Battling Chargeback Fraud in Digital Marketplaces With AI

Imagine losing billions in e-commerce revenue because consumers are taught how to game the chargeback system. This is the harsh reality facing digital marketplaces like Uber, Airbnb, Turo, and Etsy as they grapple with an escalating wave of fraudulent chargebacks.

The global online marketplace sector is projected to reach a gross merchandise value (GMV) of $3.832 trillion by the end of 2024, reflecting 10% growth from the previous year.

This rapid expansion brings opportunities and an increase in chargeback claims. As these marketplaces evolve into more complex ecosystems, they must navigate the intricate landscape of chargeback disputes, balancing their roles as connectors between consumers and merchants.

Chargebacks occur when consumers dispute transactions, leading to payment reversals that cause the merchant to lose funds for the goods or services provided. While the chargeback process is intended as a consumer protection mechanism, it is often exploited.

Friendly fraud is a specific type of chargeback fraud in which consumers dispute legitimate charges, claiming they never made the purchase or didn’t receive the goods or services. This type of fraud is particularly challenging for marketplaces because, often, the marketplace is not the entity that provides the goods or services.

Social Media Fuels Friendly Fraud

A troubling and expanding trend amplifies this challenge: the proliferation of social media videos that teach consumers how to dispute credit charges, leading to a significant rise in friendly fraud. These videos fuel a surge in illegitimate chargeback claims, impacting various industries, including digital marketplaces.

To combat this growing threat, marketplaces must go beyond merely responding to claims. AI-powered solutions help marketplaces gather the strongest evidence to recover lost revenue from fraudulent disputes by tailoring each chargeback response at scale and using machine learning to optimize and improve the results over time.

AI can identify patterns that indicate opportunities for improving operational processes. By adopting these solutions, marketplaces can comply with card network regulations, distinguish between legitimate chargebacks and friendly fraud, and create a more secure, efficient, and user-friendly environment.

Marketplaces and First-Party Fraud Risks

First-party misuse, or “friendly fraud,” is a growing concern for digital marketplaces. Unlike traditional merchants who have direct control over their transactions and customer interactions, marketplaces operate as intermediaries, connecting buyers with multiple independent sellers. This unique position makes them particularly vulnerable to first-party misuse.

In a direct merchant-to-customer scenario, the merchant manages all aspects of the transaction, from the initial sale to customer support, with direct access to purchase records, communication logs, and the quality of goods or services provided.

However, this process is more complex for marketplaces. They must rely on data from potentially thousands of sellers, often scattered across various systems and databases, making it challenging to gather the necessary evidence to contest chargebacks effectively.

Marketplaces must also manage the trust and integrity of their entire platform, balancing the interests of both buyers and sellers.

When a buyer engages in first-party misuse — such as falsely claiming that an item was never received or was not as described — the marketplace is left in a difficult position. They risk financial losses from the chargeback itself, and if they pass the chargeback on to sellers, there is potential reputational damage if sellers feel inadequately protected or supported.

Marketplace as Merchant of Record

Chargebacks present heightened risks to marketplaces when they assume the role of “merchant of record.” In this capacity, marketplaces are not only responsible for processing payments and managing customer disputes but also bear the full financial impact of chargebacks.

Additionally, repeated chargebacks can severely damage a marketplace’s reputation, eroding trust with consumers, sellers, and card processing companies. To effectively mitigate these risks, it is crucial for marketplaces to implement AI-driven measures.

A solution that utilizes AI properly can play a critical role in streamlining dispute management and enhancing win rates at scale, ensuring that marketplaces recover more to their bottom line and their reputation stays in good standing in an increasingly competitive environment.

Transparent and fair refund policies are essential, as they reduce customer dissatisfaction and preempt chargeback disputes. Providing excellent customer support, including easy access to resolution channels, ensures that issues are addressed promptly, potentially preventing disputes from escalating to chargebacks.

Simplifying and clarifying end-user flows — such as checkout processes and post-purchase communications — can also significantly decrease the likelihood of chargebacks.

Accurate transaction descriptors, which appear on customers’ credit card statements, are crucial. Using dynamic descriptors that include the merchant’s and the marketplace’s names can reduce customer confusion and decrease the chances of accidental chargebacks due to unrecognized transactions.

AI for Efficient Chargeback Management at Scale

In digital marketplaces, where data is often dispersed across multiple vendor systems, AI is an indispensable tool for consolidating and analyzing this information. AI functions as an intelligent organizer, synthesizing scattered data into a cohesive, actionable framework that streamlines chargeback management and fortifies defenses against payment disputes.

By analyzing data from chargeback claims — especially when categorized by specific reason codes or customer complaints — AI can identify patterns that reveal systemic issues or areas for improvement on the platform. For example, frequent chargebacks tied to a particular service aspect may highlight flaws in the end-user experience or transaction process, which, once corrected, can significantly reduce future chargebacks.

Unlike traditional, static template-based manual or automated systems, AI adapts chargeback mitigation strategies by considering various factors such as market trends, issuer types, and product categories. This level of detail enhances each response while reducing manual efforts.

As AI learns from each chargeback case, refining its approach based on the outcomes, it becomes increasingly effective. The more data AI processes, the better it becomes at distinguishing between winning and losing cases. Over time, this leads to continuous improvement in win and recovery rates, making AI a progressively more powerful tool for mitigating chargebacks.

Building Trust With AI-Driven Chargeback Defense

As digital marketplaces expand, managing trust and transactions becomes increasingly complex. Given their role as intermediaries, AI-driven chargeback solutions are essential. These tools help marketplaces consolidate and analyze vast amounts of data, streamline dispute management, and improve win rates, especially when they serve as the “merchant of record.”

AI’s ability to detect patterns and respond to chargebacks at scale is crucial in protecting marketplaces’ reputations and financial stability.

In a competitive landscape where trust is paramount, leveraging advanced AI solutions allows marketplaces to safeguard their platforms, ensuring they remain secure, efficient, and user-friendly. By doing so, they protect their bottom line and foster lasting trust with consumers and sellers, setting the stage for continued success.