmed? Global online payment fraud losses are expected to increase by more than 50% from 2020-2024, costing $25 billion per year.
Regional Highlights
APAC: China typically has a low incidence of credit card fraud. Why? Because credit card companies hold cardholders liable for any fraudulent purchases. So, shoppers choose mobile payments instead.
LATAM: With nearly half of the population unbanked in Latin America, it can be difficult for eCommerce merchants to sell their products online, requiring creative fraud protection tactics.
EU: FICO reports that Hungary, Poland, Romania, Greece and Italy had the highest year-over-year increase in card-not-present fraud from 2018 to 2019.
US: ClearSale internal data indicates that the US states with the highest risk of fraud are Florida, New York and Michigan. Within Florida, most fraud is concentrated around Miami due to increased freight forwarders' presence. In New York, the borough of Brooklyn has the highest fraud rate.
Trends and Developments
Unsurprisingly, the COVID-19 pandemic has had a marked effect on eCommerce sales and eCommerce fraud. In good news, eCommerce has seen rapid growth – ACI Worldwide reports that August 2020 saw a 24% increase in eCommerce transactions than the previous year.
On the contrary, the rate of attempted fraud has increased around 50 percent since the outbreak was declared a Public Health Emergency of International Concern, by WHO, on 30 January 2020.
While a spike in sales is generally a good thing for eCommerce merchants, businesses whose fraud protection may not be agile enough to handle these spikes might find themselves falling victim. In desperation, they may increase their fraud filters' strictness, potentially leading to an increase in false declines.
Regional Highlights
APAC: The massive increase in real-time payment options has made it difficult for banks to have enough time to confidently clear transactions. Four out of five Asia-Pacific banks say real-time payment platforms have increased their fraud losses.
LATAM: Mexico is an up-and-coming eCommerce juggernaut, but beware: in our research, more than half of Mexican consumers said mistakenly declined orders would cause them to abandon a website permanently.
EU: Fraudulent purchases of online or virtual services have increased. One investigation identified more than 1,000 fraudulent railway ticket bookings, with a cost of around €70,000.
US: Americans have more trust in eCommerce than ever before. In our survey, 87% of Americans said shopping online is "just as safe" or "a lot or somewhat more safe" as shopping at brick-and-mortar stores.
Preventing E-Commerce Fraud
A word that sums up the best approach to fraud prevention: flexibility. Fraud patterns change from month-to-month, product-to-product, and market-to-market. As such, it's vital to ensure any fraud prevention system is flexible enough to adapt to regional patterns, seasonal spikes and even pandemics.
Much of this flexibility can be gained by using a hybrid approach to fraud prevention, combining machine learning with manual review.
Here's why:
· Machine learning and AI are powerful tools in the fight against fraud, with their ability to process vast quantities of data and identify fraud patterns. However, they can sometimes struggle with transactions that don't fit into a specific pattern.
· On the other hand, experienced fraud analysts have in-depth knowledge and deductive reasoning that allows them to think around corners and understand the "why" behind unusual transactions. For example, a fraud analyst specializing in the Chinese market will have an in-depth knowledge of the cultural practices and holidays that might affect shopping patterns. A Chinese customer purchasing a dozen gift cards may trigger an automatic decline from an AI. Simultaneously, a manual reviewer would recognize the proximity to Chinese New Year and be familiar with the custom of giving "red envelope" gifts to friends, family members and employees. From there, the manual reviewer can quickly get in touch with the cardholder to ensure all is in order and then approve the payment – saving the merchant from a significant lost sale and an angry customer.
By combining the two approaches, merchants can get the best of all worlds. The automated fraud filters can quickly and efficiently process and approve large volumes of profitable transactions. By choosing a fraud solution that flags – not rejects – suspect transactions, merchants can then have manual reviewers (either in-house or outsourced) examine any transactions that seem dicey, only rejecting them due to strongly indicated fraud. As a bonus, when major new trends occur (such as with the COVID-19 pandemic), and the algorithms don't yet know how to process new patterns, manual reviewers can identify these new patterns and teach them to the AI. This makes future automated reviews more accurate, reducing the risk of fraud in every market – from Tokyo to Toledo.