Emily Prince
Amid the heightened attention surrounding generative AI and Large Language Models across financial markets, how is LSEG building on existing artificial intelligence capabilities to increase efficiency and enhance productivity?
- Using AI and NL to enhance productivity
- Leveraging the power of LSEG's extensive & sophisticated multi-asset analytics and pricing libraries
- Enabling data-driven decisions & greater optimisation of investment management strategies
AI technology is becoming a central part of our lives. With vast amounts of digitised data available, the need for accessing and finding relevant information through responsible AI frameworks has intensified. AI agents are expected to be fundamental to increasing efficiencies with the ability to process data much faster than humans and making analysis quicker and more accurate. This also makes acting on decisions much easier.
By leveraging the power of data and driving the next wave of digital transformation, generative AI, is largely viewed as the technology that is revolutionising how people can access information and how customers can create unique, actionable insights.
Shifting momentum
Generative AI is creating new possibilities for the industry. When utilised with care for data provenance and tracking it brings an opportunity to interact with technology differently and has the potential to perform increasingly complex tasks. For financial workflows these are powerful capabilities.
An area of increased interest for financial services is modelling and analytics bringing the ability to build views with proprietary and third-party content around modelling and analytics - from model creation to model consumption with the tooling required to execute at scale. This type of deployment of AI is expected to drive competitive advantages for businesses, by improving efficiency through productivity enhancement, as well as by enhancing the quality of services and products offered to customers.
It is here where we see the real business value in the form of a new wave of productivity.
Reshaping the data analytics experience - making better and faster decisions
As we continue to invest and accelerate our adoption of AI, Machine Learning (ML), and Natural Language Processing (NLP) technologies across the investment lifecycle, how can we optimise the organisation of assets to increase efficiency, transparency and scalability and enable a differentiated and seamless experience for customers?
With timing key to capitalising on market movements, producing code required to price sophisticated cross asset instruments is capable of being done in seconds which will not only enhance productivity with the use of AI but transform for traditional workflows. This will likely see improved efficiency gains and simplicity and flexibility for the user via Microsoft Visual Studio Code powered by LSEG Analytics.
Leveraging the power of LSEG's extensive multi-asset analytics and pricing libraries can offer a view of financial markets through sophisticated market analytics and a set of parameters that customers can use to set their own pricing strategy.
Bringing together highly fragmented workflows through a seamless integration of AI into financial analytic roadmaps and a consistent, normalised set of APIs removes the need for multiple plug-ins. This empowers quants, fin coders, traders, and user-centric copilots thus enabling data-driven decisions and greater optimisation of investment management strategies.
Working smarter with AI
AI is poised to unlock business models and transform industries, but Generative AI is only as good as the quality of the data it is trained on. It’s important to consider the risks associated with AI in financial services around the concept of AI hallucinations, which is mitigated by pinpoint accuracy. A strong commitment to data accuracy and auditability is fundamental.
We are bringing LSEG Data Trust and working with partners like Microsoft to apply Generative AI to transform the way customers gain insights from data and make their own workflows more efficient. LLM’s have been advancing and iterating to make it easier for customers to do more, create and share timely, actionable insights.
With transparency, regulation, and human oversight, we can work towards a safe and beneficial journey into the world of AI.
LSEG, in partnership with Microsoft, are at the cutting edge of a mission to empower financial services communities to substantially improve productivity, through simplified and reimagined digital workflows, powered by Generative AI.
At LSEG, we are working with partners like Microsoft to apply Generative AI to transform the way customers gain insights from data and make their own workflows more efficient.
Through our 10-year strategic partnership with Microsoft, we are:
- Transforming the way customers gain insights from data and make their workflows more efficient.
- Redefining data excellence to equip the industry with the right tools for the next generation of financial professionals.
- Empowering our customers to focus on creating unique insights bringing the transformational power of Generative AI
- Building an open, intelligent and resilient ecosystem that will utilise Microsoft’s scalable cloud infrastructure.
This will enable our customers to transact easily and securely using our trusted content and analytics, their own data, and third-party data to generate insights for their clients and innovate across their own products.
Legal Disclaimer
Republication or redistribution of LSE Group content is prohibited without our prior written consent.
The content of this publication is for informational purposes only and has no legal effect, does not form part of any contract, does not, and does not seek to constitute advice of any nature and no reliance should be placed upon statements contained herein. Whilst reasonable efforts have been taken to ensure that the contents of this publication are accurate and reliable, LSE Group does not guarantee that this document is free from errors or omissions; therefore, you may not rely upon the content of this document under any circumstances and you should seek your own independent legal, investment, tax and other advice. Neither We nor our affiliates shall be liable for any errors, inaccuracies or delays in the publication or any other content, or for any actions taken by you in reliance thereon.
Copyright © 2023 London Stock Exchange Group. All rights reserved.
The content of this publication is provided by London Stock Exchange Group plc, its applicable group undertakings and/or its affiliates or licensors (the “LSE Group” or “We”) exclusively.
Neither We nor our affiliates guarantee the accuracy of or endorse the views or opinions given by any third party content provider, advertiser, sponsor or other user. We may link to, reference, or promote websites, applications and/or services from third parties. You agree that We are not responsible for, and do not control such non-LSE Group websites, applications or services.
The content of this publication is for informational purposes only. All information and data contained in this publication is obtained by LSE Group from sources believed by it to be accurate and reliable. Because of the possibility of human and mechanical error as well as other factors, however, such information and data are provided "as is" without warranty of any kind. You understand and agree that this publication does not, and does not seek to, constitute advice of any nature. You may not rely upon the content of this document under any circumstances and should seek your own independent legal, tax or investment advice or opinion regarding the suitability, value or profitability of any particular security, portfolio or investment strategy. Neither We nor our affiliates shall be liable for any errors, inaccuracies or delays in the publication or any other content, or for any actions taken by you in reliance thereon. You expressly agree that your use of the publication and its content is at your sole risk.
To the fullest extent permitted by applicable law, LSE Group, expressly disclaims any representation or warranties, express or implied, including, without limitation, any representations or warranties of performance, merchantability, fitness for a particular purpose, accuracy, completeness, reliability and non-infringement. LSE Group, its subsidiaries, its affiliates and their respective shareholders, directors, officers employees, agents, advertisers, content providers and licensors (collectively referred to as the “LSE Group Parties”) disclaim all responsibility for any loss, liability or damage of any kind resulting from or related to access, use or the unavailability of the publication (or any part of it); and none of the LSE Group Parties will be liable (jointly or severally) to you for any direct, indirect, consequential, special, incidental, punitive or exemplary damages, howsoever arising, even if any member of the LSE Group Parties are advised in advance of the possibility of such damages or could have foreseen any such damages arising or resulting from the use of, or inability to use, the information contained in the publication. For the avoidance of doubt, the LSE Group Parties shall have no liability for any losses, claims, demands, actions, proceedings, damages, costs or expenses arising out of, or in any way connected with, the information contained in this document.
LSE Group is the owner of various intellectual property rights ("IPR”), including but not limited to, numerous trademarks that are used to identify, advertise, and promote LSE Group products, services and activities. Nothing contained herein should be construed as granting any licence or right to use any of the trademarks or any other LSE Group IPR for any purpose whatsoever without the written permission or applicable licence terms.
