AWS Machine Learning Blog
Category: Financial Services
Create a virtual stock technical analyst using Amazon Bedrock Agents
n this post, we create a virtual analyst that can answer natural language queries of stocks matching certain technical indicator criteria using Amazon Bedrock Agents.
Accelerate your financial statement analysis with Amazon Bedrock and generative AI
In this post, we demonstrate how to deploy a generative AI application that can accelerate your financial statement analysis on AWS.
Automate user on-boarding for financial services with a digital assistant powered by Amazon Bedrock
In this post, we present a solution that harnesses the power of generative AI to streamline the user onboarding process for financial services through a digital assistant.
Implement model-independent safety measures with Amazon Bedrock Guardrails
In this post, we discuss how you can use the ApplyGuardrail API in common generative AI architectures such as third-party or self-hosted large language models (LLMs), or in a self-managed Retrieval Augmented Generation (RAG) architecture.
Streamline workflow orchestration of a system of enterprise APIs using chaining with Amazon Bedrock Agents
In this post, we explore how chaining domain-specific agents using Amazon Bedrock Agents can transform a system of complex API interactions into streamlined, adaptive workflows, empowering your business to operate with agility and precision.
A review of purpose-built accelerators for financial services
In this post, we aim to provide business leaders with a non-technical overview of purpose-built accelerators (PBAs) and their role within the financial services industry (FSI).
Few-shot prompt engineering and fine-tuning for LLMs in Amazon Bedrock
This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Company earnings calls are crucial events that provide transparency into a company’s financial health and prospects. Earnings reports detail a firm’s financials over a specific period, including revenue, net income, earnings per share, balance sheet, and cash flow […]
Anthropic’s Claude 3.5 Sonnet ranks number 1 for business and finance in S&P AI Benchmarks by Kensho
Anthropic’s Claude 3.5 Sonnet currently ranks at the top of S&P AI Benchmarks by Kensho, which assesses large language models (LLMs) for finance and business. Kensho is the AI Innovation Hub for S&P Global. Using Amazon Bedrock, Kensho was able to quickly run Anthropic’s Claude 3.5 Sonnet through a challenging suite of business and financial […]
Automate derivative confirms processing using AWS AI services for the capital markets industry
In this post, we show how you can automate and intelligently process derivative confirms at scale using AWS AI services. The solution combines Amazon Textract, a fully managed ML service to effortlessly extract text, handwriting, and data from scanned documents, and AWS Serverless technologies, a suite of fully managed event-driven services for running code, managing data, and integrating applications, all without managing servers.
AI-powered assistants for investment research with multi-modal data: An application of Amazon Bedrock Agents
This post is a follow-up to Generative AI and multi-modal agents in AWS: The key to unlocking new value in financial markets. This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Financial analysts and research analysts in capital markets distill business insights from financial and non-financial data, […]