Artificial intelligence may be the most talked-about force in finance right now, but behind the buzz lies a more complicated reality. In a recent article, Sebastian Reinhard of Caleo argues that large language models (LLMs) promise transformative gains in financial planning yet without structure, governance and domain expertise, they risk delivering more noise than value.
On 15 May Stevens Institute of Technology will host the AI and Structured Data Forum: Optimizing Performance, a one-day gathering co-produced by XBRL US and the Center for Research toward Advancing Financial Technologies (CRAFT).
This week, XBRL International’s Revathy Ramanan published the third article in our series Using LLMs to Analyse Narrative Disclosures, shifting the focus from patterns in reported numbers to the tone of management commentary.
This is the third entry in the blog series “Using LLMs to Analyse Narrative Disclosures.” In the previous analysis, we explored how liquidity risk disclosures revealed clear patterns and outliers, offering valuable signals through structured XBRL tagging and LLM-powered summarisation. In this part, we shift focus to sentiment analysis — examining how management frames its […]
The UK’s Financial Conduct Authority (FCA) has launched a wide-ranging review into how artificial intelligence could reshape retail financial services in the years ahead.
An interesting piece from Vincent Huck in this week’s Corporate Disclosures e-zine (registration required, but you’ll thank us later) asking questions that need answers.
This is the second entry in the series “Using LLMs to Analyse Narrative Disclosures.” In the previous piece, we saw how a simple prompt was sufficient to uncover the pattern of audit firms across 900 reports. Because the exact fact — the audit firm code (EDRPOU) — was explicitly tagged, it became easy and reliable to […]
This week sees the second entry in our blog series “Using LLMs to Analyse Narrative Disclosures.” This time, XBRL International’s Revathy Ramanan dives into how large language models (LLMs), combined with XBRL tagging, can reveal both common patterns and outliers in how companies discuss liquidity risk.
XBRL US recently announced that it has joined the Center for Research toward Advancing Financial Technologies (CRAFT) as an affiliate member. The collaboration aims to explore how structured, standardised data, particularly in XBRL format, can enhance AI and other fintech applications.
Narratives in disclosures are just as important as numbers—but much harder to analyze. Numbers can be easily fed into a model for comparison or trend analysis. Text, however, is less straightforward. Regulatory disclosures, especially sustainability reports, often contain large volumes of narrative information: policies, strategies, risk explanations, and qualitative context. Traditionally, text analytics has been […]
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