Managing Online Payment Fraud in 2023: Key Measures and Strategies
Following an extensive & informative article from WooCommerce, this guide seeks to provide a comprehensive, engaging discussion on online payment fraud. We will detail how to prevent it, manage it, and explore tools designed to simplify these processes for ecommerce business owners in 2023.
Bottom Line: As an ecommerce business owner or manager, understanding the methods and strategies used by cyber criminals to perpetrate online payment fraud could prevent loss or disaster. This insight will ensure the continued safety of your customer’s transactions and drive customer loyalty.
Empowered by the rise in ecommerce and advances in the digital world, online payment fraud is projected to cause losses exceeding $343 billion globally between 2023 and 2027. Future advancements in technologies like artificial intelligence and machine learning, coupled with the growth of digital currencies, may deepen the scope of fraud strategies perpetrated by cybercriminals.
Defining Payment Fraud
Payment fraud is a fraudulent transaction made without the cardholder’s authorization. This often involves stolen credit card details, a form of identity theft, which brings serious financial/property losses for the merchant, consumer, or both.
The Verdict from Stripe’s Report on Online Fraud
A report from Stripe, The State of Online Fraud, concluded that fraudulent activities spiked since the Covid-19 outbreak. A majority (64%) of business leaders worldwide admitted that fighting fraud, particularly card testing attacks, has become more challenging for their businesses.
Ecommerce Growth: A Significant Fraud Enabler
The surge in online fraud is propelled by the booming growth of ecommerce. In 2021, businesses on Stripe’s platform recorded a 60% increase in payment volume compared to 2020, presenting a broader scope for fraudulent endeavors.
In card testing, a cybercriminal attempts small purchases using stolen credit card details to verify if the card is operational – an action typically taken after a data breach. Prevention of payment fraud of this type involves declining/refunding transactions that present as suspicious/fraudulent.
The Impact of Stolen Card Payment Fraud
Stolen card payment fraud transpires when purchases are made using stolen credit card information. Trustworthy-looking transactions may require manual review as spotting this fraud type can be a challenge. The failure in distinguishing these fraudulent transactions can lead to loss of revenue, an erosion of customer trust, and in worst-case scenarios, businesses may be subjected to significant fines or shutdowns.
The Cost of Disrupting Fraud
From its findings, Stripe discerned that the more a business pushes to prevent fraud, the more they risk blocking legitimate transactions, consequently reducing their payment conversion rates. While merchants bear wallet responsibility for transactions made on their sites and offline outlets, precautionary steps should be taken to ensure validation does not overshadow customer satisfaction.
Fraud Prevention Tools
Merchants can consolidate endangered transactions and alleviate the stress of dealing with payment fraud using tools such as WooPayments. Also, if there are more fraud cases, it’s essential to respond to chargebacks by providing evidence that no fraud occurred.
Five Effective Fraud Prevention Strategies
The following strategies are provided as either in-house services or purchasable third-party tools:
- Setting Fraud Thresholds: These tools prevent or hold high-risk purchases that meet your set criteria.
- Performing Transaction Review: It’s a common practice to delegate a person or team for manual transaction reviews. This checks out flagged transactions for approval or rejection based on set guidelines.
- Rejecting Fraudulent Purchases: To avoid chargebacks, flagged purchases that look like fraud should be rejected or refunded.
- Executing Risk Assessment: Carry out risk assessment to understand what your typical customer looks like, the types of fraud your business is at risk for, and how fraudsters could undermine your current fraud prevention strategies.
- Utilizing Machine Learning: Machine learning models are used for decision making by predicting the possibility of fraud occurrence in each transaction.
Custom Risk Filters
Custom risk filters permit businesses to specify risk tolerance thresholds that signify dubious transactions. They guarantee flexibility for different business types. The parameters include authorized IP addresses from specific servers, blocked IP addresses renowned for fraudulent activities, rapid transactions from the same IP address, transaction amount, and more.