Friendly Fraud Can Either Kill Your Bottom Line or Your Relationship with Customers – Which Do You Choose?

Chargeback rates are on the rise; fraud attempts are expected to grow to 3% of all transactions, with friendly fraud making up 20% of all fraud threats during the 2023 holiday season. Alongside this troubling trend, friendly fraud (also known as first-party fraud) is also increasing, posing a significant challenge for companies. It might seem inevitable for businesses to accept the costs of first-party fraud rather than undermine the trust of legitimate customers, who rightfully expect their legitimate disputes to be taken seriously. However, as first-party fraud continues to surge, the financial burden on most businesses becomes too heavy to bear. So, how can businesses strike a balance between delivering an exceptional customer experience and addressing the escalating issue of illegitimate disputes?

Understanding Friendly Fraud, aka First-Party Fraud

Despite the still-high inflation this past holiday shopping season, consumers were still spending, with Deloitte predicting that shoppers would spend an average of nearly $1,700 on holiday gifts, reflecting a 14 percent increase from the previous year, which means they will also be filing chargebacks (both legitimate and fraudulent) that will hit businesses in the early part of 2024.?

To tackle this issue effectively, it's essential to understand what friendly fraud entails. Friendly fraud occurs when customers dispute legitimate charges, sometimes without malicious intent (for example, consumers can forget that they’ve authorized a transaction, or their payment information might be used by another member of the household without their knowledge). But they can still lead to costly chargebacks, negatively impacting a business's bottom line. This category of fraud also involves deceitful actions on the part of customers who knowingly attempt to commit fraud, also known as opportunistic fraudsters. Regardless of intent, this type of fraud is on the rise, causing growing concern among businesses.

Data from Sift’s 2023 Q4 Digital Trust & Safety Index showed that fewer than half of disputes were due to “true” fraud, with 44% of surveyed consumers saying they contested a purchase because it was fraudulently made by someone else. And among consumers who filed a dispute despite receiving the item and being satisfied with the purchase, 26% did so because they wanted the money back and knew their credit card company would cover the cost if they filed a chargeback.

The costs associated with chargebacks and disputes are becoming a significant burden for merchants of all sizes –– and it is merchants who bear the burden of the costs of chargebacks, not credit card companies. It's clear that businesses need to find innovative ways to address these challenges.

The Role of Automation and Machine Learning in Reigning in Friendly Fraud

One solution lies in automation and machine learning (ML), a subset of artificial intelligence. Advanced technologies are transforming how businesses address friendly fraud. ML can analyze and process vast amounts of data, helping merchants more accurately and quickly distinguish between legitimate claims and first-party fraud attempts, and actually prove that a chargeback was fraudulent –– ML analyzes the risk signals and provides insight to fraud teams, who can then automate decisioning (auto accept, reject, review). These technologies are not only efficient but also effective in resolving disputes on the customer end.

Visa's recently updated Compelling Evidence guidelines serve as a prime example of how ML and automation can aid merchants in submitting the appropriate evidence promptly, thereby increasing the chances of a favorable outcome in dispute cases. These guidelines offer a clear (and expanded) definition of compelling evidence, emphasizing the importance of timely submission and comprehensive documentation. Companies who have AI/ML powered tools in place can more easily and quickly gather the documentation they need to submit to Visa, for example, to win a dispute.?

Detecting Patterns and Other Tactics

Apart from automation, pattern detection is another key tactic businesses can employ to combat friendly fraud. By analyzing transaction patterns, ML can identify suspicious behaviors and flag potential fraudulent activities. Other strategies, such as enhanced verification processes and educating customers about the consequences of friendly fraud, also play a role in preventing friendly fraud.?

Having access to a comprehensive transaction history, for example, is essential. Access to insights like a user’s previous transactions made with the same payment card, IP and shipping addresses, and device IDs can help a company establish the likelihood of friendly fraud for a specific transaction.

Balancing Customer Experience and Friendly Fraud Concerns

For major corporations, absorbing the costs of friendly fraud can be a strategic move to preserve customer sentiment, but not all companies have this luxury.?

Regardless of the size of a business, effective fraud prevention is important for merchants to prevent fraud in general. In fact, 83% of consumers surveyed by Sift said they would likely stop engaging with a brand if they had to dispute a merchant charge due to true fraud.

As businesses brace for the post-holiday surge in friendly fraud this month, finding a balance between customer satisfaction and financial security becomes imperative. Tackling this challenge requires a multifaceted strategy.

Taking back control over chargebacks

In the evolving landscape of e-commerce, addressing friendly fraud is not a choice but a necessity. So what, tactically, can fraud teams do??

Identifying risk signals is the first line of defense. Leveraging advanced technologies like machine learning and automation enables merchants to analyze data, detect patterns, and preemptively address potential friendly fraud issues. Automation in the dispute process, with AI aiding in distinguishing between legitimate claims and fraudulent attempts, in a game-changer as well.?

Flexibility in dispute team scaling is equally crucial. Adapting resources to match business demand ensures timely responses during peak periods, preventing backlogs and mitigating the risk of increased chargebacks.?

And finally, it’s vital to maintain strong collaboration between customer service and fraud prevention. Educating customer service teams on fraud prevention measures equips them to provide informed assistance, reducing the likelihood of disputes. This synergy not only strengthens overall customer experience but also minimizes the risk of friendly fraud.

By implementing these strategies, businesses can navigate the complexities of friendly fraud, safeguard their financial health, and maintain robust customer relationships.