Chargeback

By fraudulently reversing previously settled transactions, criminals introduce additional transaction steps that obscure the link to the original illicit funds. The disputed refunds, often routed through various channels and accounts, add complexity that hinders tracing efforts, making layering the primary objective.

Criminals exploit falsified, stolen, or synthetic customer identities to initiate disputes that appear legitimate, masking laundering activity. This misuse of the "customer" role—often in collusion with merchants—creates false narratives and disrupts trust-based dispute mechanisms, making identity integrity and customer behavior an important risk vector.

Criminals exploit the built-in chargeback and refund mechanisms of credit card and payment products to reverse transactions, masking illicit proceeds as returned funds. By manipulating legitimate dispute policies and thresholds, they add an extra layer of complexity that conceals the original source of the money. This inherent product vulnerability is central to the laundering scheme.

Geographical risk data outlines known high-risk jurisdictions, AML enforcement levels, and risk ratings, including:

• Country-specific red flags or heightened regulatory scrutiny.
• Contextual information on cross-border transactions.

Identifying chargebacks initiated from high-risk regions helps detect potentially fraudulent disputes and laundering attempts involving jurisdictions with lax oversight.

Transaction logs provide complete records of all credit card and payment transactions, including:

• Timestamps, transaction amounts, merchant details, and customer account identifiers.
• Dispute data capturing who initiated chargebacks, when, and for how much.

These details directly help identify suspicious patterns of recurrent chargebacks, collusion between merchants and customers, or attempts to keep dispute ratios low by managing transaction volumes.

Payment platform data captures usage records from e-wallets and fintech processors, including:

• Multiple payment accounts or methods tied to the same user.
• Transaction timelines and volumes across different platforms.

This data helps pinpoint customers employing diverse payment instruments to execute and later dispute transactions, revealing recurring chargeback abuse patterns.

Fraud data consolidates reported and known fraudulent activities, including:

• Documented patterns of identity theft, payment card fraud, and chargeback-related scams.
• Correlation with known fraudulent profiles or blacklisted entities.

By comparing disputed transactions against known fraud trends, investigators can identify malicious patterns underlying fraudulent chargebacks more quickly.

KYC & CDD records provide verified customer identity information, including:

• Official personal details such as names, addresses, and identification documents.
• Historical changes to customer addresses and contact information.

Access to accurate identity data helps pinpoint inconsistent or fraudulent information supplied during chargeback disputes and detect stolen or synthetic identities used in collusive chargeback schemes.

• Public blockchain records of transaction timestamps, addresses, and amounts enable on-chain analytics.
• Detects whether disputed funds are routed to decentralized exchanges or crypto wallets.
• Helps trace layered or obfuscated flows of chargeback proceeds in digital asset environments.

Registry data reveals the legal owners, shareholders, and directors of companies, including:

• Structures showing ownership or control overlap between merchants and disputing customers.
• Historical changes in beneficial ownership.

This data source helps expose collusion in fraudulent chargebacks where the merchant and the customer share hidden business interests.

Require deeper verification for merchants or customers showing unusual or excessive chargeback ratios. Verify business legitimacy, cross-check refund and ownership details, and scrutinize large or recurrent disputes to detect collusive or inflated chargebacks designed to obscure illicit fund movements.

Implement specialized chargeback monitoring rules to detect repeated or high-value disputes, unexpected dispute patterns deviating from typical merchant or customer behavior, or collusive indicators (e.g., matching addresses or suspicious dispute timing). By isolating abnormal chargeback activity, institutions can promptly investigate and prevent criminals from layering illicit funds through fraudulent reversals.

Provide specialized training for dispute resolution and customer service teams to recognize red flags associated with chargeback manipulation. Teach staff to identify collusion indicators, stolen identity usage, or repetitive high-value reversals, and to escalate these cases for thorough investigation, ensuring timely intervention against illicit layering schemes.

Temporarily limit or block payment processing capabilities for merchants or customers whose chargeback levels exceed acceptable thresholds or exhibit collusive dispute patterns. Actions may include reducing daily transaction limits, suspending specific credit card usage, or placing account holds while investigations proceed, directly curtailing further misuse of chargebacks to launder funds.

Continuously re-evaluate merchants and customers for escalating chargeback volumes, abrupt changes in dispute reasons, or sustained high dispute-to-sales ratios. Investigate sudden or repeated spikes in refund requests to identify fraudulent reversals being used for layering or obfuscating funds.

• Once chargeback refunds are approved, criminals direct these funds through decentralized exchanges, converting them into digital assets.
• This transfer obfuscates the audit trail, as cryptocurrency transactions intermix chargeback proceeds with legitimate crypto flows.
• Decentralized platforms reduce transparency around ownership, making it more difficult to trace the laundered funds back to the original fraudulent disputes.

• Criminals initiate chargebacks by falsely disputing transactions (e.g., claiming non-delivery or unauthorized use), thus reversing settled payments.
• They may use stolen or synthetic identities, or corporate/third-party cards, concealing the true origin of funds.
• By manipulating chargeback thresholds, they repeatedly launder funds without attracting immediate scrutiny from card networks or acquirers.

• Criminals use credit cards (often with stolen or synthetic identities) to file fraudulent disputes, claiming non-delivery or defective goods.
• They may exploit corporate or third-party cards to obscure the true origin of funds, manipulating the card network’s chargeback process to move illicit proceeds.

• Criminals can operate as both seller and buyer, generating fraudulent sales and then initiating chargebacks to siphon illicit funds under the guise of legitimate refunds.
• Automated or limited-oversight dispute mechanisms make it easier to file repeated or high-value chargebacks without immediate detection.

• Fraudsters rely on the dispute resolution channels within payment processors to initiate partial or full refunds based on fabricated reasons (e.g., unauthorized charges).
• By cycling funds back through legitimate settlement systems, they complicate traceability of the original criminal proceeds.

• Criminals may establish or collude with merchant accounts to inflate or fabricate sales, then initiate chargebacks.
• They monitor chargeback ratios to remain below higher scrutiny thresholds, ensuring these refunds appear routine while laundering illicit funds.

• These platforms offer quick dispute processes with minimal friction, which criminals exploit by claiming delivery issues, defective products, or billing errors.
• The anonymized or semi-anonymized user accounts enable the layering of refunds, obscuring the illicit source of funds.

Cardholders, whether using legitimate or stolen/synthetic identities, facilitate chargeback fraud by:

• Initiating disputes under claims of non-delivery, defective merchandise, or billing errors.
• Exploiting the legitimate refund process to transform illicit proceeds into apparently reimbursed funds.
• Potentially collaborating with merchants to reinforce false claims and reintroduce the funds into lawful payment channels.

Online marketplaces can be exploited when criminals operate as both buyer and seller, generating fabricated sales and:

• Initiating false chargebacks to secure refunds under fabricated reasons (e.g., non-delivery or billing inconsistencies).
• Taking advantage of automated dispute processes with limited oversight, thus repeatedly siphoning funds while concealing their true origin.

Illicit operators initiate and orchestrate fraudulent chargebacks by:

• Submitting fabricated or misleading dispute claims to credit card issuers or payment platforms.
• Coordinating with colluding merchants or controlling both merchant and cardholder roles to inflate or invent transactions.
• Manipulating transactional records and refund processes to obscure the original source of illicit funds, complicating financial institution detection.

Payment service providers are unwittingly exploited in the chargeback process by:

• Offering legitimate dispute resolution channels that criminals manipulate with fabricated justifications.
• Processing refunds that reintroduce illicit funds into regular financial flows, complicating link analysis and tracing efforts.

Merchants, under criminal control or colluding with illicit operators, enable fraudulent chargebacks by:

• Fabricating sales or inflating transaction amounts and then facilitating bogus refund requests.
• Maintaining accounts and records that support or corroborate fraudulent chargeback claims.
• Monitoring chargeback ratios to stay below thresholds that trigger acquirer or card network scrutiny, allowing ongoing laundering activity.

Virtual asset service providers are involved when criminals channel disputed refunds into digital asset exchanges by:

• Converting newly refunded funds into cryptocurrencies, thereby creating additional layers of anonymity.
• Utilizing decentralized or peer-to-peer platforms to obscure transaction trails, which complicates traditional financial tracking.