PNY Technologies Inc.

Powering The Future Of Finance

Massive and rapidly growing datasets. Perpetual market fluctuations and volatility driven by business or unforeseeable external events. Swift analysis. Personalized assistance. Remote or work from home workforce options. Intelligent technology addresses critical challenges within the modern financial services sector. Institutions can enhance risk management, data-backed decisions, security, customer interactions, and realize competitive advantage with NVIDIA-powered AI, deep learning, machine learning, natural language processing (NLP) and remote work solutions.

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Bankers, brokers, asset managers, and traders are used to working in highly customized, onsite work environments. But working remotely is a necessity in emergencies, as these professionals navigate uncharted waters with dispersed teams at offshoot sites or from home, creating unprecedented complexity in the vital day-to-day functions required for the exchange of financial assets and running global markets. Remote environments also introduce operational, security, and communications challenges. Even millisecond trading delays can be extremely costly. Although the industry is adopting virtual desktop infrastructure (VDI) for security and management, GPU-powered solutions in notebook, desktop, deskside, server, and cloud environments need to enable deep learning, data science, virtualization, and more to provide the dynamic working environments these challenging times require.

NVIDIA RTX Server For Virtual Workstations, AI and Data Science

Based on an NVIDIA® defined reference platform delivered by select OEMs, NVIDIA RTX Server systems based on NVIDIA Quadro® RTX™ 8000 and RTX 6000 (active or passive) boards are fully qualified and certified by NVIDIA for data center use – even in the most demanding financial use cases. They can deliver virtual workstations that provide all of the benefits of the Quadro platform in a virtual environment from the data center with NVIDIA Quadro Virtual Data Center Workstation (Quadro vDWS) software.

AI and Data Science financial solutions are also ideal venues for NVIDIA RTX Server deployment. Combine NVIDIA Quadro RTX 8000 and RTX 6000 GPUs with NVIDIA vComputeServer software to run compute workloads like AI, data science, and deep learning on a virtual machine to perform basic research or power next generation financial services solutions. NVIDIA’s scalable CUDA-X AI software stack and NGC containers for GPU-accelerated data science tools run across NVIDIA’s professional GPUs and scale from the desktop to servers and the cloud – at a fraction of the cost, space, and power requirements of CPU-based solutions.

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NVIDIA-Powered Data Science Workstations

Data is fundamentally changing the way finance sector companies do business, driving demand for data scientists and increasing the complexity in their workflows. Get the performance you need to transform massive amounts of data into actional business insights and create amazing customer experiences with NVIDIA-powered data science workstations. Built by leading workstation providers to combine the power of Quadro RTX GPUs with accelerated CUDA-X AI data science software to deliver a new breed of fully-integrated workstations for data science the race for competitive advantage starts here.

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NVIDIA Quadro RTX Powered Workstations

These powerful systems accelerate the future of finance and ancillary functions surrounding it. Equipped with GPUs featuring advanced multi-precision Tensor Cores for AI and big data analytics, and RT Cores for unmatched graphics and visualization with an AI assist, innovative AI-enabled financial sector applications are now accessible to finance professionals in a turnkey workstation that lets them work better, smarter, and faster than ever before.

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Faster processing results in successful trade execution and increased revenue. GPU-powered hardware acceleration decreases latency, allowing operations to remain competitive.

“Financial modeling for trading involves a considerable amount of expertise and time. The speed of NVIDIA-accelerated systems enables new design choices for a variety of models.” – How GPU-Accelerated Compute marks A New Era for Financial Trading technical brief


The complexity of fraudulent activity, such as payment theft and money laundering, has evolved (the Red Queen hypothesis) as technology has advanced. Deep learning (DL) dramatically reduces false positives in transactional fraud.

With the availability of large volumes of customer data, such as raw transactions over time (RNN) and transaction summary vectors (RNN and CNN), firms can train AI neural networks like autoencoders and models to identify irregularities in transactional activity patterns.

“97% of all AML cases are false positives which takes up significant operations resources.” – Leveraging Deep learning To Build Safer Anti-Money Laundering Solutions Webinar

Also read the and NVIDIA Joint Solution Brief


Natural language processing is helping financial institutions to personalize their customer experience and increase engagement. NVIDIA GPUs, including Quadro RTX, enable real-time conversational AI by optimizing the training and inference performance of BERT, a popular NLP model.

“NVIDIA developers optimized the 110 million-parameter BERT-Base model for inference using NVIDIA TensorRT software. Running on NVIDIA T4 GPUs, the model was able to compute responses in just 2.2 milliseconds when tested on the Stanford Question Answering Dataset.” – What is conversational AI, NVIDIA Blog


Unprecedented Acceleration at Every Scale

In today’s fast-paced and volatile markets, the ability to test and simulate model hypotheses with speed and accuracy can create revenue opportunities for financial institutions. NVIDIA Tensor Core equipped GPUs deliver acceleration at every scale for AI, data analytics, and high-performance computing (HPC) to tackle the toughest computing challenges in finance – from workstations to servers and the cloud.


Financial services customers require AI infrastructure that improves upon traditional approaches, which involved SLOW CPU-based architectures that siloed analytics, training, and inference workloads. This approach’s intrinsic complexity drives up costs, constrains the speed and scope of scalability, and isn’t ready for modern AI.

From at-the-edge to data center, Tensor Core NVIDIA GPUs, including Quadro RTX, are available from every major computer system and server manufacturer to accelerate AI training. And turnkey solutions like the NVIDIA-Powered Data Science Workstation, and reference designs like NVIDIA Quadro RTX Server, lead to NVIDIA’s DGX systems – a full suite of data science and data center solutions with CUDA-X AI at their core and a consistent, compatible, and scalable ecosystem of associated software development and deployment tools.


NVIDIA GPUs featuring Tensor Cores are available in all major cloud platforms worldwide. NVIDIA’s software libraries and software development kits (SDKs) create scalable solutions that enable companies to initiate development on the desktop with an eye to ultimate cloud deployment, on their servers, or at-the-edge. These SDKs include NVIDIA TensorRT for inference, Transfer Learning Toolkit for tuning deep neural networks (DNNs), and NGC for GPU-accelerated software containers. RAPIDS enables financial institutions to execute end-to-end data science and analytics pipelines on GPUs for better prediction accuracy. With GPU-accelerated data science, organizations can run an exhaustive array of simulations, testing the robustness of their models and creating new financial opportunities.

Only the U.S. Treasury is allowed to print money. The rest of us need to rely on NVIDIA GPUs with Tensor Cores and NVIDIA’s unmatched AI software development stack and ecosystem of 3rd party ISVs!

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