Intelligent Document Processing

Bring speed and efficiency to document processing with NVIDIA’s AI-powered services.


Generative AI


Financial Services

Business Goal

Return on Investment
Risk Mitigation


NVIDIA AI Enterprise

Automate and Accelerate Data Collection from Documents

In financial services, processing documents involves complex data, such as loan records, external regulatory filings, transaction records, public market filings, and more. The sheer volume of this financial data makes it impractical to digest and extract insights manually, and current automated solutions for unstructured data processing are inefficient.

Digitization and automation can streamline operations, reduce errors, and help organizations stay competitive in banking and insurance. In capital markets, AI algorithms can automate the processes of analyzing market trends, identifying patterns, and executing trades, which reduces time to action.

But individuals still face the time-intensive task of manually inputting data from paper-based documents. Through the integration of AI, users can seamlessly coordinate a diverse range of services and harness machine learning capabilities with intelligent document processing (IDP).

Identify and Extract Relevant Information Faster

Machine learning models can identify a wide variety of document types and extract relevant information from them. With generative AI, organizations can summarize structured and unstructured documents for research analysts, loan processors, and customer service agents.

For capital markets, the most powerful investment insights are hidden in unstructured text data from everyday sources such as news articles, blogs, and SEC filings. Generative AI lets traders provide deeper insights from unstructured data than traditional tabular data analysis, enabling faster decision-making and reducing the risk of financial losses.

Financial institutions are developing deep learning algorithms to automatically process documents digitized by their clients for various financial products. In retail banking for real estate, machine learning models accelerate title search, underwriting, and closing processes for home loan documents, helping complete home transactions much faster than before. With natural language understanding (NLU), banks can rapidly interpret the numerous requests and inquiries that occur during the due diligence process for loans and transactions.

Intelligent Document Process With the NVIDIA AI Platform

NVIDIA provides resources for financial institutions looking to use generative AI for IDP, such as constructing chatbots with retrieval-augmented generation (RAG) to automate loan processes or developing market insights in portfolio construction and trade execution.

Optimal Inference for Generative AI Workloads

NVIDIA NIM, part of NVIDIA AI Enterprise, is a set of easy-to-use inference microservices designed to accelerate the deployment of generative AI across your enterprise. This versatile runtime supports open community models and NVIDIA AI Foundation models from the NVIDIA API catalog, as well as custom AI models. NIM builds on NVIDIA Triton™ Inference Server, a powerful and scalable open-source platform for deploying AI models, and is optimized for large language model (LLM) inference on NVIDIA GPUs with NVIDIA® TensorRT™-LLM. NIM is engineered to facilitate seamless AI inferencing with high throughput and low latency, while preserving the accuracy of predictions. NIM lets organizations deploy AI applications anywhere with confidence, whether on premises or in the cloud. 

Accelerate Data Curation

NVIDIA NeMo™ Curator is a scalable, GPU-accelerated data-curation microservice that prepares high-quality datasets for pretraining and customizing generative AI models. With it, financial institutions can train and fine-tune LLMs on financial documents. NeMo Curator streamlines data-curation tasks such as data download, text extraction, reformatting, cleaning, quality filtering, and exact/fuzzy deduplication to help reduce the burden of combing through unstructured data sources. Document-level deduplication ensures that LLMs are trained on unique documents, which can greatly reduce pretraining costs.

Real-Time Information Retrieval

NeMo Retriever is a collection of CUDA-X™ microservices that enable semantic search of enterprise data to deliver highly accurate responses using retrieval augmentation. Developers can use these GPU-accelerated microservices for specific tasks, such as searching for relevant pieces of information within internal data to answer business questions, increasing accuracy and reducing hallucinations.

Getting Started with Generative AI for Document Processing

Financial institutions looking to deploy generative AI models for IDP can use the NVIDIA API catalog to quickly start building chatbots with RAG for market analysis and investment research.

Here are the four steps to get going:

  1. Start prototyping with state-of-the-art generative AI models: Leading foundation models include Meta Llama 3, Google Gemma 7B, Mixtral 8x7B, retrieval models, and NVIDIA’s Nemotron-3 8B family, optimized for the highest performance per cost.
  2. Customize foundation models: Tune and test the models with proprietary data using NVIDIA NeMo, an end-to-end platform for developing custom generative AI, anywhere.
  3. The cloud-first way to get the best of NVIDIA AI: NVIDIA DGX™ Cloud is an AI platform for enterprise developers, optimized for the demands of generative AI.
  4. Deploy and scale: Run applications anywhere, cloud, data center, or edge, by deploying with NVIDIA NIM, part of NVIDIA AI Enterprise—the production-grade, secure, end-to-end software platform that includes generative AI reference applications and enterprise support.

Quick Links

IDP is a technology that automates the process of manual data entry from paper-based documents or document images. IDP works by using optical character recognition (OCR) to scan and digitize paper-based documents. Data extracted using AI and machine learning is integrated with other digital business processes that automatically apply it to relevant systems and applications.

IDP offers numerous benefits, including increased efficiency, reduced errors, and cost savings. By automating manual data entry, IDP can significantly reduce the time and resources required for processing documents. It also eliminates the risk of human error, ensuring accurate data extraction.

Generative AI algorithms can analyze market trends and patterns in financial documents to assist with trading decisions. By analyzing market data, news articles, and other financial documents, generative AI algorithms can identify patterns, trends, and insights that can inform trading strategies. This can help traders make faster, more informed decisions and improve their trading performance.

Quick Links

Accelerate and Automate Your Document Processing

Generative AI-led applications are critical to automate document understanding across trading, insurance, and banking, offering an opportunity to improve customer satisfaction and reduce costs. Financial institutions can build and deploy generative AI models with NVIDIA AI Enterprise and develop custom chatbot applications to make better financial decisions.