Inscribe's agentic AI on Amazon Bedrock cuts document fraud detection to 90 seconds

Inscribe, a company specializing in AI-powered document fraud detection since 2017, has developed an agentic AI system using Amazon Bedrock that revolutionizes fraud detection for financial institutions. The system addresses the alarming rise in document fraud — now appearing in 1 of every 16 documents, with AI-generated forgeries increasing 5x between April and December 2025. Traditional manual review takes 30 minutes per application and struggles to catch deepfakes, AI-generated forgeries, and coordinated fraud rings. Inscribe's new system works like an expert analyst: it submits a document, routes it through specialized models, runs parallel forensic checks, searches the web to verify employer details, cross-references data across the full document set, and generates an audit-ready fraud report — all in under 90 seconds. This represents a 20x speed improvement while maintaining the accuracy and explainability required by financial services regulations.

The agentic AI system built on Amazon Bedrock coordinates multiple foundation models (from AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon) and external APIs to reason across documents the way an expert fraud analyst would. It automates routine analysis while flagging complex cases for human review, combining deep domain expertise with layered detection techniques. The system breaks a goal into steps, uses multiple tools, and works through to completion — unlike basic AI tools that answer single questions. For example, it doesn't just flag a suspicious field; it runs comprehensive checks including web searches for employer verification and cross-referencing all submitted documents. The financial stakes are significant: a single missed case can mean millions in direct losses, regulatory exposure, and reputational damage. Time-intensive manual reviews delay customer approvals for days, leading to high abandonment rates. Inscribe's solution helps financial institutions process thousands of applications daily while catching sophisticated schemes that human reviewers and legacy rule-based systems miss.