Built to stop fraud, priced to scale

Document fraud is the use of falsified, altered, or fabricated documents to misrepresent identity, income, assets, or business information. Common examples include fake bank statements, pay stubs, tax forms, invoices, and financial statements. With the rise of generative AI, document fraud has become more sophisticated and harder to detect using manual reviews or legacy rules-based systems.

AI document fraud detection works by analyzing a document across multiple layers instead of a single check. Inscribe's detection approach combines four layers: forensic analysis (examining file structure and metadata for signs of tampering), network intelligence (comparing documents against patterns seen across Inscribe's network), semantic analysis (checking that the content is internally consistent), and perceptual analysis (detecting visual manipulation such as copy-paste edits or AI-generated content). Together, these layers catch fraud that a single detection method would miss.

Businesses can detect deepfake documents and AI-generated fraud by using detection tools built specifically for generative AI, since manual review and legacy rules-based systems weren't designed to catch AI-generated forgeries. Effective detection combines perceptual analysis, which flags visual inconsistencies AI image generation tends to introduce, with semantic analysis, which checks whether the numbers and details in a document are internally consistent. Inscribe's AI agents run these checks automatically as documents are submitted, flagging any that show signs of AI generation before they reach a lending decision.

Inscribe detects fraud across the financial documents lenders rely on most, including bank statements, pay stubs, W-2s, tax transcripts, invoices, and business formation documents. Detection methods vary by document type. Bank statement fraud often involves altered balances or fabricated transaction histories, while pay stub fraud typically involves inflated income figures or fabricated employer details. Inscribe's four-layer detection framework applies forensic, network intelligence, semantic, and perceptual checks to each document type to catch these patterns.

Banks and fintechs are adopting AI-powered document fraud detection software because document fraud has grown more sophisticated and harder to catch manually. Generative AI tools have made it easier to fabricate convincing bank statements, pay stubs, and other financial documents, and manual review or legacy rules-based systems can't keep pace with that sophistication. AI-powered detection can review documents in seconds rather than minutes, reducing both fraud losses and the manual review burden on risk teams.

Inscribe's pricing is based on document volume and the features included in your plan. Most customers choose between the Base and Premium plans, with custom quotes available for enterprise needs. Book a demo to get pricing specific to your document volume and use case.

Yes. Inscribe offers a four-week pilot that lets your team evaluate the platform using your own document sample. The pilot includes document analysis, technical performance results, live user testing, and a business case review to help determine ROI before you commit.

The Base plan covers document and customer-level fraud analysis, including document classification, verification, basic parsing, risk scoring, and basic decision engine configurability. The Premium plan includes everything in Base, plus custom insights, advanced parsing, a credit insights dashboard, advanced decision engine configurability, and Collect. Book a demo to see which plan fits your document volume and workflow.