The Bank for International Settlements’ Innovation Hub (BISIH) has a new work programme for 2020/21, its second full year, aiming to foster international collaboration among central banks on innovative financial technology.
How do you spot financial reporting errors or attempted fraud before they grow into problems? And – when serving a population of over 1.3 billion people – how can you both boost data quality and make the reporting and review process as efficient as possible? For the Institute of Chartered Accountants of India (ICAI), the […]
Touted as one of the big innovations set to shakeup the coming decades, artificial intelligence (AI) and machine learning (ML) are playing an increasingly central role in financial reporting and analysis. With the age of big data meaning the volume of data sets is growing ever larger, it helps to have a computer aid with the analysis.
How do reporting firms talk when they know that the machines are listening? A new working paper from the National Bureau of Economic Research (NBER) is the first of its kind to take a look at how increasing machine and AI readership is altering the way companies write their financial reports.
Shenzhen, China’s southern metropolis, is named after the rice paddy drains, or ‘zhen’, that once stretched across the landscape. Today, where mere decades ago sat a small fishing village, Shenzhen is a city of over 11 million inhabitants, known as China’s answer to Silicon Valley.
What do your mortgage, your car, and maybe even your fridge have in common? They are all either already or could soon be reliant on AI and machine-learning (ML) algorithms.
Technology is changing the world of audit. From the systems auditors rely on to improve the accuracy of their audits, to the data (soon to include, under ESEF, XBRL tagging) that requires review, tomorrows’ auditors must know how to work digitally.
In a recent speech Benoît Cœuré, Head of the Bank for International Settlements (BIS) Innovation Hub, asked the listener to imagine a world where regulators have access to big data sets of high granularity, diversity, and frequency.
AI and machine learning (ML) are playing an ever-growing role in financial markets around the world – and while these new technologies can reduce costs and increase speed for firms and investors, they also come with an element of risk.
Amongst several fascinating presentations at the Eurofiling Innovation Day this week was an interesting demonstration on how XBRL reports can be used as the basis of explainable AI for bankruptcy prediction.
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