Inscribe Uses Amazon Bedrock to Combat Document Fraud
Summary
Inscribe developed an agentic AI system using Amazon Bedrock that mimics expert fraud analysts to detect tampered, fabricated, and AI-generated financial documents. This system achieves a 20x improvement in detection speed, identifying fraud in under 90 seconds while maintaining accuracy and regulatory compliance.
Why it matters
This case study demonstrates how agentic AI and LLMs can be applied to critical business problems like fraud detection, offering substantial improvements in speed and efficiency while meeting regulatory requirements.
How to implement this in your domain
- 1Identify specific high-value, repetitive tasks within your organization that require expert reasoning.
- 2Explore agentic AI frameworks and platforms like Amazon Bedrock for building custom solutions.
- 3Develop a robust dataset of both legitimate and fraudulent examples for training and validation.
- 4Design the AI agent to mimic the decision-making process of human experts, ensuring explainability.
- 5Integrate the AI system into existing workflows, focusing on seamless data input and output for rapid deployment.
Who benefits
Key takeaways
- Agentic AI systems can automate complex, expert-level tasks like fraud detection.
- Amazon Bedrock offers a platform for developing such advanced AI solutions.
- Significant efficiency gains (20x faster) are achievable while maintaining accuracy.
- AI can meet stringent regulatory requirements for explainability in critical domains.
Original post by Conor Burke
"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 u…"
View on XOriginally posted by Conor Burke on X · view source
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