In search of clean data: Firms navigate data challenges as LLM adoption flourishes

In search of clean data: Firms navigate data challenges as LLM adoption flourishes

Large language models (LLMs), a form of artificial intelligence (AI) specialising in natural language processing, represent many opportunities for financial services firms to improve investment decisions and enhance risk management. These models are transforming the way they analyze data and identify trends, and are ultimately revolutionizing decision-making processes in capital markets.

This WatersTechnology rapid read report, commissioned by LSEG Data & Analytics, details the evolution of LLM implementation in financial services, and provides a comprehensive view of the challenges, concerns, objectives and experiences firms are encountering in their journeys with LLMs. 

Many in the industry are proactively planning to adopt these models, indicating a forward-looking stance toward leveraging generative AI capabilities. Privacy concerns and data control are key considerations, underscoring the industry’s commitment to safeguarding sensitive information. Although still in the early stages of implementation, the global interest and diverse applications of these models highlight the potential for innovation and addressing organisational difficulties. Despite challenges in sourcing clean text, users report a positive impact, signaling a promising future for LLM integration in financial operations.

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SaaS and the evolution of cloud-based data management

In this white paper, we provide an overview of the evolution of cloud-based technology in the data management space; we assess the benefits of the most commonly used deployment models; we set out our own vision for the future based on a software-as-a-service (SaaS) model; and we explain the journey we are on to deliver increased value for our clients, including the end business user.

SaaS and the evolution of cloud-based data management

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