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description: European banks and fintechs are deploying open weight AI models on NVIDIA accelerated computing to build proprietary financial intelligence. Revolut is...
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og:description: European banks and fintechs are deploying open weight AI models on NVIDIA accelerated computing to build proprietary financial intelligence. Revolut is...
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# Leading European Financial Services Organizations Embrace Open Models to Build Proprietary Intelligence

**[NVIDIA](https://daily.dev/sources/nvidia)** · 4 min read · 0 upvotes · 0 comments

## Summary

European banks and fintechs are deploying open weight AI models on NVIDIA accelerated computing to build proprietary financial intelligence. Revolut is rebuilding its technology stack on a single transaction foundation model called PRAGMA, powered by NVIDIA Blackwell Ultra GPUs, and is scaling it in production with an initial 80 million customers, engineered to scale 3x. Starling Bank trained an agentic model on U.K. sovereign cloud, while Lloyds built ATUM using RTX PRO 6000 Blackwell GPUs. Neobank bunq's Finn assistant now runs on open weight models, matching the quality of leading closed models at 60% of the cost per answer when deployed on Nebius. Stripe reports 42x faster data pipelines and 92% cost savings for its Radar fraud-detection platform using NVIDIA GPU-accelerated Ray Data in offline testing.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blogs.nvidia.com/blog/european-financial-services-organizations-open-models-proprietary-intelligence>

## Questions this post answers

### How much does running open weight models cost compared to closed models for a banking AI assistant?

Neobank bunq's agentic assistant Finn runs on open weight models deployed on Nebius, matching the quality of leading closed models while costing 60% of the cost per answer. This is powered by NVIDIA accelerated computing, demonstrating that open weight models can match closed-model quality at a fraction of the price for production banking assistants.

_Teams weighing open versus closed models for AI assistants can track real-world cost comparisons like this on daily.dev._

### What performance gains has Stripe seen from GPU-accelerated data pipelines for fraud detection?

Stripe sees 42x faster data pipelines and 92% cost savings for its Stripe Radar fraud-detection platform using NVIDIA GPU-accelerated Ray Data in offline testing. This allows Stripe Radar's machine learning pipelines to continuously optimize model training and improve fraud detection at much lower infrastructure cost.

_Engineers building fraud-detection pipelines can follow benchmarks like this on daily.dev to size their own GPU infrastructure._

### What is Revolut's PRAGMA foundation model and what scale does it operate at?

PRAGMA is a single foundation model Revolut built to rebuild its technology stack, powered by NVIDIA accelerated computing including cuDF and Dynamo-Triton software on NVIDIA Blackwell Ultra GPUs. It is in production serving an initial 80 million customers and is engineered to scale 3x, built in collaboration with NVIDIA.

_Developers tracking how banks productionize foundation models can follow cases like Revolut's PRAGMA on daily.dev._

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---

Tags: [#open-source](https://daily.dev/tags/open-source), [#nvidia](https://daily.dev/tags/nvidia), [#gpu](https://daily.dev/tags/gpu), [#fintech](https://daily.dev/tags/fintech), [#fraud-detection](https://daily.dev/tags/fraud-detection)

[View this post on daily.dev](https://daily.dev/posts/leading-european-financial-services-organizations-embrace-open-models-to-build-proprietary-intellige-ycglgxpsp)

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