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Deep Learning Powers Better Decisions in Finance

Massive datasets. Perpetual market fluctuations. Swift analysis. Personalized assistance. Remote workforces. Intelligent technology can address critical challenges within the modern financial services industry. Institutions can boost risk management, data-backed decisions, security, and customer experiences with NVIDIA’s AI, deep learning, machine learning, natural language processing (NLP), and remote work solutions.

Key Financial Sectors









Computational Risk

Accurate forecasts are critical for the performance of businesses. NVIDIA’s AI platform accelerates the creation of models that help financial experts assess trends, identify risks, and ensure better information for prospective planning.

Using an NVIDIA DGX-2 system running accelerated Python libraries, NVIDIA shattered the previous STAC-A3 benchmark result by running  20 million simulations versus the previous record of 3,200 simulations during the prescribed 60-minute test period.

– NVIDIA Delivers More Than 6,000x Speedup on Key Algorithm for Hedge Funds, NVIDIA Blog

Accelerated Computing for Trading

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

Fraud Detection

The complexity of fraudulent activity, such as payment theft and money laundering, has evolved in proportionate to advancements in technology. 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

Conversational AI

Natural language processing is helping financial institutions to personalize their customer experience and increase engagement. NVIDIA is enabling 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

Do Your Life’s Work from Anywhere

In financial services, seconds can be critical, so professionals, from bankers to traders, need powerful computing tools that work in real time—especially when working remotely with dispersed teams. Explore ways to digitally transform your organization and give your employees the ability to work effectively from wherever they are.

Watch Webinar: Financial Professionals Stay Productive While Working Remote

Read E-Book: Do Your Life’s Work from Anywhere in Finance

View Webpage: Work Remote with NVIDIA

AI in Finance from Data Center to Cloud

Unprecedented Acceleration at Every Scale

In today's fast-paced markets, the ability to test and simulate model hypotheses with speed and accuracy can create revenue opportunities for financial institutions. The NVIDIA A100 Tensor Core GPU delivers acceleration at every scale for AI, data analytics, and high-performance computing (HPC) to tackle the toughest computing challenges in finance.

Unprecedented Acceleration at Every Scale
Powerful Computing for Data Centers

Powerful Computing for Data Centers

Financial services customers require AI infrastructure that improves upon traditional approaches, which involved slow architectures that siloed analytics, training, and inference workloads. This approach created complexity, drove up costs, constrained speed of scale, and wasn’t ready for modern AI.

From edge to data center, Tensor Core GPUs are available from every major computer system and server manufacturer to accelerate AI training. And NVIDIA DGX systems are equipped with the DGX software stack for rapid AI deployment.

Democratization—from Data Center to the Cloud

NVIDIA GPUs are available in all major cloud platforms worldwide. And NVIDIA’s software libraries and software development kits (SDKs) create a scalable solution that enables customers to deploy AI in the cloud, 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. And with GPU-accelerated data science, organizations can run an exhaustive array of simulations, testing the robustness of their models and creating new financial opportunities

Democratization—from Data Center to the Cloud

NVIDIA AI Consulting Partner Network

Service Delivery Partners have special expertise in the transformational business benefits afforded by deep learning (DL), machine learning (ML), and artificial intelligence (AI). Learn about the consulting services they provide, as well as impactful solutions specifically for critical use cases in finance like conversational AI, computational risk, and fraud detection.

How GPUs Are Changing the Industry

Discover the key role GPUs are playing in Wells Fargo’s risk management strategy.

When you’re ready for a deeper dive, continue exploring to see how other leaders in financial services are leveraging the power of GPUs. 

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