Your physical identity (Social Security number, etc.) is trivial to breach. The single most effective defense is to lock your credit reports with the major bureaus. This prevents fraudulent accounts from being opened in your name, as it blocks most verification checks, effectively freezing out attackers.

Binary decisions are brittle. For payments that are neither clearly safe nor clearly fraudulent, Stripe uses a "soft block." This triggers a 3DS authentication step, allowing legitimate users to proceed while stopping fraudsters, resolving ambiguity without losing revenue.

Major retailers use third-party program managers for their gift cards. When a customer is scammed, the retailer deflects responsibility, stating they don't issue the cards. This structure, combined with weak regulation, leaves fraud victims with little recourse, creating an "accountability sink."

Stripe's AI model processes payments as a distinct data type, not just text. It analyzes transaction sequences across buyers, cards, devices, and merchants to uncover complex fraud patterns invisible to humans, boosting card testing detection from 59% to 97%.

Rather than simply failing to police fraud, Meta perversely profits from it by charging higher rates for ads its systems suspect are fraudulent. This 'scam tax' creates a direct financial incentive to allow illicit ads, turning a blind eye into a lucrative revenue stream.

By creating dense embeddings for every transaction, Stripe's model identifies subtle patterns of card testing (e.g., tiny, repetitive charges) hidden within high-volume merchants' traffic. These attacks are invisible to traditional ML but appear as distinct clusters to the foundation model, boosting detection on large users from 59% to 97%.

While many focus on AI for consumer apps or underwriting, its most significant immediate application has been by fraudsters. AI is driving an 18-20% annual growth in financial fraud by automating scams at an unprecedented scale, making it the most urgent AI-related challenge for the industry.

Unlike debit cards protected by Regulation E, gift cards are intentionally exempted from strong consumer protection laws. This carve-out, lobbied for by retailers to ease commerce, removes the legal requirement for financial institutions to investigate fraud and reimburse victims, shifting the entire loss to the consumer.

Purely model-based or rule-based systems have flaws. Stripe combines them for better results. For instance, a transaction with a CVC code mismatch (a rule) is only blocked if its model-generated risk score is also elevated, preventing rejection of good customers who make simple mistakes.