Onboard sellers faster. Stop payout fraud before it hits P&L.
Marketplaces face high-volume review work across onboarding, refunds, payouts, and trust & safety , but manual review still creates bottlenecks despite many fraud tools. Credio deploys specialized AI agents as a risk intelligence layer inside your existing stack, extending analyst capacity without rip-and-replace.
Workflow in order of execution
01
Onboarding Verification
Verify seller, vendor, and customer legitimacy before go-live
Without Credio · High-volume seller onboarding overwhelms trust teams , synthetic identities, document forgeries, and incomplete KYB signals slip through despite automated screening.
Agentic verification at intake , including entity legitimacy checks, document fraud detection (metadata forensics, visual tampering, risk intelligence), and structured outreach when ownership or business signals are unclear , closing the recall-vs-precision gap before sellers transact.
Onboarding checks
02
Refund Review Automation
Front-line refund decisions with abuse pattern detection
Without Credio · Refund queues grow faster than analyst headcount , multi-account abuse, synthetic identity, and refund-habit patterns are hard to catch consistently at scale.
Agents review flagged refunds against customer behavior history, multi-account linkages, and refund-habit patterns , bringing BPO-level effort back in house with documented approve, deny, or escalate recommendations.
Refund checks
03
Payout ATO Prevention
Verify payout changes before funds move
Without Credio · Account takeover on seller payout details causes direct P&L impact , ACH transfers execute before teams can verify whether the change was legitimate.
Before every ACH transfer, agents verify recent payout-detail changes through outbound calls and identity checks , stopping account takeover losses before funds leave the platform.
Verification checks
04
Trust & Safety QA
Sample reviews and content moderation at scale
Without Credio · Fraud-engine decisions drift as attack patterns evolve , teams lack bandwidth for sample QA, content moderation backlogs grow, and rule thresholds go stale without structured review.
Post-fact sample reviews of flagged orders detect rule drift and assess whether current thresholds still hold. Content moderation scales across image detection, comments, and policy violations , with alerts routed to analysts with full evidence trails.
QA outputs
Risk intelligence layer
Credio extends your existing fraud stack , not a replacement. Agents handle high-volume review, context gathering, and documentation so analysts focus on policy, exceptions, and evolving attack patterns.
Expected outcomes
Seller onboarding throughput without adding headcount
Reduction in payout fraud losses from account takeover
Auditable trust & safety decisions at scale
Credio is live in production at a leading online booking platform, a large e-commerce jewelry business, and a major food delivery service , handling agentic review at scale with full audit trails.
FAQ
Common questions
No , Credio acts as a risk intelligence layer inside your existing stack, handling high-volume review work and documentation while your rules engines and analysts retain policy control.
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