When LSEG (London Stock Exchange Group) and Microsoft announced our strategic partnership in December 2022, our shared goal was to create new value for LSEG customers by innovating next-generation data, analytics and workflow experiences. Along the way, we have sought to reshape the the future of global finance through joint innovation.
Microsoft Cloud for Financial Services
Unlock business value and deepen customer relationships in the AI era
Today, 18 months into a 10-year partnership, we are seeing incredible progress in realizing this shared vision, with generative AI playing a central role.
As Matthew Kerner, corporate vice president of Microsoft Cloud for Industry, noticed during the Sibos 2023 conferencethe partnership will ultimately evolve the customer experience at scale across global financial markets to provide advanced, easily accessible financial data and actionable insights through optimized workflows.
In my previous blog post, I have reviewed a set of principles that I recommend for successful adoption of AI in financial services. Here, I’d like to share three key lessons from our work with LSEG that are relevant to other financial services organizations, particularly on how to determine a good solution, strategy and direction for financial services innovations. AI.
Generative AI: the next phase of digital transformation
On the day the LSEG-Microsoft partnership was announced, barely two weeks had passed since OpenAI’s unveiling of ChatGPT. Generative AI has yet to capture the world’s imagination, although it will soon. Although some people may have thought this happened overnight, at LSEG and Microsoft it was a logical extension of the technical advances we had been focusing on for years.
The emergence of generative AI represents the next phase of digital transformation. A central aspect of the first phase was instrumenting operations, processes and products across different scenarios and industries to gain visibility into how things were working (or not) and organizing this telemetry into ever-increasing data stores. sophisticated to glean valuable information. Generative AI enhances this capability with extended language models (LLMs) that dig deeper into data at incredible speed and conversational interfaces that allow people to interact using natural language. The result is a democratization of empowerment and knowledge to a level not seen since the advent of the Internet.
This is good news for financial services organizations that have invested heavily in digital transformation. This means they are well-positioned to capitalize on the fundamental attributes of hyperscale cloud computing, including security, compliance and assurance. From here, the factor that can help achieve the greatest innovation with generative AI is a data strategy that ensures the right data is made available to the right LLMs, and ultimately only to the right people.
With this general baseline, here are three important lessons about generative AI from our work with LSEG so far.
1. Choose the right AI solution for the right problem
Generative AI is so cool that it’s tempting to try to use the full extent of its capabilities. Resist this temptation. Focus your attention on the problems that actually need to be solved, rather than looking for ways to put AI to work.
Start with the problems that burden your users (for example, laborious processes between people whose time costs money) and work backwards. Look at the applications and environments where users spend most of their time and think about how to optimize them. One thing we’ve learned is that integrating AI directly into existing experiences and seamlessly adding support to existing workflows is far more effective than trying to create new application destinations. If you can suddenly summarize a document in 30 seconds where it previously took 10 minutes, you’re sure to find value.
As part of the LSEG partnership, we are focused on illuminating experiences within existing Microsoft investments, including Microsoft Teams, Microsoft Power Platform, and Microsoft Fabric. Among the early highlights of this approach is a new solution in the works to streamline meeting preparation for investment bankers, integrated directly into Teams.
We also work together to create custom chatbots and co-pilots within Teams to minimize the shift to custom application environments and answer questions like: “Show me the P/E ratio of (company).”
2. Apply your data management, leasing and residency strategy
The highly regulated nature of financial services means that system design and software architecture are particularly complex. Different people within the same organization will often need different levels of access to the key data under management, and these rules must be respected by an AI solution.
Rather than developing new ways to manage data access and security for AI, the better approach is to leverage existing solutions that provide these capabilities to adopt and implement access controls and regulatory requirements for AI. If existing solutions are inadequate, then the priority is to upgrade them. In other words, fix the foundations first, then build your AI solutions on top of them.
This allows you to understand the topology of what is happening where, e.g. what actions are happening in which tenant (e.g. LSEG customer data vs. MicrosoftGraph) — while ensuring complete security and compliance. This will also allow you to continue your existing practices around data residency, as well as those of high availability and disaster recovery (HA/DR).
With LSEG, we are focused on innovations designed to evolve how customers leverage their data to unlock new opportunities. This involves combining LSEG data and content sources into Microsoft Fabric and integrating them into the enterprise-wide data catalog and governance framework. Microsoft Competency.
“Together with Microsoft, we are empowering our customers to increase productivity while delivering greater efficiency, resiliency and scalability across all workflows, and equipping the industry with the right tools for the next generation of business professionals. finance. Our multidisciplinary data trust practice is an integral part of LSEG’s open ecosystem for financial services, built on transparency, security and information integrity. It aims to provide rigorous data quality and governance processes, scalable technology powered by Microsoft Fabric and Microsoft Purview, and the principles of “Responsible AI”..”
Satvinder Singh, Group Head of Data and Analytics at LSEG
3. Move towards greater customer focus
In the early stages of innovation, a common challenge is how to manage an overabundance of opportunities and interesting ideas from a very wide range of stakeholders. With so many exciting options available to us with AI, we realized we needed to focus more on prioritizing decision-making based on potential value to the business.
It’s important to resist the temptation to “boil the ocean” by trying to solve too many problems at once. Instead, identify a handful of usage scenarios that aim to benefit the end customer in a way that has a measurable impact on business goals. To achieve this, our teams have developed a methodology for scoring and ranking potential initiatives in order to identify the most promising options. We then surveyed LSEG’s end customers to help us better understand their needs and inform us about their preferences.
By combining rigorous customer discovery and a clear validation prioritization process, we were able to identify opportunities that we might otherwise have missed. For example, recognizing an emerging set of personas at the intersection of data and AI that we might expect to grow in value. years to come. Adopting a customer-centric approach also created a discipline to quickly test and disprove hypotheses that would prove to deliver minimal customer value at unacceptable cost.
Looking to the future with LSEG and Microsoft
As we progress in our partnership, LSEG will continue to move beyond providing data-driven products to offering services that leverage the expertise, data assets and insights gleaned from the Enterprise AI. This will help consolidate LSEG’s leading position in the market, delivering new solutions to drive financial stability, empower economies and enable customers to create sustainable growth.
For every business, there is a real opportunity to reinvent financial services. We are excited to continue our partnership with LSEG to deliver this value to customers and the industry as a whole.
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Adrian has over 25 years of experience building transformational businesses and supporting enterprise technology platforms at the intersection of finance, data, analytics and visualization. At Microsoft, he is currently General Manager, Microsoft Cloud for Industry – Capital Markets and was previously Partner and Head of Product Strategy, Microsoft Cloud for Industry – Financial Services.
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