A couple of weeks ago we commented unfavourably on the use of PDF versions of SEC filings as inputs to Large Language Models (LLMs). We are much more interested in how these tools can be leveraged to examine structured data.
A couple of weeks ago, in the XBRL International newsletter, we commented unfavourably on the use of PDF versions of SEC filings as inputs to Large Language Models (LLMs). We are much more interested in how these tools can be leveraged to examine structured data, such as the Inline XBRL formatted structured filings provided to […]
One item in particular over the holiday break caught our attention. Research by Patronus AI highlighted apparent challenges faced by large language models (LLMs), such as OpenAI’s GPT-4, in analysing financial data contained in US Securities and Exchange Commission (SEC) filings.
Continuing the theme, the Financial Reporting Council (FRC) recently released a research report delving into the increased uptake of Artificial Intelligence (AI) and Machine Learning (ML) in the UK actuarial landscape.
The European Central Bank (ECB) is starting to use artificial intelligence (AI) to enhance its operations. As AI continues to evolve, it offers interesting potential for a range of central banking tasks, including data analysis, risk management, banking supervision, and monetary policy analysis.
It’s been said that artificial intelligence – AI – replaces the need for structured data, but we believe that idea could not be further from the truth. It is certainly possible to skip digital tagging and use AI to get answers out of unstructured data, but they are often not very good answers.
Deep learning models, often the bedrock of machine learning and artificial intelligence, are playing an increasingly large role in financial analysis. These models, while powerful, lack transparency – often known as ‘black boxes’ due to the opacity of their algorithms.
US Securities and Exchange Commission (SEC) Commissioner Mark T. Uyeda recently addressed the 2023 NASAA Fall Annual Meeting, emphasising the role of innovation and technology in modernising investor protection.
In the era of artificial intelligence (AI), there is a growing interest in the use of AI models like ChatGPT to enhance financial reporting processes. However, it is crucial to recognise the importance of structured, machine-readable data in training AI models effectively.
At the recent Innovate Finance Global Summit, Jessica Rusu, Chief Data, Information, and Intelligence Officer of the UK’s Financial Conduct Authority (FCA), delivered a speech highlighting the importance of innovation, AI, and data-driven regulation in the future of finance.
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