Blockchain

Institutional Traders Shifting Attention from Blockchain to AI

More than half of the institutional traders surveyed by global financial services giant JP Morgan said that artificial intelligence and machine learning will be the most influential technology in shaping the future of trading over the next three years—cited four times more often than blockchain and distributed ledger technology.

JP Morgan’s e-Trading Edit report is now in its seventh year, the latest report drawn from a January survey of 835 institutional traders in 60 global markets. The annual assessment of trader sentiment spans several asset classes and is intended to reveal « upcoming trends and the most hotly debated topics. »

The tumultuous bear market in crypto—coupled with the recent consumer and commercial hype over accessible AI technology like ChatGPT—seems to have shifted the outlook of financial industry professionals. Last year, blockchain and distributed ledger technology tied for second with AI and machine learning with 25 percent of respondents declaring them key to the future. Mobile trading applications came in first, with 29 percent.

Now, AI dwarfs every other major category of technology, its 53% citation rate far and away ahead of API integration (14%) and blockchain (12%). The top 2022 technology, mobile apps, fell to 7%, along with quantum computing and natural language processing.

Tackling crypto specifically, JP Morgan found that 72% of traders « have no plans to trade crypto [or] digital coins, » with 14% predicting they plan to trade within five years.

Even so, respondents clearly felt that other players were bullish on the space.

« Crypto and digital coins, commodities, and credit are predicted to have the biggest increases in electronic trading volumes over the next year, » the report notes, with participants predicting 64 percent of their activity will be in the crypto space by 2024.

Source 

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

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