With customers in 30 countries and products spanning automotive, telecoms, and finance, BNP Paribas Cardif must take a proactive approach to research and development – especially when it comes to AI use cases.
Cardif's insurance workflows handle everything from ID cards to injury claim reports – vast numbers of varied, sensitive documents. It needed an on-premises solution to process these documents quickly and at scale to keep data safe, outpace competitors, and protect its brand reputation.
Using Domino as its in-house platform, Cardif built an intelligent document processing system that delivers:
The pipeline-first, on-premises approach helps speed up AI innovation, reduces operational costs by minimizing memory requirements, and improves model responsiveness with lower latency.
Powered by Domino, Cardif’s in-house AI models now achieve 85% accuracy, significantly outperforming third-party tools. It can also keep critical customer data on-premises for added security, and rapidly roll out new AI capabilities to better serve its customers.
with 85% extraction accuracy
enabling secure, compliant processes
end-to-end generative pipelines
When we benchmark what we can do on-premises compared to external vendors, we do far better.
— Sébastien Conort, Chief Data Scientist & ML Engineering Director, BNP Paribas Cardif.
Source: Building future-proof in-house AI systems: An illustration with intelligent document processing session delivered at RevX London.
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