The Rise of Remote Purchase Fraud and AI-Generated Financial Fakes
The Rise of Remote Purchase Fraud and AI-Generated Financial Fakes
By Matthew Grosse and team
Updated with 2025 UK Finance insights & industry recommendations
Online Fraud Is Reaching New Heights — Here’s Why
Fraud has gone digital — and fast. In 2024, UK Finance reported a record-breaking 2.6 million cases of remote purchase fraud, where scammers use stolen card data to shop online. That’s over 7,000 incidents per day.
At the same time, AI-generated fake documents are making it harder to tell real from forged receipts, expense claims, and invoices. Whether you’re a fintech, payment processor, or marketplace platform, the risk is no longer theoretical — it’s systemic.
How the Scams Work
Many remote purchase frauds start with phishing or smishing tactics. Users receive texts or emails that trick them into sharing:
- Card details
- Login credentials
- One-time passcodes (OTPs) sent via SMS
With this data, criminals can:
- Shop online using stolen credentials
- Add cards to digital wallets and use them in-store
- Defeat OTP-based security for “card-not-present” transactions
Why Visual Inspection Is Dead
Even sophisticated back-office teams can’t spot modern fakes by eye. New AI models (like those from OpenAI and Midjourney) can generate photorealistic receipts, invoices, and ID documents.
This affects:
- Expense reimbursement systems
- Merchant refund validations
- Tax deduction claims
- B2B platform onboarding
Read: Can You Spot a Financial Fake?
🔍 Real Solutions: BIN + ML-Based Fraud Defense
✅ BIN Lookup API
Instantly identify the true identity of a card:
- Issuer and country
- Card brand (Visa, Mastercard, etc.)
- Prepaid vs. credit vs. debit
- Risk-prone BINs
Use Case: Detect cards issued in high-fraud regions, catch prepaid cards pretending to be credit, flag inconsistencies in geo-IP vs. issuing country.
🧠 ML-Powered Fraud Detection API
This API scores every transaction in real time using:
- User behavior patterns
- Device fingerprinting
- Velocity tracking
- Historical fraud clusters
Use Case: Flag high-risk transactions before they settle, reduce chargebacks, and detect synthetic ID usage at the edge.
How Major Card Networks Fight Back
According to Yahoo Finance, Visa, Mastercard, Amex, and Discover now deploy:
- AI-powered risk scoring
- EMV chip authentication
- 3DS secure layers
- Tokenization and biometrics
Yet even with billions in network-level defenses, fraud still cost the UK £1.2 billion in 2024 — showing that pre-transaction risk scoring tools are a critical extra layer.
What You Can Do Now
If you’re building or running:
- A fintech app
- A lending platform
- A payroll or expense product
- A payment gateway
Integrate defenses early. Here’s where to start:
- BIN Lookup API: Spot risky cards fast
- Fraud Detection API: Score transactions in real time
These tools are developer-friendly, scalable, and work alongside your existing stack.
Final Takeaway
Fraud isn't just a back-office headache anymore — it's a front-line security threat. AI fakes and card-based scams are evolving faster than ever. The solution? Modern APIs that integrate behavioral intelligence, network verification, and real-time scoring.
Protect your platform — before the fraud lands.