The financial services industry is undergoing a profound transformation, driven by the rapid advancements in artificial intelligence (AI) technology. A staggering 91% of financial services companies are either exploring or already implementing AI solutions to drive innovation, improve operational efficiency, and elevate customer experiences. This article delves into the cutting-edge AI applications that are reshaping the industry, showcasing how leading organizations are harnessing the power of NVIDIA's NIM microservices and accelerated computing to revolutionize their operations.

Empowering Financial Institutions to Thrive in the AI Era

Ntropy: Bringing Order to Unstructured Financial Data

New York-based Ntropy is tackling the challenge of unstructured financial data, which has traditionally been a significant obstacle for financial services applications. The company's transaction enrichment API standardizes data from diverse sources and geographies, acting as a common language that enables financial services applications to understand any transaction with human-like accuracy in milliseconds, at a fraction of the cost of traditional methods. Leveraging the Llama 3 NVIDIA NIM microservice and NVIDIA Triton Inference Server running on NVIDIA H100 Tensor Core GPUs, Ntropy has achieved up to 20x better utilization and throughput for its large language models (LLMs) compared to running the native models. This technology is already being used by leading procure-to-pay software platform provider Airbase to boost transaction authorization processes, and Ntropy will showcase how its API can be used to enhance fraud detection and streamline loan disbursement and decision-making at the upcoming Money20/20 conference.

Contextual AI: Advancing Retrieval-Augmented Generation for Financial Services

Contextual AI, a Mountain View-based company, offers a production-grade AI platform powered by retrieval-augmented generation (RAG) that is ideally suited for building enterprise AI applications in knowledge-intensive financial services use cases. The Contextual AI RAG 2.0 platform integrates the entire RAG pipeline, including extraction, retrieval, reranking, and generation, into a single optimized system that can be deployed in minutes and further tuned and specialized based on customer needs. This approach delivers much greater accuracy in context-dependent tasks, as demonstrated by HSBC's plans to use Contextual AI to provide research insights and process guidance support by retrieving and synthesizing relevant market outlooks, financial news, and operational documents. Contextual AI leverages NVIDIA Triton Inference Server and the open-source NVIDIA TensorRT-LLM library to accelerate and optimize LLM inference performance.

NayaOne: Fostering Financial Services Innovation through a Digital Sandbox

London-based NayaOne offers an AI sandbox that allows financial institutions to securely test and validate AI applications prior to commercial deployment. Its technology platform enables the creation of synthetic data and provides access to a marketplace of hundreds of fintechs, allowing customers to benchmark applications for fairness, transparency, accuracy, and other compliance measures, ensuring top performance and successful integration. Using NVIDIA NIM microservices, NayaOne's AI Sandbox lets customers explore and experiment with optimized AI models, taking them to deployment more easily. With NVIDIA accelerated computing, NayaOne achieves up to 10x faster processing for the large datasets used in its fraud detection models, at up to 40% lower infrastructure costs compared to running extensive CPU-based models. The company will showcase its digital sandbox at the NVIDIA AI Pavilion at Money20/20.

Securiti: Empowering Financial Planning with AI Copilot

Securiti, a Silicon Valley-based startup, is leveraging the power of NVIDIA NIM to build an AI-powered copilot for financial services. The company's highly flexible Data+AI platform enables the development of safe, end-to-end enterprise AI systems, including generative AI applications such as the financial planning assistant. The copilot chatbot accesses diverse financial data while adhering to privacy and entitlement policies, providing context-aware responses to users' finance-related questions. By using the Llama 3 70B-Instruct NIM microservice, Securiti has optimized the performance of the LLM, ensuring the safe use of data. The company will demonstrate its generative AI solution at Money20/20, showcasing how it can help banks overcome the challenge of providing personalized financial advice at scale while maintaining data security, privacy, and compliance with regulations.