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TabbFORUM Report: The State of AI in the Capital Markets

Market Note

Financial markets practitioners are no strangers to automation and machine learning. In the 2010s, high-frequency trading algorithms changed how the buy-side and sell-side approach the capital markets by reducing the latency between trades, increasing alpha for early adopters.

Machine learning has only grown stronger over the last decade. With the introduction of large language models (LLMs), natural language processors (NLPs), and generative pre-training transformers (GPTs), the new age of artificial intelligence (AI) stands to reshape the capital markets once again.

Across the front, middle, and back offices, AI’s ability to process vast amounts of data in real-time is revolutionizing multi-asset trading strategies, automating compliance tasks, and helping to balance portfolios. From optimizing meetings with clients to speeding up the trade settlement process, the growing influence of AI across fixed income, equities, and commodities presents unique opportunities and challenges for firms in the capital markets.

This report explores how advancements in AI, including large language models and natural language processing, are revolutionizing every aspect of capital markets, from trading strategies to compliance and portfolio management including:

  • Streamlining Data in Fixed Income Markets
  • Natural Language Processing in Financial Markets
  • AI-Driven Multi-Asset Strategies
  • Personalizing Client Services
  • AI for Investment Research and Risk Management
  • Addressing AI Hallucinations
  • Balancing Build vs. Buy in AI Solutions
  • AI Interfaces
  • How AI Polices Itself
  • Regulatory Oversight for AI

Sumber Daya Terkait

01 November, 2024
BLOOR Research Opinion Article
This article from UK Analyst Bloor Research recognises the capabilities and advantages of InterSystems IRIS data platform as an "innovative and powerful data management platform" and it’s Smart Data Fabric capabilities offering a market differentiator.
23 October, 2024
Fact Sheet
Unified Data has the Power to Transform
17 October, 2024
TabbFORUM’s Market Structure Wave
In this edition of TabbFORUM’s Market Structure Wave video series, InterSystems Irene Galperin, Senior Advisor, Financial Services, discusses how firms in the capital markets have been investing and experimenting with AI, particularly most recently with the advent of ChatGPT. In this interview, conducted by TABB Group CEO Bruce Morris, Irene offers several use cases and explains that data is at the core of implementing AI, as data needs to be "high quality and consistent," essentially "AI-ready."
04 October, 2024
Product Fact Sheet
InterSystems Data Fabric Studio is an essential element of a modern data strategy required to enable growth, optimize business reporting, reduce risk, and support compliance for any firm in the financial services industry.
30 April, 2024
A Semantic Layer Summit Lightning Talk
Harris Associates leverages a smart data fabric architecture enriched with a semantic layer.
30 October, 2023
A Global Survey of 375 Asset Management Firms' Top Data Challenges and Initiatives
How Asset Management Organizations Are Investing in Data Management Download the eBook
12 October, 2023
A Bloor InContext Report
Innovation starts with an idea and a vision. It takes root through people accepting the need for change, but it relies on the availability of good quality, accessible, and timely data to deliver both the insights that identify opportunities for innovation and the evidence that innovation is producing the desired improvements.
06 October, 2023
Analytics
InterSystems proven technology is used today to replicate data from an operational production system to a “reporting node,” where it can be queried and analyzed without impacting the operational system.
22 August, 2023
Smart Data Fabric
As enterprise data grows in volume and complexity, solutions have evolved.
21 June, 2023
Asset Management
Asset management firms have been trying to solve the same data problem for decades: how do you aggregate all of your enterprise data, including from vendor applications in the front-, middle-, and back-office, along with third-party service provider data, publicly available data, and data from other sources?

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