Payment Processing Services

• Criminals can route covert bribe payments under ambiguous labels (e.g., 'facilitation fees' or inflated consultancy charges), causing them to appear as ordinary transactions.
• By blending these payments among legitimate flows, bribes are less likely to trigger immediate AML alerts.

• Criminals route inflated invoice transactions through standard payment channels, blending them with legitimate business payments.
• Automated or high-volume payment systems often lack thorough scrutiny, allowing disguised overpayments to pass as routine transactions.

• Illicit actors may inject or modify payment data mid-process, creating false transaction logs or receipts to hide the true flow of illicit funds.
• They can also exploit any lack of robust audit trails to reconcile manipulated payouts with fabricated documentation, preventing timely red flags.

• Enable large volumes of card-based or online transactions to be recorded as legitimate ticket or merchandise revenues for concerts or events.
• Facilitate rapid co-mingling of illicit proceeds with legitimate entertainment income, obscuring the true source of funds.

• VPN usage masks user location, thwarting region-specific transaction filtering or velocity checks.
• Fraud detection tools relying on IP-based rulesets are less effective, potentially enabling layered transactions that evade typical red flags.
• This anonymity can hamper monitoring of suspicious payment routes and undermine due diligence protocols.

• Illicit operators can set up or manage merchant accounts from public WiFi, masking user identities and complicating location-based transaction monitoring.
• Fraudulent payment requests or suspiciously large transactions are disguised as legitimate e-commerce flows, exploiting weak verification controls from open hotspots.

• Allows larger amounts to be broken into numerous micro-payments to avoid daily or per-transaction monitoring triggers.
• High-volume, low-value transactions can blend in with ordinary merchant activities, complicating detection.

• Educational institutions acting as laundromats can use comprehensive payment gateways to accept large ‘tuition’ or ‘donation’ payments from questionable sources, blending illicit funds with legitimate educational revenues.
• By routing high volumes of transactions through these services, criminals obscure fund origin and reduce scrutiny over individual payments.

• Insiders can selectively disable or override automated fraud filters, allowing suspicious or high-risk transactions to proceed without the usual flags.
• They may manipulate internal transaction records or authorization logs, concealing illicit fund movements from standard monitoring routines.

• Fraudsters route funds to fictitious vendors under the guise of normal operating expenses, making the payments appear routine in financial records.
• Partial or disguised refunds can be issued to further obscure the paper trail, facilitating bribery or siphoning of funds back to conspirators.

• Criminals submit fraudulent identification to set up a merchant profile, passing as legitimate businesses.
• Illicit proceeds enter the financial system disguised as normal customer transactions, making it harder for authorities to link funds to criminal origins.

Automated scripts integrate with payment-gateway APIs or webhooks to trigger thousands of small authorizations and settlements that, in aggregate, launder large sums while each micro-payment mimics ordinary consumer traffic.

• Criminals funnel suspicious or inflated e-commerce payments through mainstream processors, intermingling illicit funds with legitimate flows.
• Automated approvals and rapid settlement processes can limit effective oversight, enabling criminals to obscure transaction details and bypass routine AML triggers.

• Criminals establish merchant accounts or payment gateways linked to sham businesses.
• They process credit card or other electronic payments for non-existent goods or services, disguising illicit funds as genuine commercial receipts.

• Criminals conduct numerous small-value transactions to gauge the threshold at which automated flags or merchant alerts are triggered.
• Once they learn the threshold or suspicious transaction triggers, they adapt subsequent transactions to remain under detection parameters, facilitating larger-scale laundering activities.

• Aggregate diverse payment channels, potentially mixing illicit child exploitation revenues with legitimate transactions.
• Enable rapid settlement of multiple small payments, reducing the likelihood of individual suspicious activity alerts.

• Outsource wage distributions, reducing internal oversight and enabling systematically inflated or fictitious payroll remittances.
• Exploit batch payment platforms that may not rigorously verify each payee’s legitimacy or wage amount.

• Criminals utilize intermediary or aggregator payment solutions to commingle funds, obscuring payer identity and origin.
• External third-party billers or automated payment gateways may omit or mask complete payer details, impeding suspicious activity detection.

• Fraudsters impersonate businesses or authorized representatives to establish merchant accounts, masking the real beneficiaries.
• Under a stolen identity, they process high volumes of payments to integrate illicit funds into seemingly legitimate transactions.

• Criminals route numerous small, ostensibly legitimate transactions through merchant or payment gateways.
• They quickly settle or withdraw funds in other regions, making it difficult to detect the layering of illicit proceeds via disparate payment channels.

• 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 or insiders can alter digital transaction logs to conceal or erase evidence of illicit payments.
• By falsifying records or removing transaction entries, it becomes more difficult for auditors and law enforcement to trace suspicious fund flows.

• By using white-labeled or aggregator-driven payment channels, criminals insert an extra intermediary layer between the licensed provider and end users.
• Sub-agents can handle funds and client onboarding independently, bypassing full AML/CFT checks.
• This fragmentation of transaction data across multiple sub-level platforms hinders effective tracing of illicit flows.

• Criminals exploit payment processing channels to funnel illicit proceeds into legitimate transaction flows, mixing criminal funds with authentic sales.
• By leveraging aggregator or sub-merchant models, they conceal the true source of funds and complicate oversight, allowing seemingly normal transactions to mask fraudulent deposits.

• Fraudsters may set up fake merchant accounts or websites to appear legitimate, directing victims to submit 'advance fees' through these channels.
• The service infrastructure enables seamless acceptance of credit/debit payments, which are then swiftly rerouted or cashed out, hindering detection of fraudulent fund flows.

• Criminals send fraudulent invoices through spoofed or compromised vendor emails, prompting victims to pay via legitimate payment processors but directing funds to attacker-owned accounts.
• Once the payment is approved, the criminals quickly transfer or withdraw the money, making recovery difficult and detection delayed.

• Fraudsters create an investment portal that leverages payment processors to collect funds from new investors quickly.
• Incoming investor capital masks the origin of illicit money by mingling it with legitimate payments and outgoing distributions to earlier participants.