Developer Resources For Financial Services

A hub of news, SDKs, technical resources, and more for developers working in the financial services industry.

The NVIDIA Developer Program gives access to a wide range of SDKs, technical resources, and more for financial services. Sign Up

App Frameworks and SDKs


CUDA

CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs to boost risk management.


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RAPIDS

Run entire data science workflows with high-speed GPU compute and parallelize data loading, data manipulation, and machine learning for 50X faster end-to-end data science pipelines to improve data-backed decisions and security.


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TensorRT

NVIDIA® TensorRT™, an SDK for high-performance deep learning inference, includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for inference applications.


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Riva

NVIDIA® Riva is a GPU-accelerated SDK for building Speech AI applications that are customized for your use case and deliver real-time performance.


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Triton Inference Server

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NVIDIA Triton™ Inference Server, part of the NVIDIA AI platform, is an open-source inference serving software that helps standardize model deployment and execution and delivers fast and scalable AI in production.

NVIDIA® DOCA™ SDK

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With DOCA, developers can program the data center infrastructure of tomorrow by creating software-defined, cloud-native, DPU-accelerated services with zero-trust protection to address the increasing performance and security demands of modern data centers.

NVIDIA Morpheus

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NVIDIA Morpheus is an open application framework that enables cybersecurity developers to create optimized AI pipelines for filtering, processing and classifying large volumes of real-time data.

cuDNN

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The NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers.

Automatic Mixed Precision

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Deep Neural Network training has traditionally relied on IEEE single-precision format, however with mixed precision, you can train with half precision while maintaining the network accuracy achieved with single precision.

JetPack

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NVIDIA JetPack SDK is the most comprehensive solution for building end-to-end accelerated AI applications. JetPack SDK provides a full development environment for hardware-accelerated AI-at-the-edge development.

NVIDIA Collective Communications Library

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The NVIDIA Collective Communication Library (NCCL) implements multi-GPU and multi-node communication primitives optimized for NVIDIA GPUs and Networking. NCCL provides routines such as all-gather, all-reduce, broadcast, reduce, reduce-scatter as well as point-to-point send and receive that are optimized to achieve high bandwidth and low latency over PCIe and NVLink high-speed interconnects.

Browse by Resource Type

Detecting Financial Fraud Using GANs at Swedbank with Hopsworks and NVIDIA GPUs

Discover how Swedbank trains advanced deep learning models such as generative adversarial neural networks (GANs) using NVIDIA GPUs and Logical Clock’s Hopsworks as part of its fraud and anti-money laundering (AML) strategy.


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GPU-Accelerated Examples for Quantitative Analyst Tasks

Learn about an example to show how simple it is to accelerate the quant workflow in the GPU and visualize the data flow.


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Fast Fractional Differencing on GPUs Using Numba and RAPIDS

Fractional differencing is widely used today in the financial services industry for preparing training data for machine learning algorithms to generate signals for stock trading.


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Accelerated Python in Banking


RAPIDS is an open-source platform, incubated at NVIDIA, for GPU-accelerated data science. It’s transforming many areas of the financial services industry, including the performance record for a representative benchmark designed to evaluate platforms for backtesting trading strategies. Learn how financial institutions are leveraging the RAPIDS platform.


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Advancing Financial Services with Conversational AI

Natural Language Processing (NLP) is a critical part of building better chatbots and AI assistants. Among the numerous language models used in NLP-based applications, BERT has emerged as a leader due to its innovative use of machine learning, rapid iteration and ease of use. Learn How the BERT language model is used for NLP.


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Deep Learning in Asset Pricing

Stanford University uses deep neural networks to estimate asset pricing for individual stock returns, taking advantage of a vast amount of conditioning information while keeping a fully flexible form and accounting for time variations. Their key innovations include constructing the most informative test assets with an adversarial approach and extracting the states of the economy from many macroeconomic time series.


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Fundamentals of Accelerated Data Science with RAPIDS

You’ll learn how to:


  • Perform multiple analysis tasks on large datasets using RAPIDS
  • Use cuDF, Dask, and BlazingSQL to evaluate datasets
  • Utilize cuML algorithms to perform data analysis at massive scale

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Fundamentals of Accelerated Computing with CUDA Python

You’ll learn how to:


  • Use Numba to compile CUDA kernels from NumPy universal functions (ufuncs)
  • Use Numba to create and launch custom CUDA kernels
  • Apply key GPU memory management techniques

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Building Intelligent Recommender Systems

You’ll learn how to:


  • Build a content-based recommender system using the open-source cuDF library and Apache Arrow
  • Optimize performance for both training and inference using large, sparse datasets
  • Deploy a recommender model as a high-performance web service

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Accelerating Data Science Workflows with RAPIDS

You’ll learn how to:


  • Use cuDF to manipulate massive datasets directly on the GPU
  • Utilize a wide variety of GPU-accelerated machine learning algorithms including XGBoost and several other cuML algorithms to perform data analysis
  • Perform end to end analysis tasks utilizing several realistic data sets

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PROGRAMS FOR YOU

Developer Resources

The NVIDIA Developer Program provides the advanced tools and training needed to successfully build applications on all NVIDIA technology platforms. This includes access to hundreds of SDKs, a network of like-minded developers through our community forums, and more.

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Technical Training

NVIDIA Deep Learning Institute (DLI) offers hands-on training in AI, accelerated computing, and accelerated data science to solve real-world problems. Powered by GPUs in the cloud, training is available as self-paced, online courses or live, instructor-led workshops.

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Accelerate Your Startup

NVIDIA Inception—an acceleration platform for AI, data science, and HPC startups—supports over 7,000 startups worldwide with go-to-market support, expertise, and technology. Startups get access to training through the DLI, preferred pricing on hardware, and invitations to exclusive networking events.

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NVIDIA Financial Services News

Best Practices: Explainable AI Powered by Synthetic Data

Best Practices: Explainable AI Powered by Synthetic Data

Learn how financial institutions are using high-quality synthetic data to validate explainable AI models and comply with data privacy regulations.

Scaling AI for Financial Services with Full-Stack Solutions to Implementation Challenges

Scaling AI for Financial Services with Full-Stack Solutions to Implementation Challenges

To scale AI for financial services, companies must face several resource hurdles. The full-stack solution from NVIDIA and VMware helps you leverage the competitive advantages of AI.

Send Instant Business Payments with Photon Commerce’s Financial AI Platform  

Send Instant Business Payments with Photon Commerce’s Financial AI Platform  

Partnering with NVIDIA and the ICC, Photon Commerce is creating the world’s most intelligent financial AI platform for instant B2B payments, invoices, statements, and receipts.

Deep Learning vs Machine Learning Challenger Models for Default Risk with Explainability

Deep Learning vs Machine Learning Challenger Models for Default Risk with Explainability

This post details the credit default risk prediction with deep learning and machine learning models.


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