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Amazon Bedrock: A Boon for the Financial Services Industry
Open Source For You
|December 2024
Amazon Bedrock is a fully managed service that provides access to foundation models from top AI providers, enabling organisations to build and scale generative AI applications. It is specifically designed to bring AI solutions to the financial sector. Let's explore all that it can do...
Amazon Bedrock is a cloud platform that provides a comprehensive set of foundation models (FMS). These are used to create API services and tools for building, deploying, and managing solutions in the financial services industry. The platform helps customers to leverage the scalability, security, reliability, and innovation of the AWS cloud, while addressing the specific requirements and challenges of the financial sector. It offers solutions for banking, financial services, securities, capital markets, and insurance use cases, such as payments and risk management.
The financial industry is undergoing a rapid and profound transformation, driven by changing customer expectations, regulatory pressures, competitive forces, and technological innovations. Customers are demanding more personalised, convenient, and secure financial services, accessible anytime and anywhere. Regulators are imposing stricter rules and standards for data protection, privacy, and transparency. Competitors, including new entrants and fintech startups, are challenging the traditional business models and offerings of incumbent financial institutions. Innovations, such as artificial intelligence, blockchain, cloud computing, and Big Data, are creating new possibilities and challenges for delivering value and enhancing efficiency in the financial sector.
To succeed in this dynamic and complex environment, financial institutions need to adopt a cloud-first strategy that enables them to innovate faster, scale on demand, reduce costs, and comply with regulations. However, moving to the cloud is not a simple task, especially for the financial industry, which has unique and stringent requirements and challenges, such as:
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