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DigiTalks: Digital Focus on AI Markets
26 Plays1 year ago
In the midst of high levels of innovation in the trading space, HSBC has introduced AI Markets, a platform that is using AI to revolutionise the financial markets ecosystem. Listen as Selene Chong, Managing Director, Deputy Global Head of Equities & Head of Equities, Asia Pacific, speaks with Allen Li and Andrew Sharkey share the journey from ideation to implementation, giving a first- hand account of the thought processes and the collaboration that was needed to create the final product.
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Transcript
Introduction to HSBC Global Viewpoint
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Welcome to HSBC Global Viewpoint, the podcast series that brings together business leaders and industry experts to explore the latest global insights, trends, and opportunities.
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Make sure you're subscribed to stay up to date with new episodes.
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Thanks for listening, and now onto today's show.
AI in Trading: Innovations with AI Markets
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Welcome to Digitalks, focused on AI markets.
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I am Celine Chong, Deputy Global Head of Equities,
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And joining me here today are Andrew Sharkey, Global Co-Head of FX and Precious Metal Options, and Alan Li, Managing Director of GFX, the person behind AI markets.
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So
Platforms for Data and Execution in Banking
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there has been a lot of innovation in the trading space with banks moving the platforms to manage data, analytics, pricing and execution more effectively.
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As you can imagine, this can
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be quite an endeavor from realizing the idea within the organization to finally bringing it to its full fruition with clients.
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This is especially the case if you're also trying to simplify complex programming and works through legacy technology.
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AI
What Sets AI Markets Apart?
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Markets is such a platform that is using AI to simplify the entire trading lifecycle.
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We wanted to share the journey from ideation to implementation so you can witness firsthand
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the thought processes and collaboration that was needed to create the final product.
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But first, I wanted to take a step back for our listeners, for those of you who may not still not know what AI Markets is.
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So I will start with Alan.
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Alan, can you explain briefly what AI Markets encompasses and also why is it different to other platforms in financial services?
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Sure,
Vision and Support Behind AI Markets
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thank you, Shirley.
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I will start with the first part.
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So, AI market is essentially a financial market intelligence put into a box.
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Now, what I mean by that is in intelligence for financial market, you can have all the data, analytics, models, and your workflow.
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And the box here, what we mean is something that bring all this into one ecosystem, including the things like the collection, collection,
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of the data accessing visualization of the data, your pricing execution, and all those workflow digitization for pre and post trades.
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So this ecosystem of intelligence will basically make out AI markets.
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Now, the reason why this is different is it is the first large scale client facing natural language interface to access all those data analytics pricing execution.
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from bank.
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So, you know, having such a single portal for this intelligence basically makes it a lot easier for users to access this intelligence.
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Now, having that in one single platform also allow, enable a lot more collaboration
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And the adoption on the platform also makes it even easier to drive and make this ecosystem better.
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So overall, I think the system represents a significant innovation in the financial market.
Fostering an Innovative Environment at HSBC
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And I truly believe that it has the potential to revolutionize the way we do banking.
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Thanks, Alan.
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That explains it well.
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Every great idea needs encouragement and support for it to grow.
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So let me turn to Sharkey.
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Can you explain how this was made possible within HSBC and what factors were important in the final implementation of AI markets?
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Thanks, Celine.
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I think most importantly, Alan showed me his disruptive idea along with a basic proof of concept to digitize many of our workflows and information streams into one, leveraging some of the tech that had become available.
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It created that
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light bulb moment in my head.
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And I guess between Alan and I, we carved out a vision of what we could achieve short term and then what was needed to realize that on a step-by-step basis.
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We have to say, I mean, we've been incredibly fortunate that early on our management were comfortable for the development resources that we had within our business to be fungible.
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And I was able to carve out a small amount of funding for this, I guess, experiment, right?
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I really wanted
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I really want to call out and show my gratitude for management at this point, for the faith that they had in what was going to be one of our first experiments, particularly into AI.
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Moreover, what this did is it allowed me to tell the experiment team, Alan's team, that they weren't to worry about funding being withdrawn.
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I would be the shield, and I basically just told them to go.
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And as an asset class head, I was able to do this.
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And I think that statement, given my relationship with them and Alan and the team, it was genuine and it was authentic.
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Then each time Alan and the team delivered a release using this agile approach, I basically pushed the expectation and vision out a little bit incrementally, challenging Alan and the team at each step.
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I mean, we're definitely fortunate.
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that we were able to ride the AI buzz that was in the market at that time.
Agile Approach and Stakeholder Management
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Everybody was interested in what we were doing.
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But I think there was a difference in that we had a very flat organizational structure where within Alan's team, everyone knew what we were doing, what we were trying to achieve.
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And everybody had a voice at the table.
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We definitely built small and failed very, very quickly.
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And I think creating a culture of experimentation where team members felt
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comfortable proposing new ideas, testing new approaches, learning from the mistakes was key.
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I saw my role as creating the environment for innovation to thrive, to nurture, to protect, to challenge, and on occasion to shield.
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And basically, Alan and his team did the rest, setting aside dedicated time for brainstorming, providing resources for prototyping and testing, and recognizing and rewarding team members who take calculated risks.
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I think that innovation often occurs at the intersection of different disciplines and perspectives.
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We had brought together a small but cross-functional team from different departments and backgrounds to work together.
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You know, this helped us generate new ideas and approaches that probably wouldn't have been possible or thought of, you know, within a single department or function.
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Alan was also very able to encourage collaboration.
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by setting clear goals and expectations, providing opportunities to team members to share their ideas and insights directly with our front office trading team, and also for recognizing and rewarding collaboration.
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I think it is also key that we provide our teams access to the right tools, technology, and training.
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With AI Markets, we did this.
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We allowed our development team to access resources they needed to innovate.
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We invested in new technologies.
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We provided access to training and development programs, and we created opportunities
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for the team members to learn from experts within their field.
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We have a culture in HSBC where leaders encourage continuous learning by setting aside dedicated time for professional development, providing opportunities for team members to attend conferences and workshops, and recognizing rewarding team members who pursue ongoing learning and development.
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For example, within AI Markets, I created a program where we rewarded the developer of the month with a trip to one of our main hubs.
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I think it's good to have an incentivization structure, but it also needs to be paired with recognition.
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One of our industry recognition results that we're very proud to achieve was having AI markets identified and awarded top financial innovations in artificial intelligence by Global Financial Magazine in 2023.
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I think what's impressive is that large organizations have many stakeholders and you need to make sure that everyone is on board.
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So
Understanding Market Needs and User Feedback
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thank you for sharing what is truly a recipe for success.
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I have one more question for you, Sharkey.
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I mentioned multi-stakeholder management.
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How did you finally manage to get this over the line?
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And what are the ingredients for success here?
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It is definitely key to ensure senior stakeholders are engaged, that they feel part of the project and feel able to input, but most importantly, witness the incremental deliveries regularly so that they can see, I guess, a return on investment.
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An agile approach allows this.
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We regularly exceed over 200 software updates a week in AI markets.
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I am also of the belief that communication holds the keys to success.
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So Alan and I ensured that we had suitable communications on what we were doing to ensure all stakeholders felt engaged on a regular basis.
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We bothered a lot of senior people a lot of the time.
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But I also think it's not easy to do 200 software releases a week.
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And I think there are three main ingredients for this.
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One, we had to ensure we created a flexible and agile environment that encourages experimentation and risk-taking.
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By having the right level of governance, we gave the development team the freedom to innovate and try new things without getting bogged down in unnecessary processes and regulations.
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We moved quickly and we made decisions with minimal approvals leading to faster time to market and thus a competitive advantage.
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Secondly, another thing we did extensively was understanding the needs and preferences of the target market.
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Alan and I were actively trading on the desk and so we knew
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what AI markets needed to do and to have.
Future of AI in HSBC's Financial Functions
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We saw lots of client feedback.
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More generally, I think that by listening to users and incorporating their feedback into the development product process, teams can generate products that are able and likely to meet the needs of the market and be adopted more quickly.
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This helps to build trust and credibility with users, which can lead to increased adoption and advocacy.
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Last but not least, and probably above all,
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Alan and I received continuous support and trust from our management, and I then provided the same for the AI Markets team.
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I believe managerial support and trust will help ensure the success of an innovative product by providing ongoing guidance as well as resources for the teams.
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I think by fostering a culture of continuous learning and improvement, we can help teams stay up to date with the latest trends and technologies and make informed decisions about the product roadmap.
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I couldn't agree more.
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Continued support and trust is definitely pivotal to getting a successful product over the line.
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Okay, so Alan, where do we go from here?
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Sure.
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At a high level, we're going to continue to build out the intelligence so that it becomes more intelligent.
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And we're going to continue to build out that box so that it's going to connect better, both connecting user to the function system, but also connecting user to user.
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Now, what this means is that in practice, there are a few things we want to focus on.
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One, we want to focus on really improving the user experience to drive adoption and that adoption will then also drive the evolution of this ecosystem of intelligence.
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The second thing, we want to build this out as an open platform infrastructure so that we can get more people engaged, function built, and also benefit from this.
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We want to expand this to equities, to GDN, to other parts of the banks.
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Thirdly, we want to also expand this distribution fabric so that it becomes easier for our users to use that in a way and to interact that in a way that they like.
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And lastly, just continue to integrate cutting edge development in AI and large language model in the system so that we continue to improve this financial market intelligence in a box.
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Thank you, Alan.
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That's very exciting stuff to look forward to.
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So, Sharkey, where is the sector going in the next few years?
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I think banking and finance are young in their adoption of AI and machine learning, you know, say versus medicine or graphic design.
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There is no doubt that this is going to catch up.
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I see lots of positive disruption and process optimization using the AI improvements and functionality across front and middle office, as well as across operations and downstream processes.
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In AI markets, particularly, what we're going to see and deliver will be a lot more asset class and HSBC group functions coming online and the integration and harnessing of generative AI that will allow us to push concepts rather than requiring the user to input a command to do some instruction that the user asked for initially.
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The system, as Alan has said, will get smarter and cleverer, pick up its intelligence.
Conclusion and Call to Action
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We have a real buzz in HSBC with AI markets and our other AI streams of work across the bank, as it is something we can really get behind and iterate quickly.
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It is both very exciting and a true honor to be at the cutting edge of financial AI development with HSBC.
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But we are also very humble to the fact that we are very early in our lifecycle journey.
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And with that, we conclude this Digitalks.
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Thank you very much, Andrew Sharkey and Alan Lee for sharing your insights with us today.
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Thank you listeners for being with us.
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Go and check out AI Markets.
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Thank you for joining us at HSBC Global Viewpoint.
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We hope you enjoyed the discussion.
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