Sun Finance drastically improves ID verification with AI on AWS
Sun Finance has implemented an AI-driven solution on AWS to automate ID verification and fraud detection. This has led to improved accuracy and significantly shorter processing times.
What happened?
Sun Finance, a global fintech operation, has developed an AI-driven pipeline for identity verification (IDV) and fraud detection. The solution is built on AWS services such as Amazon Bedrock, Amazon Textract, and Amazon Rekognition. By combining specialised OCR with large language models (LLM), they have significantly streamlined the process.
Key facts
”In this post, we show how Sun Finance used Amazon Bedrock, Amazon Textract, and Amazon Rekognition to build an AI-powered identity verification (IDV) pipeline.”
”The solution improved extraction accuracy from 79.7% to 90.8%, cut per-document costs by 91%, and reduced processing time from up to 20 hours to under 5 seconds.”
”You'll learn how combining specialized OCR with large language model (LLM) structuring outperformed using either tool alone.”
Why it matters
The new AI solution has improved extraction accuracy from 79.7% to 90.8%. Furthermore, costs per document have decreased by 91%, and processing time has been reduced from up to 20 hours to under 5 seconds. This demonstrates the potential to automate and improve financial processes with generative AI, as the combined effect of the tools exceeds that of individual solutions.
Who is affected?
Fintech companies handling large volumes of customer identification and fraud prevention are affected. Developers and AI architects working with cloud-based AI solutions, machine learning, and generative AI can benefit from this architecture. End-users seeking fast and secure identity verification are also impacted.
What else you should know
The architecture also includes a serverless system for fraud detection via vector search. The solution emphasises the synergy between different AI technologies to achieve results that are not possible with individual tools.
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