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In this post, you will learn how Inscribe developed an agentic AI system using Amazon Bedrock that reasons across documents the way an expert fraud analyst would. With this new agentic AI system, Inscribe now detects tampered, fabricated, and AI-generated financial documents in under 90 seconds. This is a 20x improvement over traditional manual review, while maintaining the accuracy and explainability required by financial services regulations.
Fraud now appears in 1 of every 16 documents, and AI-generated forgeries grew 5x from April to December 2025 (Inscribe’s 2026 State of Document Fraud Report). For financial institutions processing thousands of applications daily, this scale of deception creates an impossible challenge. Traditional manual review takes 30 minutes per application and cannot keep pace with rising volumes. More critically, manual processes struggle to detect the evolving tactics that modern fraud tools make possible. Speed alone is not enough. The solution must also catch sophisticated forgeries, deepfakes, and coordinated fraud rings that human reviewers and legacy rule-based systems were never designed to identify.
Inscribe has been building AI-powered document fraud detection since 2017 for leading banks, lenders, and fintechs. In this post, you will learn how Inscribe developed an agentic AI system using Amazon Bedrock that reasons across documents the way an expert fraud analyst would. With this new agentic AI system, Inscribe now detects tampered, fabricated, and AI-generated financial documents in under 90 seconds. This is a 20x improvement over traditional manual review, while maintaining the accuracy and explainability required by financial services regulations.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies, such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API. It also provides a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.
Consider a typical loan application at a mid-sized bank. A customer submits bank statements, pay stubs, tax documents, and identification. A fraud analyst must verify each document’s authenticity, cross-reference information across documents, check for signs of manipulation including increasingly sophisticated deepfakes and AI-generated forgeries, and research the applicant’s employer and address. They must do all of this while maintaining a fast turnaround to avoid losing the customer to competitors.
The financial stakes are significant. A single missed case can mean millions in direct losses, regulatory exposure for financial crime failures, and reputational consequences that are even harder to recover from. Time-intensive manual reviews delay customer approvals for days, leading to high abandonment rates. Meanwhile, fraudsters continuously change tactics, shifting from AI deepfakes and fabricated documents to synthetic identity fraud, knowing that overworked analysts might miss subtle manipulation signals when processing hundreds of applications daily.
Inscribe built an AI solution that works alongside risk and underwriting teams. It automates routine document analysis while flagging complex cases for human review, combining deep domain expertise with layered detection techniques to uncover what manual review teams and other providers miss.
