European neobank bunq has partnered with NVIDIA with the aim of debunking financial fraudsters with the help of accelerated computing and AI. As per the announcement, to meet growing customer needs, bunq turned to generative AI to help detect fraud and money laundering.

Reportedly, its automated transaction-monitoring system, powered by NVIDIA accelerated computing has improved its training speed. A spokesperson from bunq commented that AI has enormous potential to help humanity in so many ways, and this is a great example of how human intelligence can be coupled with AI. Faster fraud detection Traditional transaction-monitoring systems are rules based, meaning algorithms flag suspicious transactions according to a set of criteria that determine if an activity presents risk of fraud or money laundering.

These criteria must be manually set, resulting in high false-positive rates and making such systems labor intensive and difficult to scale. Instead, using supervised and unsupervised learning, bunq’s AI-powered transaction-monitoring system is completely automated and easily scalable. Per the announcement, bunq achieved this using NVIDIA GPUs, which accelerated its data processing pipeline more than 5x.

Moreover, compared with previous methods, bunq trained its fraud-detection model nearly 100x faster using the open-source NVIDIA RAPIDS suite of GPU-accelerated data science libraries. RAPIDS is part of the NVIDIA AI Enterprise software platform, which accelerates data science pipelines and streamlines the development and deployment of production-grade generative AI applications. AI across the bank Additionally, the announcement also stated that the company is exploring NVIDIA NeMo Retriever, a collection of generative AI microservices, to further improve the accuracy of the bank's personal AI assistant called Finn.

NeMo Retriever is a part of NVIDIA NIM inference microservices, which provide models as optimised containers, available with NVIDIA AI Enterprise. .