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Enhancing Regulatory Compliance through Logical Data Management

Data Virtualization

Reading Time: 2 minutes Regulatory compliance is a critical consideration for businesses, especially in heavily regulated sectors such as financial services and pharmaceuticals, which require companies to frequently submit detailed reports about their operations to government agencies.

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TransUnion transforms its business model with IT

CIO Business Intelligence

billion acquisition of data and analytics company Neustar in 2021, TransUnion has expanded into other services such as marketing, fraud detection and prevention, and robust analytical services. At the core of its strategy is the mountain of data that TransUnion has acquired — along with more than 25 companies — over decades.

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Examples of IBM assisting insurance companies in implementing generative AI-based solutions  

IBM Big Data Hub

This approach can accelerate speed-to-market by providing enhanced capabilities for developing innovative products and services, facilitating business growth and improving the overall customer experience in their interactions with the company. Below, we provide summaries of some of our current generative AI implementation initiatives.

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Forging a framework for central bank digital currencies and tokenization of other financial assets

IBM Big Data Hub

As a result, new forms of centrally managed digital currencies are emerging alongside cryptocurrencies like Bitcoin, the notorious volatility of which has challenged their acceptance worldwide. Regulatory compliance and efficient dispute resolution capabilities require transparency, auditability, and non-repudiation.

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How Do Banks and Other Financial Institutions Benefit from AI

Smart Data Collective

Compliance and Fraud Detection. It analyzes huge amounts of data to identify suspicious transactions. AI can easily comb through billions of transactions and flag any that meet specific criteria. AI can’t entirely replace human specialists—but it can enhance their productivity. Investment Valuation. Reduced Costs.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

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Data Lineage XD: Taking Data Lineage Solutions to the Next Level

Octopai

Data lineage is also a tool. Different business intelligence jobs require different kinds of data lineage. The type of lineage that a BI Developer would use to perform root cause analysis is not the same type of lineage that the Data Engineer would use to do data flow visualization inside of an ETL process.