AWS Machine Learning Blog
Category: Financial Services
Transforming credit decisions using generative AI with Rich Data Co and AWS
The mission of Rich Data Co (RDC) is to broaden access to sustainable credit globally. Its software-as-a-service (SaaS) solution empowers leading banks and lenders with deep customer insights and AI-driven decision-making capabilities. In this post, we discuss how RDC uses generative AI on Amazon Bedrock to build these assistants and accelerate its overall mission of democratizing access to sustainable credit.
How Travelers Insurance classified emails with Amazon Bedrock and prompt engineering
In this post, we discuss how FMs can reliably automate the classification of insurance service emails through prompt engineering. When formulating the problem as a classification task, an FM can perform well enough for production environments, while maintaining extensibility into other tasks and getting up and running quickly. All experiments were conducted using Anthropic’s Claude models on Amazon Bedrock.
London Stock Exchange Group uses Amazon Q Business to enhance post-trade client services
In this blog post, we explore a client services agent assistant application developed by the London Stock Exchange Group (LSEG) using Amazon Q Business. We will discuss how Amazon Q Business saved time in generating answers, including summarizing documents, retrieving answers to complex Member enquiries, and combining information from different data sources (while providing in-text citations to the data sources used for each answer).
How Clearwater Analytics is revolutionizing investment management with generative AI and Amazon SageMaker JumpStart
In this post, we explore Clearwater Analytics’ foray into generative AI, how they’ve architected their solution with Amazon SageMaker, and dive deep into how Clearwater Analytics is using LLMs to take advantage of more than 18 years of experience within the investment management domain while optimizing model cost and performance.
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).