Category: Financial Services

This is the first post in a two-part series exploring how AWS-native services, including Amazon Bedrock AgentCore, Amazon Neptune Analytics, Strands Agents, and a serverless data pipeline, power three transformative advisor capabilities:

This blog explains what the AI- Driven Development Lifecycle is and why it can help you drive faster application development using AI in a well governed and controlled way.

Learn how AI has changed the economics of core banking modernization. Services like AWS Transform for mainframe and development tools such as Kiro now enable banks to compress multi-year migration programs into months , reducing the manual effort necessary, project risk, and overall transformation costs associated with modernizing the mainframe platform.

This post provides architectural guidance only and does not constitute legal or compliance advice. Consult your compliance and legal teams for your specific regulatory obligations.

This article focuses on the Amazon Managed Streaming for Apache Kafka (Amazon MSK) and Amazon Elastic Kubernetes Service (Amazon EKS) integration pattern that enable elastic, cost-efficient processing at scale.

This post shows you how to build an AI-powered investment research platform using the Strands agents -multi-agent framework deployed on Amazon Bedrock AgentCore.

In this post, you learn how the Options Clearing Corporation (OCC) partnered with AWS to solve these challenges by automating governance across a multi-account environment with AWS Control Tower and then validating infrastructure resilience through a structured AWS Fault Injection Service (AWS FIS) program.

This blog post shows you how to design an architecture that receives CME Group MDP multicast data on AWS, then deploy and configure the solution with setup steps.

In this post, we introduce four connectivity patterns that represent different approaches to integrating AWS-based workloads with FMIs.

Learn how to transform collections operations for banks and fintechs with AI and ML on AWS The Business Challenge Financial institutions face mounting pressure in collections operations. Traditional debt collection operates on a simple playbook: aggressive phone calls, generic messaging, and rule-based workflows. Yet customers have unique capacity to pay (income, assets, competing obligations), willingness […]