AI Turns Fake Hardship Claims Into Easy Fraud

Socure research describes how people are using generative AI to create fake hardship letters, income statements, and bank statements to support fraudulent claims using their own identities. The report also observed large-scale account and promotion abuse during the 2026 World Cup, where fraudsters combined real and synthetic identities with burner phones and coordinated account creation.

Key findings

• 13.4 percent of surveyed consumers reported using AI to commit at least one form of fraud.
• AI-fluent fraudsters reported attempting twice as many fraud types and targeting 40 percent more businesses than fraudsters who did not use AI.
• First-party fraud was the most common reported activity among AI-fluent fraudsters, affecting 81 percent of that group.
• 61.3 percent of AI-fluent fraudsters reported using fake hardship letters, while 32.1 percent reported using fake income or bank statements.
• During the 2026 World Cup, Socure tracked 451,884 fraud attempts associated with online sports betting and prediction-market activity.
• The World Cup attacks focused on sign-up bonuses, referral rewards, promotional credits, deposit offers, and rapid onboarding flows.
• About 90 percent of the World Cup-related attacks used real consumer identities, showing that a real identity does not necessarily mean an activity is legitimate.

Who’s being targeted

• Commonly targeted roles: Customer support, Fraud operations, Claims processing teams, Underwriting and lending teams, Customer onboarding teams, Gaming and promotion operations, Financial assistance teams.
• Affected industries: Online gambling and sports betting, Prediction markets, Buy now, pay later providers, Telecommunications, Financial services, Gaming platforms.
• Attack channels: website.
• Impersonated: A legitimate account holder, A legitimate applicant or account holder, A new legitimate customer.

Awareness takeaways

• Treat hardship letters, income records, and bank statements as claims that need independent verification, not as proof simply because they look professional.
• Train customer-facing and review teams to look beyond whether an identity is real; assess whether the requested action and supporting evidence make sense together.
• Apply extra review to promotion-driven new accounts, especially when multiple accounts share device, contact, or behavioral signals.
• Give staff a safe escalation path when a customer cannot explain or validate documents they submitted, rather than relying on a document’s appearance alone.

Red flags to watch for

• The document is unusually polished but provides little verifiable detail.
• The customer cannot independently explain details in the submitted document.
• The claim or document conflicts with account history or other available records.
• Financial documents cannot be verified against trusted sources.
• Document details are inconsistent with known customer, device, or account behavior.
• The applicant rushes approval or repeatedly submits revised documents.
• Multiple new accounts show links through device, phone, domain, or behavioral patterns.
• The account is created only to use a promotion and shows little normal customer activity.
• Contact details use burner phone numbers or disposable domains.