Dutch neobank Bunq enters partnerships with Mastercard and Nvidia
Dutch neobank Bunq has entered into two partnerships with Mastercard and US-based computer hardware manufacturer Nvidia to enhance its user experience through open banking and to combat fraudsters with the help of accelerated computing and AI.
Bunq partners Mastercard and Nvidia
Bunq’s collaboration with Mastercard will see it leverage the payment giant’s Open Banking platform, which will enable Bunq customers to add accounts from any bank to their Bunq app, providing them with a “complete overview of their finances” and spending insights across all their accounts.
Moreover, the company says that Finn, Bunq’s personal AI assistant, will be able to “enrich these insights” by incorporating transaction data from multiple banks.
Bunq claims that this development makes it Europe’s first bank to leverage AI in open banking.
The digital challenger says it has seen a “surge in user engagement” since its adoption of open banking, reporting that approximately 40% of surveyed users showed a significant increase in app usage once the features were introduced.
Currently, the open banking features are available to users in France, Germany, and the Netherlands, with the bank planning to expand the services across the rest of Europe at a later date.
“Debunking financial fraudsters”
Nvidia also revealed this week that Bunq has partnered with the firm to leverage generative AI (GenAI) to help improve its fraud and money laundering detection capabilities.
The neobank has selected Nvidia’s GPUs to power its AI-driven transaction monitoring system and accelerate its data processing pipeline.
Furthermore, the California-headquartered firm claims that Bunq was able to train its fraud-detection model nearly 100 times faster by utilising the open source Nvidia Rapids suite of GPU-accelerated data science libraries.
“We chose NVIDIA’s advanced, GPU-optimised software as it enables us to use larger datasets and speed the training of new models — sometimes by an order of magnitude — resulting in improved model accuracy and reduced false positives,” says Ali el Hassouni, head of data and AI at Bunq.
In addition, to further boost the response accuracy of Bunq’s Finn offering, the company is exploring the benefits of implementing Nvidia’s NeMo Retriever offering, a collection of GenAI microservices.
“Our initial testing of NeMo Retriever embedding NIM has been extremely positive, and our collaboration with Nvidia on LLMs is poised to help us to take Finn to the next level and enhance customer experience,” explains el Hassouni.
