It's time to navigate the riveting world of capital markets and technology. Neil Chinai, Operating Partner at Sand Hill East joins us to discuss four technology trends you should be tracking if you work in Capital Markets. With over 25 years of experience driving innovation in IT for Tier 1 banks, Neil brings a wealth of expertise to the table. During this episode Neil and host, Jim Jockle of Numerix, provide expert insight on how low code, no code, and blockchain asset tokenization are reshaping the financial industry. We also discuss the vast impact AL/ML has and will have on the industry and digitalization in the face of recent technological advancements.
It's time to navigate the riveting world of capital markets and technology. Neil Chinai, Operating Partner at Sand Hill East joins us to discuss four technology trends you should be tracking if you work in Capital Markets. With over 25 years of experience driving innovation in IT for Tier 1 banks, Neil brings a wealth of expertise to the table. During this episode Neil and host, Jim Jockle of Numerix, provide expert insight on how low code, no code, and blockchain asset tokenization are reshaping the financial industry. We also discuss the vast impact AL/ML has and will have on the industry and digitalization in the face of recent technological advancements.
Welcome to Trading Tomorrow, navigating trends in capital markets. I'm your host, jim Jockel. In my decade plus of working with Numeric's global leader in capital markets risk management technology, I have launched our Thought Leadership Division, a place where insights, innovation and expertise converge, just like this podcast. Through my journey in the financial realm, I've had the privilege of witnessing firsthand how the capital markets landscape has transformed. The complex dance of market trends and innovative technology has redefined how the finance industry operates. With game changing innovations just around the corner, we now stand at a crossroads, one where it is more crucial than ever to understand the interplay between these realms. That's what we do here. We talk about current and future processes and technologies you need to be aware of moving forward. Today, we'll be talking about four technologies or trends you need to be tracking if you work in capital markets. With this episode, we are hoping to help you remain ahead of the trends. If you're someone who just found out about chat, gbt or AI just a few months ago, this is the podcast episode for you. We will cover what will be some of the biggest tech trends and innovations coming in the capital markets, so you can be at the forefront.
Speaker 1:Joining me today for this discussion is Neil Chenai. As an operating partner at Sandhill East, neil has carved a reputation as a visionary disruptor and a thought leader within financial services and fintech communities. With over 25 years of experience driving innovation in IT for tier one banks, neil brings a wealth of experience to the table. His influence spans across capital markets, investment, banking, security services, lending and structure products. Neil's keen insight has led him to guide early stage fintech firms and financial services software providers in areas like product strategy, business plans, it infrastructure and fundraising. His career journey has seen him at the helm of technology transformation for global giants like HSBC. Neil's ability to adapt technology enablers for everything from analytics and data science to digitalization and blockchain integration has left a lasting impact on the industry. Neil, thank you so much for joining us today. Jim, thanks for having me. So first up, we have low code, no code for banking. Can you briefly describe what this is and why you think it will be revolutionary for this space?
Speaker 2:Well, low code no code is really moving to a visualization and for end users to really be able to wire applications together. Low code sort of means you can wire a lot of it through visualization and tools and you do a little coding. No code means there's absolutely no code required and the visualization and the IDE you're working in makes it easy for end users and rad work to be done. I mean, the real importance of this is you're not dependent on the IT department, where it tends to be a big backlog, and we're really trying to bring agility and helping the end users drive more software releases and help their businesses.
Speaker 1:So many banks still rely on legacy systems, though. Do you think the adoption of low code no code will change that, and if yes, how?
Speaker 2:so Well, I think when you think about legacy systems, we think about monolithic systems. It's been around for a while. I think there's a whole rabbit of change going on, and one of them is low code, no code. That's going to allow end users to be more empowered as part of the whole digitalization strategy that are going on inside of firms and what they're trying to do with their data.
Speaker 1:So one of the things that I would want to kind of jump in there is when you talk about end user, can you describe that end user and what kind of? How is the skill set changing?
Speaker 2:Well, I mean, I think an end user to me is usually a business user and if the technology allows you, as an end user, to do more yourself, that's really, really important, because then it brings this ability to do releases quicker to you understand your business, to make changes faster right Now, on the other hand, the IT department, I think, will still be very important. They'll probably be doing more core types of work where this is what we're describing more end user driven types of applications.
Speaker 1:And in terms of low code, no code are there any specific areas within institutions or within FinTechs that you've been working with that you're seeing interesting adoptions and changes that are really affecting businesses today?
Speaker 2:Yeah, I mean inside of some of the cell side and certainly inside of some of the fintechs. We are trying to adopt it so end users can do more on their own and be less dependent on the IT department. The IT department and some of the cell signs firms that we work with are thinking this way so that they could empower their users and the end user can then do more.
Speaker 1:So the second technology that you really wanted to chat about with us today is around blockchain asset tokenization. So why is this technology a good fit for banking and how could it enhance liquidity and be a more cost effective option?
Speaker 2:Well, I mean, the first thing I think that happens if you could, but digital assets or tokens on a blockchain is that it's more liquid, it's more streamlined, it's more cost efficient. There's plenty more you can do off the blockchain once you're on the blockchain. Also, if you look at let's just take something simple as real estate, you could fractionalize it so much easier once in digital form. So it's really like, when we talk about digital assets and blockchain, I think almost everybody says the blockchain is what is really powerful, the blockchain is what we like. So the more we can tokenize on a blockchain, the more power, simplicity, cost efficient and liquidity drive into your solutions.
Speaker 1:And this technology would open a more global marketplace, which is crucial for the future state of trading, correct?
Speaker 2:Yeah, I mean I think we're headed in that direction. Some of the sell side firms are already doing tokenization. It could be bond offerings, it could be different aspects of the capital market structure. I think we're going to see a lot of this kind of play out in the next couple of years. If you know the company digital asset they just rolled out on top of down below blockchain solution. So there's a lot of activity in the background going on that will come more into mainstream over the next couple of years.
Speaker 1:You know specific to blockchain. Obviously there was the introduction of blockchain specifically around crypto and the two became synonymous. Then there was the hype cycle, where everybody's going to be in the blockchain. Where are we in that hype cycle today? And from what you're saying, development is continuing and moving forward, correct? Yeah, I mean.
Speaker 2:I think there are a number of really interesting initiatives going on. Some of them could be around stablecoin. Others are just using the blockchain. Yeah, so I think it is going on in the background. Different firms are trying to leverage the blockchain, but it's not at the hype where we're all talking about cryptocurrencies anymore. It's more about your business, how you leverage the blockchain and how you become more efficient, and I think one of the key things that drives people in this direction is cost efficiency and reaching more customers.
Speaker 1:So the third technology is incredibly popular. I think everybody's thinking about how they use it and in their own lives, across many, many different markets, and that's AI. And last one we spoke in May. You said that chat, gpt and AI. It's moving at incredible speeds. So here we are, you know, a couple months later. What changes have you seen since that time regarding this technology?
Speaker 2:Well, I think chat GPT is only getting better and more powerful. More releases are coming out. I think we've seen an enormous amount of releases from Microsoft, google, amazon, nvidia, and all you see happening is partnerships and the idea that you're going to marry what we call advanced computing, which is really the cloud, with generative AI on, basically, gpus. So you know, as Jensen said from the video, this is an incredible explosion of two trends coming together. So I think we're continuing to see that.
Speaker 2:I think on the other side, you'll also hear that there's still a long way to go. Where there is A big part of what firms have to do is figure out their data strategy and how they're going to adopt GPT into that strategy. You know the use cases, I think, that are really simple, are ones that come to mind really quickly, is anything with unstructured data. So if you look around call centers, around R&D, around software generation against marketing and sales research, I mean, there are large, large amounts of documents or anything that's textual or anything that's natural language and how humans interact, and that's where GPT comes in and generative AI comes in very, very well.
Speaker 1:But yet there's certain objections by banks in terms of usage of that, in terms of data privacy, you know, public information or private information going out into public. Where do you see that debate at this point in time? Or is that creating more opportunity for private training, private clouds, things of that nature to take advantages of those technologies? I mean the way I look at.
Speaker 2:Privacy is obviously an issue and something that we need to be very mindful of, but, unlike when Facebook came out, there was no real conversations about social media, any rails. The industry is trying to set some rails in terms of what you can and can't do, and I think there'll be continued to be a lot of discussion around how far to take AI. So, yeah, I think I'm mindful of the fact that if we put it in the wrong people's hands and we use it for the wrong purposes, it could be quite disruptive. So I think firms themselves, through their data architecture and how they use a cloud, or how they use a hybrid cloud and how they use generative AI, will be mindful of what power they're going to unleash.
Speaker 1:So in that adoption period, obviously people are playing with it. They're trying to discover new opportunities for it. Is that going to curtail adoption within financial services, specifically banks or other highly regulated entities?
Speaker 2:So what I kind of I think I see happening and I see this across a number of different software companies and also inside the banks is people are trying just starting to play with chat, gbt or other forms to generate AI and trying to see what kind of power they can get out of it. So that could be you could just get a co-pilot from Microsoft and start using that as an assistant to all the work you do in office and your product typically go up five to 10 times right. Or you could start using just chat, gbt, other forms of it in terms of software testing, software code generation. You could start using it in terms of just different textual types of questions. You ask it and refined it.
Speaker 2:This term of a prompt engineer has gotten a lot of notice and it's becoming a job that what a prompt engineer does is basically interact with the AI models, and so that's going to continue. We're actually working on a project at Sandhill that tries to automate prompt engineering by taking all your corporate data and signaling it into the AI models to give you better answers. So the idea is, if you ask a very wide searching question, you'll get a wide searching answer from chat GBT If you ask. If you say I work at X company, I do this job and you ask a very specific question, you'll get a better answer. So there's a lot of that going on to experimentation and how to get the most out of AI. Darrell.
Speaker 1:Bock, and there's even quality controls in terms of empowering the AI's imagination, if you will, versus very specific answers to your question. As I understand it, david Kroger.
Speaker 2:I think quality control is going to be part of the whole testing mechanism and to make sure that the output you're getting are reliable, believable, but that would go for any kind of technology too. I think there's a lot of awareness around making sure you get accurate answers, darrell.
Speaker 1:Bock. So just out of pure curiosity how do you gain confidence? What does that backtesting look like? What is? How do I sit here and say chat GBT. I trust you.
Speaker 2:Well, remember we're early days, right In terms of results. But I think the way you're gonna get confidence by the way you interact with the models and you start to get the answers you think are reliable and accurate for your business.
Speaker 1:Well, you know, offline, as we were chatting about today and this podcast was, you know, you call digitalization the future. You know? Perhaps you can explain to us what that is and why you believe digitalization is the future.
Speaker 2:We think at San Jose. This decade is about digitalization, right, and if you kind of look at the map we've been on 2022 to 2024, you know really you could put that the center of that timeframe is huge advancements in the cloud and then bringing AI in. And when we think of digitalization, we think about, first, customer centric. Everything you do must be about the customer. At the same time, it must be sustainable. You know, any technology or business that doesn't think about sustainability will have issues. It must be frictionalist, right. The value to the customer is zero touch. Reduce all those back end processes. A big part of this is talent. You're gonna have to be on top of your talent and make sure you have the right talent. And kind of in the center of it is AI, data and analytics, and the big thing is monetizing your data.
Speaker 1:And it feels right now there's a convergence of maturity in a lot of these technologies, whether it's cloud, whether it's AI, whether it's blockchain, whether it's even just the last 10 years of data rationalization, building of data lakes the whole bit. It just seems like everything's coming to an acceleration point. Would you agree with that?
Speaker 2:Well, I think things are accelerating, but I think I'm gonna go to a little different path to answer that for a minute. So, when we say digitalization, you know what we're really talking about is optimizing processes and becoming more operational. Agile number one, you know I mentioned the customer experience, also having employee productivity tools. It's also about being more like a technology company and it's also about what you do with your data, whether it's real time or in batch and monetizing and then out front. I think we're only at the beginning, like how many of the companies out there are truly monetizing their data? How many of them are thinking about how to monetize their data?
Speaker 1:And so to that end. So what are some of the dimensions of a successful digital company? You know, when you look across the landscape, you know, obviously, we know the big brands. But to you what stands out as someone who's differentiating themselves through the adoption of different technologies, and what are the key signs of that?
Speaker 2:Well, the first one, I think, is when you talk to people that work with that company or use that service, the first question is are they customer centric? Number one. Number two is it frictionless? So when you use the product, it works front to back. You don't have to go to some production support person who then feels your questions right, it's all automated.
Speaker 2:Have they thought about sustainability, like how they're actually going about it? We do care about ESG and what is their data and process architecture right? So I think a lot of companies are down that path, but there's so much more to go, and you know big thing about blockchain and digitalization. Honestly, it's the kind of technology that's working more on the operational side. To be honest, right Versus over the last 20 years, we were automating everything on the front side. As you said, I worked in banking for a long time. You know we had these pricing systems, these risk systems. It was all before the trade, and a part of digitalization and blockchain is up after the trade and having the front to back be fully automated, and for that I think we got a long way to go.
Speaker 1:Have we started to see, and I'm assuming the tangible results are going to be margin improvement, revenue growth and translate into opportunities for the business itself.
Speaker 2:Yes, I would agree with all that. Also, how we use our people, right. If one of the things you have is a team of 20 people who read emails and then routed into service, now that's not the best use of employees, right? So if we can automate that and we have a number of companies even at Sand Hill that can do that, can digitize it then the idea is that the employee morale should go up because the type of work they're doing should be more value added, and I think that's part of what has to happen here.
Speaker 1:And you bring up a thing that I think a lot of people are afraid of and I'm going to stay on that word people right. You see studies from the London Business School of Economics and how AI is going to change job profiles or eliminate jobs right, whether it's robotics or whatever. But I think a key point is the technologies as of today are helping people do better jobs and more rewarding jobs. Would you agree with that?
Speaker 2:No, I would agree with that, and I think it will get better from here. The fear, of course, this is you know, we've had many revolutions in terms of technology changes, and every one of them has always been people worried that all it really means is all jobs are going away, and that has yet to happen. This particular one, with general AI, does come across as hitting the white collar work, or more, so I think there is a lot of fear around it, and, you know, a lot of times, people are used to doing things in a certain way, and if we want to change their jobs, that could be fearful to them. So I think, though, the idea is that jobs should get better, things should get more automated and more value should be added in general overall.
Speaker 1:So just coming back to financial service companies, capital markets I mean obviously certain companies have a lot more resource, whether that is people or talented people in these areas, deeper pockets, time for investments. You know, for smaller industries to be competitive against these larger players, obviously they need to make investments as well. So you know, how is the industry going to align itself between the haves and have nots in this type of revolution?
Speaker 2:Well, I think it's kind of an interesting dichotomy right now because the bigger companies have a lot of legacy right and moving that legacy out is not easy and someone will be in a cloud, some don't, someone a hybrid cloud, younger companies, smaller companies that don't have any of that legacy and can focus on digitalization and automating could actually advance quicker. So I think that remains to be seen. The larger companies have probably the market share and all the clients that you want that the smaller ones want. So I think it's going to be really an interesting story to see how many of the smaller companies can leapfrog and there are always a few that do leapfrog especially around tokenization, blockchain, digitalization, right and how many of the larger companies make the adoption at the pace they make it. At Sandhill, we have a lot of startups and early stage companies that are all working on different forms of digitalization and we see them making some real end roads in terms of how they change the footprint.
Speaker 1:You know it's funny when you talk about revolution. I think back to my first firm that I worked with. We had a print shop in the basement that was probably the size of about 20 Kinkos and you know the whole company thought it was going to be the end of the world when we closed it to save money. So yeah, I think a lot of fun evolutions to come. So we're now made it to the final question in this podcast and we call it the trend drop. It's like a desert island question. So if you could only track one future technology within capital markets over the next few years, what would it be and why?
Speaker 2:Well, I kind of think it's a combination of the advanced cloud computing being the cloud and genera of AI and how that's going to change how people do their job, and a lot of it's going to drive productivity in terms of what people are able to do, the whole world of natural language, communicating as humans and using generative AI as a tool to help drive productivity. Research I mean, if you look across the whole research in the medicine field, in the farmer field, it just seems like over the next three years let's pick that number that generative AI is going to provide really, really great advances in research.
Speaker 1:Well, neil, I want to thank you so much for joining us today, and this was a fantastic conversation. I hope you'll join us again next time.
Speaker 2:Definitely, and I very much enjoyed it and thank you very much, jim.
Speaker 1:Coming up next week. We're covering survey findings from Acuity and why anyone working in derivatives and risk management should be taking note. Stay ahead by tuning in to our latest episode. But first, if you enjoyed the podcast, make sure you hit the subscribe button, leave a comment, a like and check out our other episodes. Thanks for joining.