Developer Resources for Financial Services

NVIDIA technologies for use cases across capital markets, banking, payments, and fintech.

Starter Kits by Use Case

Detect Anomalies With Fraud Prevention

AI-enabled applications using deep learning techniques such as graph neural networks (GNNs) can reduce false positives in transaction fraud detection, enhance identity verification accuracy for know-your-customer (KYC) requirements, and make anti-money laundering (AML) efforts more effective, improving both the customer experience and your company’s financial health.

Enhance Customer Service With AI Virtual Assistants

AI agents in financial services redefine customer experiences by delivering more accurate, personalized, and sophisticated responses than traditional chatbot solutions. Support customers through secure, real-time responses by leveraging AI-driven assistants.

Extract Insights With Financial Document Processing

Intelligent document processing with generative AI lets financial institutions gather insights from unstructured data, enabling faster decision-making and reducing the risk of financial losses. Unlock highly accurate insights from massive volumes of financial data, such as loan records, external regulatory filings, transaction records, public market filings, and more.

Explore Tools and Technologies for Financial Services

NVIDIA HPC SDK

Optimize High-Performance Computing for Trading

Segments: Trading

The NVIDIA HPC SDK includes the proven compilers, libraries, and software tools essential for maximizing developer productivity and the performance and portability of HPC applications.

NVIDIA NeMo

Build, Customize, and Deploy Generative AI Models

Segments: Banking, Payments, Trading

NVIDIA NeMo™ is an end-to-end platform for developing custom generative AI—including large language models (LLMs) and speech AI—anywhere.

NVIDIA Dynamo

Distribute and Disaggregate Generative AI Serving

Segments: Banking, Payments, Trading

NVIDIA Dynamo is an open-source, low-latency inference framework for serving generative AI models in distributed environments. It scales inference workloads across large GPU fleets with optimized resource scheduling, memory management, and data transfer, and it supports all major AI inference backends.

NVIDIA RAPIDS

Accelerate Data Preparation

Segments: Banking, Payments, Trading

NVIDIA RAPIDS™ is an open-source suite of data science libraries that accelerates data processing. It comes with simple integration options for the most popular data science tools.

GNNs

Detect Anomalies for Fraud Prevention

Segments: Payments

Graph neural network (GNN) frameworks are easy-to-use Python packages that offer building blocks to build GNNs on top of existing deep learning frameworks. These can be used for a wide range of applications, such as enhancing accuracy for transaction fraud detection.

NVIDIA FLARE

Train Machine Learning Models with Privacy and Security

Segments: Banking, Payments

NVIDIA FLARE™ (Federated Learning Application Runtime Environment) is a domain-agnostic, open-source, and extensible SDK for federated learning.

Browse by Resource Type

Accelerating End-to-End Data Science Workflows

Learn how to build and execute end-to-end, GPU-accelerated data science workflows that let you quickly explore, iterate, and move your work into production. In this self-paced lab, you’ll learn how to use RAPIDS accelerated data science libraries to perform data analysis at scale with a wide variety of GPU-accelerated algorithms.

Generative AI Explained

Explore generative AI, which has recently taken the world by storm. Using neural networks to identify patterns and structures within existing data, it generates new content based on a variety of inputs. In this course, you’ll learn generative AI concepts, applications, and the challenges and opportunities of this exciting field.

Synthetic Data Generation for Training Computer Vision Models

Streamline synthetic data generation (SDG) using 3D assets into a single application—and modify the appearance and format of the data—with NVIDIA Omniverse Replicator. This lab highlights one of the ways deep learning tools and Omniverse can be used together to streamline deep learning workloads.

img-alt-text

Supercharging Fraud Detection in Financial Services With Graph Neural Networks

In this blog, we walk through how you can leverage the NVIDIA AI Blueprint for financial fraud detection and get started with model building and inference to detect payment transaction fraud.

img-alt-text

Streamline Trade Capture and Evaluation with Self-Correcting AI Workflows

Read this technical blog to learn how self-correcting LLMs can improve trade capture in capital markets.

img-alt-text

Transforming Financial Analysis With NVIDIA NIM

Read this technical blog to learn how to build an AI assistant to extract insights from earnings call transcripts using generative AI techniques like retrieval-augmented generation (RAG).

img-alt-text

GPU-Accelerate Algorithmic Trading Simulations by over 100x with Numba

Computational simulations of financial markets are an integral part of doing business in high-frequency trading. Read how Numba was used on NVIDIA H200 GPUs to obtain up to 114x performance improvement compared to CPU-only simulations.

A business manager uses NVIDIA Retail Shopping Advisor on the laptop

Accelerate Financial Services With Enterprise AI

Massive datasets. Perpetual market fluctuations. Customer inquiries. Intelligent technology can address critical challenges within the modern financial services industry. With NVIDIA’s AI solutions—for generative AI, LLMs, data analytics, and more—institutions can optimize trading, detect transaction fraud, and enhance customer experiences.