Executive Summary

SaaS merchants face repeat chargebacks from serial disputers who refile after losing. Build an AI-enabled system to detect serial disputers, automate evidence bundling, and block repeat abuse at the payments layer. Volume and cost of card-not-present disputes have risen with more digital subscriptions and video/AI usage; the poster reports heavy usage of AI credits and exports during repeated filings, showing high frequency and financial exposure per incident. Modern payments platforms and issuers now accept richer machine-readable evidence and merchant-to-issuer communication channels, so automating evidence packaging and pattern scoring is now actionable. Advances in anomaly detection and entity resolution let vendors reliably link repeat filers across changing dispute reasons, making automated prevention and issuer coordination practical today. Use dispute outcome signals plus product usage telemetry to build a data moat that identifies serial disputers and hostile reuse patterns. The Reddit thread shows a user who lost a dispute but immediately refiled with a new reason while continuing heavy use of the product, indicating repeat-pattern behavior that can be detected by correlating cardholder IDs, device fingerprints, activity timelines, and evidence response histories. By combining automated evidence bundling, issuer-format responses, and behavioral scoring tied to a growing cross-customer dataset, the product creates a defensible signal set that improves over time and reduces manual effort for merchants.

Market Opportunity

Stop repeat chargeback abuse - automated detection and dispute defense targets a $12.0B = 3,000,000 online merchants x $4,000 ACV (global merchants paying chargeback prevention/mitigation services averaged over SMB and mid-market) total addressable market with medium saturation and a year-over-year growth rate of 8-12% estimated growth in payments risk and chargeback mitigation solutions driven by digital subscriptions and CNP volume.

Key trends driving demand: Rising subscription commerce -- more recurring payments increase exposure to repeat disputes and higher lifetime cost per abuse incident, creating demand for specialized prevention; Issuer-merchant data sharing -- networks and issuers allow richer evidence formats and merchant-to-issuer signals, improving chance to win disputes if packaged correctly; Automation of ops -- merchants want to replace manual evidence submission with automated, standardized workflows to lower cost and speed response; Behavioral fraud detection -- pattern recognition across transactions and account activity makes serial disputer detection possible at scale.

Key competitors include Chargebacks911, Ethoca (Mastercard), Verifi, Midigator, Stripe Radar (adjacent).

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Stop repeat chargeback abuse - automated detection and dispute defense

Executive Summary

Market Validation

Market Opportunity

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