The data readiness bottleneck
A recent survey by PwC, drawing on interviews with 50 Chief Information Officers in Germany, offers a glimpse of where AI adoption is getting stuck: the data.
A recent survey by PwC, drawing on interviews with 50 Chief Information Officers in Germany, offers a glimpse of where AI adoption is getting stuck: the data.
Everyone’s talking about generative AI, not least in finance, where CFOs are dreaming of AI assistants to whip up reports, streamline analysis processes, and perhaps even make the coffee. But before businesses get swept up in the AI gold rush, it’s important to take a moment to ask: what’s feeding the machine?
The European Central Bank (ECB) has launched its 2025 stress testing exercise, with a sharper focus on addressing data quality issues and overly optimistic projections from banks. Stress tests are critical for assessing resilience under adverse economic conditions, but past submissions have underestimated risks, prompting the ECB to tighten its approach.
On 20 January, the Financial Supervisory Service (FSS) in Korea introduced a new guide designed to elevate the accuracy and consistency of financial reporting using XBRL. Borrowing from a number of global best practices, this comprehensive resource aims to set a new benchmark for XBRL preparation in Korea.
Last week, John Schindler, Secretary General of the Financial Stability Board (FSB), addressed the Eurofi Financial Forum in Budapest, stressing the need for better data and regulatory coordination in the non-bank financial sector.
US Treasury Official Nellie Liang, Chair of the Financial Stability Board (FSB) Standing Committee on Assessment of Vulnerabilities, addressed the OECD-FSB Roundtable on Artificial Intelligence in Finance. Liang emphasised the transformative potential of AI in finance, however she also highlighted the need for robust data quality to manage the risks associated with AI deployment.
Or at least that’s the message from a recent Forbes article written by Kevin Campell, CEO at Syniti. In an era of digital transformation, organisations worldwide are recognising the pivotal role of data in driving innovation and achieving business success.
As our regular readers will know, we’ve been exploring some of the filing issues that crop up in comment letters to individual companies from the US Securities and Exchange Commission (SEC).
We continue to explore the US Securities and Exchange Commission’s (SEC) comment letter archive this week – catch up with parts one and two on our website. These letters, sent to individual companies regarding issues in their financial statements, provide an overview of the kinds of errors cropping up in Inline XBRL filings.
As we discussed last week, comment letters from the US Securities and Exchange Commission (SEC) can be a useful resource – not just for the individual companies they are addressed to, but for many of us using Inline XBRL both stateside and elsewhere.