Financial Services

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Responsible AI for the payments industry – Part 1

The payments industry stands at the forefront of digital transformation, with artificial intelligence (AI) rapidly becoming a cornerstone technology that powers a variety of solutions, from fraud detection to customer service. According to the following Number Analytics report, digital payment transactions are projected to exceed $15 trillion globally by 2027. Generative AI has expanded the […]

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Responsible AI for the payments industry – Part 2

In Part 1 of our series, we explored the foundational concepts of responsible AI in the payments industry. In this post, we discuss the practical implementation of responsible AI frameworks. The need for responsible AI The implementation of responsible AI is not passive, but a dynamic process of reimagining how technology can serve a customer’s

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Accelerating AI innovation: Scale MCP servers for enterprise workloads with Amazon Bedrock

Generative AI has been moving at a rapid pace, with new tools, offerings, and models released frequently. According to Gartner, agentic AI is one of the top technology trends of 2025, and organizations are performing prototypes on how to use agents in their enterprise environment. Agents depend on tools, and each tool might have its

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NewDay builds A Generative AI based Customer service Agent Assist with over 90% accuracy

This post is co-written with Sergio Zavota and Amy Perring from NewDay. NewDay has a clear and defining purpose: to help people move forward with credit. NewDay provides around 4 million customers access to credit responsibly and delivers exceptional customer experiences, powered by their in-house technology system. NewDay’s contact center handles 2.5 million calls annually,

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Part 3: Building an AI-powered assistant for investment research with multi-agent collaboration in Amazon Bedrock and Amazon Bedrock Data Automation

In the financial services industry, analysts need to switch between structured data (such as time-series pricing information), unstructured text (such as SEC filings and analyst reports), and audio/visual content (earnings calls and presentations). Each format requires different analytical approaches and specialized tools, creating workflow inefficiencies. Add on top of this the intense time pressure resulting

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Create a virtual stock technical analyst using Amazon Bedrock Agents

Stock technical analysis questions can be as unique as the individual stock analyst themselves. Queries often have multiple technical indicators like Simple Moving Average (SMA), Exponential Moving Average (EMA), Relative Strength Index (RSI), and others. Answering these varied questions would mean writing complex business logic to unpack the query into parts and fetching the necessary

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