Remove APIs Remove Banking Remove Big data
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Transforming credit decisions using generative AI with Rich Data Co and AWS

AWS Machine Learning

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. They provide access to external data and APIs or enable specific actions and computation.

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Reducing hallucinations in LLM agents with a verified semantic cache using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Similar to how a customer service team maintains a bank of carefully crafted answers to frequently asked questions (FAQs), our solution first checks if a users question matches curated and verified responses before letting the LLM generate a new answer. User submits a question When is re:Invent happening this year?,

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Capgemini Releases the World Retail Banking Report 2016: Customer Experience

Natalie Petouhof

Tweet Capgemini and Efma today released the 2016 World Retail Banking Report (WRBR). The information in this report will help banks to: Assess current levels of customer experience. Retail banks have been eyeing the steady advance of fintech competitors for some time now. Determine the impact of improved customer experience.

Banking 40
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A review of purpose-built accelerators for financial services

AWS Machine Learning

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously.

Benchmark 105
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Governing the ML lifecycle at scale: Centralized observability with Amazon SageMaker and Amazon CloudWatch

AWS Machine Learning

AWS CloudTrail is also essential for maintaining security and compliance in your AWS environment by providing a comprehensive log of all API calls and actions taken across your AWS account, enabling you to track changes, monitor user activities, and detect suspicious behavior. Enable CloudWatch cross-account observability.

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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

Their aim is to feed data into a centralized feature store, establishing it as the undisputed reference point. In the context of banking, they might deduce statistical insights from account balances, identifying trends and flow patterns. ML engineers refine these foundational features, tailoring them for mature ML workflows.

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MLOps foundation roadmap for enterprises with Amazon SageMaker

AWS Machine Learning

This might be a triggering mechanism via Amazon EventBridge , Amazon API Gateway , AWS Lambda functions, or SageMaker Pipelines. In addition to the model endpoint, the CI/CD also tests the triggering infrastructure, such as EventBridge, Lambda functions, or API Gateway. Data lake and MLOps integration.