While e-commerce has created new opportunities for merchants, it also comes with new complexities and setbacks — such as chargebacks.
A chargeback is the reversal of a credit or debit card transaction, usually due to unauthorised charges, billing errors, or a fraudulent transaction. While chargebacks are meant to protect customers, they also present additional costs to merchants — and may significantly drain business resources over time.
In fact, a 2025 Mastercard report shows that the global cost of chargebacks is forecasted to rise to USD 42 billion by 2028. In Asia Pacific, chargeback volume is expected to rise 35% alongside associated costs projected to reach $6 billion by 2028.
Even more concerning: nearly 45% of chargebacks are flagged by merchants as fraudulent or misuse.
For merchants dealing with mounting disputes, shrinking margins, and tighter scrutiny from acquiring banks, artificial intelligence (AI) may offer a solution. AI tools can transform chargebacks from a constant firefight into a proactive revenue-recovery engine.
Let’s explore why and how AI-driven chargeback management is not just nice to have, but is becoming essential — and how Antom is making it a reality for online merchants.
Most chargebacks today aren’t from unauthorised fraud, but from friendly fraud (also called first-party misuse). This is when a customer disputes a legitimate purchase after receiving the product or service.
While catching stolen cards, scams, and malicious bots matters, they don’t stop post-purchase disputes from legitimate customers.
Friendly fraud often strikes after delivery or fulfillment. The only way to recover lost funds is through chargeback representment: gathering documentation, building your case, and presenting it to the issuing bank.
Especially for small and medium enterprises (SMEs), this process is time-consuming, resource-intensive, and often deprioritised. As a result, almost 50% of SMEs skip chargeback responses entirely. But as card-not-present and digital goods sales surge globally, the risk grows not just from fraud but from system misuse.
Traditional chargeback handling is tedious. You have to manually gather documents like proof of delivery, order records, payment logs, and emails. You need to format representment packages, and then wait with no guarantees.
AI changes the game, shifting chargeback management from reactive troubleshooting into proactive strategy.
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Here’s how that could play out in real life using a tool like Antom’s Copilot 2.0, which comes with an industry-first Chargeback AI Assistant:
Consider a mid-sized digital-goods merchant specialising in online courses and digital content — a category especially vulnerable to friendly fraud. In this hypothetical scenario, they notice a surge in chargebacks, many flagged as “item not received” or “product not as described.” Despite delivering the content, the merchant loses both revenue and incurred chargeback fees.
Instead of manually gathering documentation each time, the merchant activates Antom Copilot 2.0 as their Chargeback AI Assistant to do the following:
● Develop a tailored response strategy: The assistant organises and analyses relevant data (shipping confirmations, chat logs, payment authorisations, etc). Then, it recommends a response strategy based on a specific reason code (a capability that’s core to Copilot 2.0’s case-by-case automation).
● Enhance documentation processes: It assembles and formats all necessary documentation, so merchants no longer have to dig through logs, emails, and records to prepare evidence for chargeback representment.
● Build a credible defense: Copilot drafts, organises, and structures each case, while merchants review and verify everything to ensure accuracy and compliance.
● Help you learn from post-case analysis: After every dispute, the Chargeback AI Assistant delivers post-case analysis and insights to help merchants identify patterns (true fraud vs friendly fraud vs merchant error). It also identifies weak spots in checkout or fulfilment, and suggests ways to improve your workflow to prevent future scenarios. |
The Chargeback AI Assistant handles case management end-to-end: it evaluates disputes, recommends tailored responses, organises documentation, and tracks outcomes — all within a single dashboard. Human review keeps submissions credible and compliant. As a result, merchants can respond faster, spend less time and resources on disputing chargebacks, and potentially increase their win rates, particularly for “item not received” disputes.
AI-enhanced chargeback operations deliver tangible business impact:
By automating the evidence-gathering and representment workflow, merchants spend significantly less time on manual dispute administration and excess paperwork, enabling teams to focus on growth. Merchants who participated in the Chargeback AI Assistant pilot program reported 46% less time spent on dispute resolution.
Beyond case wins, AI-powered tools can give merchants insightful feedback: patterns in chargebacks, common dispute triggers, and areas to tighten (e.g., billing descriptors, shipping times, customer communication). Over time, this supports fewer disputes, improved customer satisfaction, and stronger fraud prevention, be it true fraud or friendly fraud.
When chargeback rates get too high (or disputes go unchallenged), it can trigger flags or penalties from your acquiring bank. AI-driven representment makes handling disputes faster, sharper, and more strategic. Winning more cases, reducing errors, and preventing repeat issues keep merchant accounts and revenue protected.
Better-prepared evidence and strategic responses win more cases, and even a small increase in win rates can significantly reduce revenue loss for sellers who often treat disputes as just a “cost of doing business”. In Antom’s Copilot 2.0 pilot program, merchants saw a 3 percentage point increase in win rates, translating directly into recovered revenue. The recovered revenue flows straight back into cash flow, a critical advantage for businesses already dealing with slow settlement times in cross-border markets.
For global e-commerce merchants, chargebacks are no longer a minor nuisance but a major operational risk. With card-not-present transactions and friendly fraud climbing, relying on traditional fraud prevention or ignoring disputes puts revenue at risk. AI-driven chargeback representment offers strategic, evidence-backed business impact, paired with human verification for credibility and compliance.
Antom Copilot 2.0 delivers this end-to-end: analysing cases, recommending tailored responses, preparing documentation, and providing post-case insights. The capabilities are backed by Antom’s regional expertise, SOC 2 Type II security, and coverage of 300+ payment methods across 50+ markets.
Contact us to learn how Antom can protect your revenue and streamline dispute management.