# Source: https://developer.nvidia.com/industries/financial-services.md

1. [Industries](/industries/overview)
2. 
Financial Services

# Developer Resources for Financial Services

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

Use Cases:

- 
Fraud detection
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Financial crime (AML/KYC)
- 
Customer service
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Algorithmic trading
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Intelligent document processing

### Starter Kits by Use Case

### Detect Anomalies With Fraud Prevention  

AI-enabled applications using deep learning techniques such as [graph neural networks](https://blogs.nvidia.com/blog/what-are-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.

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[Learn About the Use Case](https://www.nvidia.com/en-us/use-cases/ai-for-fraud-detection/)

- 

[Explore the NVIDIA AI Blueprint](https://build.nvidia.com/nvidia/financial-fraud-detection)

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[View Self-Paced Course](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+C-TC-01+V1)

### Scale Real-Time Decisions With Accelerated Portfolio Optimization

Traditional CPU-based workflows for portfolio optimization are slow, limited in scale, and unable to support real-time analysis. With AI acceleration, financial firms can model advanced risk measures, process large-scale portfolios in real time, and improve operational efficiency, enabling faster, more informed investment decisions.

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[Read the Technical Blog](https://developer.nvidia.com/blog/accelerating-real-time-financial-decisions-with-quantitative-portfolio-optimization/)

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[Explore the AI Developer Example](https://build.nvidia.com/nvidia/quantitative-portfolio-optimization)

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[View Self-Paced Course](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-DS-09+V1)

### Accelerate Feature Engineering From Unstructured Data

Financial institutions consume massive volumes of unstructured data in their alpha research, feature generation, and strategy creation processes. By combining real-world financial data streams (news, filings, calls) with automated fine-tuning and evaluation, AI accelerates signal backtesting and the time from research to actionable models.

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[Read the Technical Blog](https://developer.nvidia.com/blog/build-efficient-financial-data-workflows-with-ai-model-distillation)

- 

[Explore the AI Developer Example](http://build.nvidia.com/nvidia/ai-model-distillation-for-financial-data)

### 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.

[Get Started With the HPC SDK](/hpc-sdk)

**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.

[Get Started With NeMo](https://www.nvidia.com/en-us/ai-data-science/products/nemo/)

**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.

[Get Started With NVIDIA Dynamo](/triton-inference-server)

**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.

[Get Started With RAPIDS](/rapids)[Try the RAPIDS Accelerator for Apache Spark](https://docs.nvidia.com/spark-rapids/index.html)

**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.

[Get Started With GNNs](/gnn-frameworks#gnn-frameworks)

**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.

[Get Started With FLARE](/flare)

## Browse by Resource Type

GTC Sessions

Webinars

Blogs

[View All](https://www.nvidia.com/en-us/on-demand/playlist/playList-e332507f-4ab8-46d8-8827-756cd25aba13/ &quot;View All&quot;)

### 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.

[Enroll Now](https://courses.nvidia.com/courses/course-v1:DLI+S-DS-01+V1/)

### 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.

[Enroll Now](https://courses.nvidia.com/courses/course-v1:DLI+S-FX-07+V1/)

### 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.

[Enroll Now](https://courses.nvidia.com/courses/course-v1:DLI+S-OV-10+V1/)

[View All Courses](https://www.nvidia.com/en-us/training/ &quot;Download Workflows&quot;)

 

![An analyst reviews real-time market data and financial portfolio graphs on monitors](https://developer.download.nvidia.com/images/fsi-visual-1920x1080(1).jpg)

### Accelerating Real-Time Financial Decisions with Quantitative Portfolio Optimization  

Learn how the Quantitative Portfolio Optimization developer example accelerates strategy testing and time to decision in financial services.

[Read Blog](https://developer.nvidia.com/blog/accelerating-real-time-financial-decisions-with-quantitative-portfolio-optimization/)

![Efficient Financial Data Workflows with AI Model Distillation](https://developer.download.nvidia.com/images/financial-data-workflows-1920x1080.jpg)

### Build Efficient Financial Data Workflows With AI Model Distillation  

Learn how the AI Model Distillation for Financial Data developer example enables feature engineering and faster backtesting for research in capital markets.

[Read Blog](https://developer.nvidia.com/blog/build-efficient-financial-data-workflows-with-ai-model-distillation)

![Fraud Detection in Financial Services with Graph Neural Networks](https://developer.download.nvidia.com/images/ai-workflow-fraud-1920x1080.jpg)

### Supercharging Fraud Detection in Financial Services With Graph Neural Networks  

Learn how you can leverage the NVIDIA AI Blueprint for financial fraud detection to get started with model building and inference to detect payment transaction fraud.

[Read Blog](https://resources.nvidia.com/en-us-financial-services-industry/supercharging-fraud-detection-in-financial-services-with-graph-neural-networks)

![Algorithmic Trading Simulations](https://developer.download.nvidia.com/images/algorithmic-trading-simulations-1920x1080.jpg)

### GPU-Accelerate Algorithmic Trading Simulations by Over 100x With Numba  

Read how Numba was used on NVIDIA H200 Tensor Core GPUs to boost the performance of computational simulations of financial markets by up to 114x, compared to CPU-only approaches.

[Read Blog](https://resources.nvidia.com/en-us-financial-services-industry/gpu-accelerate-algorithmic)

![](https://developer.download.nvidia.com/images/industry/financial-service-industry.jpg)
_Figure caption_

## 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.

[Learn About AI for Financial Services](https://www.nvidia.com/en-us/industries/finance/)