How Busy Professionals Can Use AI to Invest Smarter | Eric Chu, CFA

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Speaker B: Oh, I think after this almost 20 years on wall street, you know, I think the most important critical skill set as an investor is really you want to. You want to watch out for the pitfalls, right? You don't want to do market timing because honestly, nobody can do it. You don't want to, you know, dive into things or invest into things you don't understand because that's how you make mistakes easily. And I think so uh, on the flip side, really, the way to do it is you have a goal. You have a clear goal. What you Want to achieve either financial freedom, college education or retirement, what have you. Right. Then you work backwards.

Speaker D: Right?

Speaker B: Here's my goal. What in order to achieve that goal, here are the resources, here's the income I have.

Speaker D: Right.

Speaker B: How do I go from here to there? Right? You have a clear plan. And then especially for individual investors, right.

Speaker D: You know, we are live. Ladies and gentlemen, you once again, welcome to the King Danes forecast and Diary of a cfo. And today I've got with me a, uh, very special guest, fighting out of New Jersey, United States of America. Make welcome Eric Chu. How are you today, Eric?

Speaker B: Good, good. How are you?

Speaker D: I, um, am amazing. I'm amazing. It is always, uh, an amazing thing to have people from the world of finance on the podcast because I am a finance person myself, so I always have a positive bias with finance people. I'm chartered accountant, you know, with a first degree in economics, an MBA as well, with background with the big four accounts and firms, um, PwC and KPMG. So appreciate having you so sit back while I read, uh, to you the carefully curated introduction we have for you. So, uh, ladies and gentlemen, today's conversation sits right at the intersection of finance, technology, trust and human behavior. Our guest is Eric Chu, cfa, CEO and co founder of uh, Trades Securities, a fintech leader working to modernize retail brokerage by making investing more transparent, more intelligent, and more aligned with how people actually make financial decisions. Eric brings a rare blend of, uh, experience across engineering, Wall street, capital markets, data centers, hedge funds, public company finance, and regulated fintech. Through Trade Desk, he is helping investors cut through market noise with AI powered insights, portfolio tools, and a, um, more disciplined approach to decision making. What makes this conversation important now is simple. AI is transforming finance. But, uh, the real question is not whether technology can produce more information. The deeper question is whether it can help leaders, investors and entrepreneurs make better decisions. So today we are going beyond stock tips. We are exploring systems, judgment, trust, transparency, and the future on investing. Eric, welcome to the podcast.

Speaker B: Thank you. Thank you, Adamora. Uh, thank you for, uh, inviting me over. It's a pleasure to be joining the podcast and then, you know, discuss my experience, my background, and also what's going on in the market overall. So, yeah, so it's a pleasure.

Speaker D: Okay, amazing. So, uh, before we talk about AI investing or fintech, take us back to the beginning. What? Early experience. First, uh, shift how you think about money, about risk, and about opportunity.

Speaker B: Sure. I think, if I may, let me sort of, uh, do a quick introduction of my background just to put some context for the audience and just to know where I'm coming from and where some of the sort of references, the talk points that I'll be mentioning, where are those are coming from. So you know um, being in the financial services industry for almost 20 years after business school from NYU Stern, I joined an investment bank covering telecommunication services companies including data centers, fiber optic companies and then followed by a couple of years at hedge funds doing long short equity investments for a variety of industries. And then later on had the experience joining a um, publicly traded data center company as one of their uh, senior executives in charge of capital market activities. And also later on I went into operations, very deep into operations, actively developing data centers, financing uh, data centers and working with institutional investors. Along the way we brought in uh, one of the top premier uh, private equity firms, Warburg Pincus. And then uh, we back then about almost 10 years ago now looking back, we formed one of the largest and the earliest data center development platforms in Asia. Back then about uh, 300 million M US dollars equivalent. When you know that amount is still a reasonable amount, you know, large amount rather than today it's kind of a, you know a small fraction of a lot of the large projects, data center projects. So that's kind of my background. Right. You know it's had um, a kind of interesting path in engineering which is before my uh, sort of the finance world. I was also an engineer prior to my mba. So you know, interesting experience there and then the investment banking side experience there. Capital markets and hedge funds as well as publicly listed companies. And I think tradeesk is really, which is the company that I helped founded about three or four years ago actually brought everything into one place where our, we have a couple of sort of angles. One is that we believed in the market there is still opportunities, a lot of investors that are struggling with a efficient and clear investment tool, A uh, platform that can help them make decisions and cutting through noise, a lot of market noise. So that's one reason why we helped found Tradest Securities. And then the other angle for us is really given my background in the data center world, you know we believe this is a market still underserved, underdeveloped, especially for you know, newer developers in the data center services industry. Some of them, they might be prior crypto mining companies, they uh, might be commercial real estate developers but obviously you know, all a lot of demand in the data center world and then a lot of activities and then we're just helping them to sort of make the transition along the way given our hands on experience uh, developing some of the largest data center projects. So that's kind of where we are coming from to kind of go back to your question. Um, in terms of the risks in the market, the market especially, I'm talking about more specifically in the US Financial services market in general. It's a highly sophisticated market. A lot of players in the market, you know, investment banks, uh, hedge funds, ah, trading firms. Obviously, increasingly important are the retail investors led by some of the company, ah, starting with the letter R. We probably all know who that company is. But anyway, just a lot of moving parts, very dynamic, very sophisticated, and a lot of things move very quickly. So, uh, then the natural question is, how does a individual investor handle a lot of the moving parts, the dynamics, the market noise, and still be able to kind of achieve his or her goal, financial goal along the way? I think that's part of the reason for us to establish traded securities. You know, we are not a platform that put together every and all the sophisticated tools in the market. There are other platforms that are doing that. So for us, we are specifically targeting the busy working professionals. Most of them, honestly, they are not in the financial services industry. But these could be lawyers, doctors, maybe pharmaceutical, you know, executives, marketing, uh, you know, managers. Right. These are all very, very busy working professionals. They are busy building a career.

Speaker D: So who are your competitors?

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Speaker B: So our competitors, you know, we have a lot of them, big and small. The big ones obviously are, some of them are well established, uh, companies like Charles Schwab, Fidelity, you know, uh, and some of the newer ones are companies like Robinhood, just to name a few. But these are really, really very large platforms, very large competitors. We don't see them as ah, direct competitors to us because we have a very specific niche, uh, and targeted segment which is um, kind of from the 30 to 40 year old working professional that is very, very busy building up their career and building a family. Right, who has, may have the discretionary income to invest in the market, but does not have a whole lot of time. So that's where sort of the pain point we're trying to solve by leveraging AI technology by leveraging a lot of the uh, insights experience that we have built throughout the career, my career and my team's careers.

Speaker D: You trained in engineering, then moved into Wall street and capital markets. What did engineering teach you about problem solving that finance later confirmed or challenged?

Speaker B: Yeah, very, very, very good question. I mean this is kind of a, you know, feels like 20 some years ago, uh, in my prior life. But we had, I uh, mean I had very rigorous training in engineering and prior to engineering, obviously leading into engineering, uh, you know, field in math, physics and computer programming. Right. A lot including a graduate school in engineering, uh, prior to my, um, finance sort of finance career. I mean, I think all those background and years of training really built a very strong foundation in terms of the analytical capabilities. Be able to cut through numbers, understanding numbers, the sense of not only just doing the addition and subtraction, but really have us very clear sense of numbers, of directions, statistical results. All of these are clearly foundational skill sets that are required in the financial services industry. Whether or not I say financial, uh, analyst or research analyst. That was my sort of the first career, first job out of business school. You know, every single day, whether or not you are building financial models or reading industry reports or writing industry reports or talking to companies that we cover or the senior executives, uh, of the companies that we cover, analytical skills, quantitative skills are sort of the foundation. Right. The very basis of a lot of things we do. Same, same thing fall after that, you know, for all the other careers that have had at either the publicly, uh, listed data center company as the executive executive in charge of engineering, new project development or financing. Right. You know, all these skills are very, very essential to, to be able to support, to be able to, to, to do that job well. So I would say that's kind of a, uh, the, the, the, the origin of it.

Speaker D: Okay, so your, your career trajectory is a very interesting story. So I am curious about what career breakthrough was it that gave you the confidence to build something as complex as three desk?

Speaker B: Again, that's a very, very good question. I think really comes from not just my background experience, but also all the experience and backgrounds from our team. M. Because we have very talented and hardworking dedicated engineers, group of engineers that bring in all the skills that can essentially put an idea or insights or analytical results into computer programs, into nat. Right. Into a uh, desktop sort uh, of a platform that can help our investor, uh, clients manage their portfolio in research.

Speaker D: Right.

Speaker B: That's very, very key because without that there's no execution. Everything would still be on paper. Right. So that's very important part of it. And then I would say probably the most important, the more important part of it. It's really the insights that myself and the other senior executives on the team have gained. Um, throughout our careers, primarily in the financial services industry, we have seen uh, some of the up and downs in the market. Personally, I have been through three, um, uh, sort of downturns in the market. Big ones all the way from 2020, the Internet bubble to 2008 to the uh, financial crisis.

Speaker D: Now I'm curious, I have a question for you for 2008. So what did the 2008 financial crisis or other market shocks teach you about humility in finance.

Speaker B: I got a very, very interesting story to tell there. So after, during B school that was in the middle of the financial crisis, right. You know I started my MBA, uh, at NYU in 2006 when things were all booming, right. Everything was really sort of up and right. But you know, come 2007 and early 2008 a lot of things have changed. Right. You know we were literally on front row seat. I was actually supposed to join a company called Bear Sterns. That's one of the top, you know, investment banks essentially. You know almost 100 year old bank back then was top five in the US but you know, one thing led to another and then the uh, the company essentially went bankrupt and got acquired by JP Morgan. This is in early 2008. And so everything went you know, uh, sideways along with my job right after B school I was supposed to, I signed the offer with them, um, supposed to join them on a full time basis after graduation. But obviously a lot of things changed. So that's kind of a. To answer your question in terms of humility, that's the very first lesson, right? Coming into the financial services industry, coming to Wall street, you know you're kind of. My full time job at the very top investment bank essentially went poof overnight, right. So had to kind of look for other opportunities uh along the way. And uh, I was fortunate enough to join a ah, pretty large uh, hedge fund right after the Bear Stearns um you know story and then joined hedge fund also at a very interest interesting time during the, the v shape of the recovery of the market. This is back in 2008 and 2009 a lot of things changed almost on a daily basis, sometimes on a, on an hourly basis. Back then at working at the front, you know, at the hedge fund volatility, got to see a lot about volatility honestly a lot of hard work, a lot of changes by the hour. Uh, obviously a lot of responsibility as well because we manage you know, clients money, we investing in positions and some of them they worked out, some of them they didn't. So you know along the way you got to. And then things move really, really quickly. So you have to be sort of on top of things on a, on a minute by minute basis. Right? Why this is changing this way, why this company is not working out as we had anticipated. You know, what's changing the market, what's the change in the fundamentals was not changed. Right. So a lot of things that kind of goes in there. But you know, again, sort of that gives us, gives me a good, you know, sort of front row sea experience of how sort of things move around. Right. You know, how the dynamics work in the market, in the hedge fund world, in sort of the public listed companies, so on and so forth. So that's really a good, absolutely a good experience that helped me tremendously afterwards in my career.

Speaker D: Interesting. So when building in a regulated industry, what is harder than what outsiders would expect? Because you talk about the volatility, talk about, you know, still meeting compliance, you know, with the regulatory bodies. Like what is really harder than what, you know, meets the eye to an untrained eye.

Speaker B: Yeah. So you know, being a CC registered broker dealer, uh, today security. So we are also a member of FINRA and sipc. Uh so you know, we follow, I mean financial services industry, especially as a broker dealer, as a heavily regulated industry, there are a lot of regulations and also securities laws that we have to follow. And then we have very strict procedures, policies and procedures that we have to follow. This is a document that's hundreds of pages that kind of defines almost everything that we have to follow. We have to do as a broker dealer, how to handle customer accounts, how to handle archiving, how to handle, how to manage our employees, how to supervise, you know, the register representatives, how to work with clearance firms, how to work with the other vendors, service providers, data providers, quotation providers, uh, and other broker dealers. Right. It's a lot of things that we have to follow. And then on a regular basis we are also kind of a. Will be audited by the auditor again per regulation rules. And uh, and then we also have full time um, uh, compliance staff that's full time with the firm that's taking care of and overseeing all the regulatory related aspects of the business. So it's a lot, uh, there's a lot going on behind the scenes, um, in order to be able to support a trading platform or a broker dealer or a boutique investment bank that's sort of on the front end that customers can see.

Speaker D: So uh, moving into AI and data centers, because these are two themes that are very close to your heart. What is it that people misunderstand about AI in investing?

Speaker B: Yeah, so this is a big topic that involves a lot of moving parts. I would say maybe we start from the basics, right? So AIs and in general data centers. So nothing happens for AI unless there is a data center and all the infrastructure that would support it. To give you an example, right. You pull up one of the most Popular sort of AI tools, right. You know, interactive chat based tools. You put in the prompt, right. As soon as you hit the Enter button, a lot of things happens in the background, right. You know, that command after you hit the Enter button gets sent through your local network into the closest wireless tower and then through a, uh, fiber. Typically the wireless towers are connected through fiber network and then that same command sent through the fiber network to the nearest, to the closest data center and then to a server in a data center.

Speaker D: Right.

Speaker B: You know, then all the data and this data gets processed, stored and then most likely transmitted either to another data center or back to the network that your home, your office came from. Right. That, that's one command. Just imagine there's hundreds and thousands, if not billions of commands that's going on at the same time. So all those things occur because of the infrastructure. Data center, data centers, networks, towers, fiber network, all those have to be present in order for the AI sort of uh, applications to be able to be executed. Uh, so that's kind of the area that we have been focusing on. And frankly about 15 years of my professional career have been on the data centers. Different, various functions, different angles, but in general basic, basic sort of, that's kind of what's really supporting the AI.

Speaker D: Thank you for that brilliant analysis. So how can AI, uh, help investors without turning them into passive followers of a tool, of a machine?

Speaker B: Yeah. Uh, so you know, AI in my view the most direct usage or functionality is especially related to the investment world is that it can help substantially increase productivity or in other words, get things done, cut through data in a much, much quicker manner than it used to. I'll give you an example. So about 10, about 15 years ago when I was working at the investment bank, right, as a research analyst, we used to cover about 20 companies. And every single company, there's quarterly reports, there's SEC documents, SEC filings, annual, uh, filing, quarterly filings, and sometimes, you know, daily filings for events. Right. And we as analysts, we have to spend days and days and weeks of, to research one idea, one company to, in order to put up, for example, to put together a industry deep dive, even 10, 20 pages that used to take us about two, three weeks to do, right? You know, because man, we have to manually dig through all those ACC filings, financial documents, press releases, earnings transcripts, and then also do the financial models in whatever is needed, industry model or company specific model in order to support our view, our research reports. But today for the same kind of output, let's say if you want to generate the company specific report, industry uh, report, all you have to do is you put in some prompts in the AI engine, right? And then the AI engine obviously you want to structure your prompt, uh, correctly. But once you have that done, then within maybe half an hour, if not sooner, you get a comprehensive summary. That's output from the AI that even as recent as 10 years ago used to take about two, three weeks to do. So that's minutes versus weeks. That's the kind of productivity that AI Engine can help individual investors do. So what that means is in the old days, even 10 years ago, you really needed a team, passionately trained team in order to do the research. That's why a lot of the institutional grade research used to belong only to the financial institutions, investment banks, because those were the organizations that can afford uh, to hire the best, smartest people working 15 hours, days in order to put out these, uh, sort of a heavy duty industry report. But these days, today with the help of AI, individual investors can get something that's almost as good, not 100% but almost as good as those sort of professionally produced reports back call it 10 years ago. So I think that's sort of the first immediate usage. Obviously with that the caveat is that you got to watch out what the AI output is, right? You know, it does not put out the most accurate information there could be. Hallucination, that's from the AI output. So you got to, you got to check, right? You got to do the reference checks, you got to do the accuracy checks. You got to watch out for those, for those, uh, for those things. But even with that, I think, you know, in terms of productivity, it helps a lot, especially for individual investors these days.

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Speaker D: Thank you very much for that deep entire. You know it for, for those people who understand finance, that deep dive he did, you know, felt like stripping the financial statements back to the trial balance down to the gls. That's the general ledgers to the sub ledgers and to the individual transactions. That, that was great detailed, uh, analysis. So it's interesting you, you seem to have had this really broad and deep experience, competence, skill sets in the world of finance and investment. There's something I always say on the podcast that there is a difference between the good and the great. So what mindset actually separates excellent investors from the merely active investors?

Speaker B: Yeah, that's a, ah, that's a very hard question. I'll try to give my sort of, uh, a, you know, my two cents, my point of view. Oh, I think after this, almost 20 years on wall street, you know, I think the most important critical skill set as an investor is really you want to be, you want to watch out for the, for the pitfalls, right? You don't want to do market timing because honestly nobody can do it. You don't want to, you know, dive into things or invest into things you don't understand because that's how you make mistakes easily. And I think so. Uh, on the flip side really the way to do it is you have a goal, right? You have a clear goal, what you want to achieve, either financial freedom or college education or retirement, what have you. Then you work backwards. Here's my goal in order to achieve that goal. Here are the resources, here's the income I have. How do I go from here to there? You have a clear plan. And then especially for individual investors, we are again back to what I mentioned earlier. We are, most of us, we are working professionals, right. We don't have the time to spend 8, 10 hours a day doing fundamental research on stocks, on options, on derivatives industries. So what do we do? We rely on uh, professionals who do that and manage those things, do those things professionally on a daily basis. And then um, in the meantime, as the individual investor, you have to have, allow for a longer investment horizon. I think that's another really one of the few advantages that we have as individual investors compared to the professional investors.

Speaker D: Right.

Speaker B: This is again coming from my own experience, right? You know, whether or not you are on the investment banking side as analyst covering those public listed companies, or you are a hedge fund portfolio manager or maybe, um, you know, investment, uh, firms, you always have to have short term, near term constraints. You have to be able to compete. You have to report your performance results on a, uh, on a monthly quarterly basis, right? You have to be the market, right. I'm talking about those professional investors. In order to do that, there are a lot of short term actions as a result of those short term constraints and then which lead to sometimes not favorable outcomes. But as individual investors, if you have, have, for example, if you have a retirement plan in 20 years, obviously technically, you have a 20 year investment horizon, right? Then along the way, what you want to do is try to avoid those pitfalls. Try to avoid those emotional, uh, kind of knee jerking actions. Typically, those are the things that are, would kind of be the most detrimental to your kind of performance along the way.

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Speaker D: Interesting. So you actually operate in an industry where trust does everything. How have you intentionally built credibility for yourself and for trust?

Speaker B: Yeah, so I think what we believe in is that we believe in expertise, you know, related to certain topics and certain industries. You know, we are not trying to be the jacks of all trades. Right. We are specialists in, for example, in the data center industry. We're specialists in the, um, you know, retail finance, retail investment industry.

Speaker D: Right.

Speaker B: So, um, we expand, we build on top of those industry expertise. That's kind of a one area to build trust because you Know, for example, using data center clients as an example. Once we have the first couple of conversations, then they know, okay, we had the direct hands on experience managing, developing and then financing data centers all the way from the scratch, um, you know, from the drawings on paper, all the way to execution and delivery to the end customers. So that's kind of a one. In my point of view, the ultimate way to build credibility is really you had the direct experience and then you're helping your clients to achieve, uh, similar things by offering them the insight, advice, recommendations that they do not necessarily have. I think that's ultimately is the way to add credibility and trust. But then, you know, by the end of the day, it's really about delivering results right to your customers. You know, the customers come to you for a reason. For example, if these are investment banking customers, they come to you for, um, strategic advisory services, they come to you for fundraising, either equity or debt. Ultimately we would need to be able to not only help them, right. But also deliver, uh, the result that they are, they are, they are anticipated. So that's kind of the ultimately to build trust.

Speaker D: Interesting. So, uh, what do you think that business leaders are currently underestimating about AI in finance over the next five to ten years?

Speaker B: Uh, that's actually a hard question. I think it's really how to form the AI engines into, from the basic training model, the ll, the large language model.

Speaker D: Right.

Speaker B: The LLM model into specific verticals.

Speaker D: Right.

Speaker B: Train your AI engine smart enough, specialized enough so that it can work much, much smarter and much, much more efficiently, more accurately into those specific industries. So I think that's the next, next layer of the, uh, sort of the adoption of AI because so far AI did not really come out materially until 2020-23. Right. This has been only about three, four years. I think in the first three, four years there's quite a few very famous, uh, household names, AI companies that are building the LLM models, right. The basic training models, the inference models. But I think the beyond that or the next wave of growth, it's really to, you got to have the specialists, right, that can build, then take into the industry knowledge of certain verticals industries, right. And then bundle it with your large language models and then build into essentially sector specialist sort of AI engines, right. You know, be it pharmaceutical, be it legal, be it finance, right. You know, all these, I think that's probably the next wave and then the next sort of a, you know, a world of opportunities would be coming.

Speaker D: So what role do you think that, uh, tokenization 247 trading and real world assets play in this next wave of a financial market.

Speaker B: Yeah, those things that you mentioned, you know, we see a lot of innovations uh, and changes in the market, right. You see some of the uh, very large um, you know the largest exchanges in the world, the US and also in the world are, are adopting uh, sort of the more um, trading hours, be it 245 or 24 7. There might be um, um, some exchanges, large financial organizations that are adopting tokenization of uh, securities. That's all sort of in the works as we speak. I think these financial innovations are definitely the direction of the industry. Because we financial services industry tend to be the industry and because it's one of the most regulated industry, there is a lot of compliance procedures that companies have to figure out in order to put out the most innovative products into the market. Uh, so that's the reason why sometimes people feel that there are a delay between a technology that's available in the market versus a related financial products that can leverage, fully leverage that technology. I think that's part of the reason why. But you know, more and more as we see all those innovations, you know, by, that's adopted by exchanges and frankly regulators. Right. You know, that's a very, very important piece of stakeholder. And then certainly, you know, technology companies all work together sort of to come up with the most innovative design in a compliant way. I think that's sort of the key word in the financial services industry.

Speaker D: Thank you for that. And it makes me curious, what are your thoughts on crypto? Cryptocurrency?

Speaker B: Yeah, um, you know, crypto, obviously it's an interesting, I think I call that a asset class. But I think you know, as individual investors, you know, even, even the institutional investors, right, you gotta, you gotta look out. Obviously it's a lot more volatile than some of the more well established uh, asset classes. But honestly, you know, I think the jury is still out whether or not crypto assets should be part of everyone, individual investors and overall portfolio. I think there's different schools of thought thoughts behind that. But uh, I think it's, it's definitely very interesting. I call that a asset class to continue watching, right? There's a lot of changes, not only just the uh, market prices, but also regulations, the players, the financial institutions, more and more financial. What I can offer is that based on our sort of touch points, right, we see a lot more financial institutions, some of them are our world leading large financial institutions are adopting crypto and then I think that trend continued to change. Right. But Then with that there's the regulation consideration that ah, people are very, very closely watching. And then obviously there's the volatility that people are very, very closely watching. These are all going to be sort of the key factors that would determine where things go.

Speaker D: Amazing, amazing. Uh, brother, you have actually been technically brilliant. Uh, today on the podcast should add a PhD to your CFA and make you a college professor.

Speaker B: I don't know about that, but you know, thank you. Thank you.

Speaker D: Okay. Okay. You're welcome. So when it's all said and done, what do you want your legacy to be? When it's all said and done, what do you want your legacy to be? And you know, what do you hope that trade desk would have achieved or become known for?

Speaker B: So I think we definitely want to be, as I mentioned earlier, so we are proud to be a specialist in the, you know, as a boutique investment bank slash, uh, fintech platform. So we think we you know, know certain niche area in the market to name a, to name a couple, the data centers, the digital infrastructure. I think once we you know, we want, definitely wanted to continue to build up our presence, our um, brand in, in that area and also on the fintech side, uh, we wanted to continue to kind of grow and build up in, in that area as well. Think in order. Again, we're not trying to be the jacks of all trade. Right. We want to be a industry specialist that know our area well, that can help clients specifically on their needs and add value along the way.

Speaker D: That's what we would like to be uh, interested. So ah, at the end of the podcast, I have a tradition. You have to tell me one guest whose body of work you respect and you would invite to be on the podcast.

Speaker B: Uh, sure, you know, absolutely. The Federal Reserve is one of the most important institutions in the financial services industry. We just had a new chairman of the Federal Reserve. If there's the opportunity to invite him, Mr. M. To invite him over on the path on the podcast, I would say that would be uh, uh, an amazing addition and guest to uh, talk about all issues in the financial services industry.

Speaker D: Okay, interesting, interesting. You need to make that introduction happen on LinkedIn. I will keep uh, in touch with you here about that. So we are now down to the quick fire round. Five questions, quick answers. Are you ready to rumble?

Speaker B: Let's go. Good question. I would say specifically relate to the financial services industry heading. Before I kind of ah, became part of the financial services industry, my assumption or understanding is that this is a super efficient market. Market, right. Everything all Stones have been turned. Right. All opportunities have been exploit. Uh, not exploit, have been sort of researched by all the participants. But as it turned out, there continued to be a lot of inefficiencies in the market. Right. So that's one thing I would say I continue to. That's kind of I changed along the way, but I continue to believe that's the case. So that that's where, you know, there's new innovations, new companies that continue to sort of take advantage of that.

Speaker D: What?

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Speaker B: and like a whole community, it's a club.

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Speaker B: Oh, um, yeah. Come join us.

Speaker D: Sam's Club is the best piece of advice that you have ever received from someone.

Speaker B: Find a, uh, mentor. So this is something that we literally we have received from day one in business school at nyu. Find a mentor. This can doesn't have to be someone that's 20 years older than you, can be a couple of years older than you, your senior, you know, kind of MBA student or maybe college or maybe alumni that went into the workforce a couple of years ago. Obviously it could be senior executive in whatever industry that you're in. But you know, by talking to these people, they can offer you advice that could help you substantially along the way, help you avoid wasting time, help you avoid pitfalls along the way, either in investing or in, in career planning. So those are, I uh, would say a very, very important piece of it that.

Speaker D: What is a book you read that transformed your thinking?

Speaker B: Wow, this is a, uh, that's a good one, one. So I think the one book that I read, it's really about Warren Buffett, you know, how he came about, about his sort of his entire life, how he became from a, um, you know, all the way from a young child, uh, got into business very earlier in his career and then went into business school, went into the uh, investment world and for the, for six decades or longer. I think that's one book that really um, offered me a lot of insight, uh, of the career choices that he has made, um, and the investment choices that he has made. I think that's, that's really, really beneficial to um, to my, um, to my uh, my, my own career and, and, and thinking and growth.

Speaker D: Interesting. So what is one habit that contributes very much to your success? Ah, habits. You know, human beings are creatures of habits. What is one habit that has contributed the most to your success?

Speaker B: I think always keep open minded, always keep curiosity city. Because no matter how much education you have, no matter how much professional experience you have, no matter how high your title is, there are always new things that you uh, don't know. And there is also saying that you don't know what you don't know. Right. So always keep that in mind. There are always new innovations, new technology, new ideas, new people. Um, so, you know, these are the things that I would say, you know, keep that as a habit. That would only be beneficial.

Speaker D: I mean, so the uh, last question is, what is one message, one final message that you have for future leaders building at the intersection of finance, technology and trust?

Speaker B: One piece of advice, find the best and the smartest partners that you have. You know, only working with the best people, the best team that can help elevate you can do more than what you can uh, by yourself is hopefully, you know, it's a one plus one one equals to one type of uh, setup. But always work with the uh, best and the brightest. I think that's sort of a, probably the most important shortcut, uh, or message that I would send.

Speaker D: I love that. You know, while I was at PwC, PwC used to boast of the fact that they only employ the best and the brightest. You know, it's quite an elite club to be part of and of course I think amongst podcast guests as well, you have, have actually proven yourself today to be brilliant and to be bright as well. A very, very big thank you to Hugh Eric Chu. And how can the audience uh, get to find you or engage with your body of sure.

Speaker B: Uh, so you can find us at our website, company website www.tradedesk.co or you can find me on LinkedIn. Just look up Eric Chu under Trade desk. I think these are probably the two most, uh, the best ways to reach me.

Speaker D: We will add those to the descriptions section. So thank you very much. And once again, I can only say, anytime a person shares a time with you, they're sharing their life with you. Because the SI unit for measuring life is time. And to the audience, uh, you know what to do, share, like, subscribe and, uh, support the show. So always go for something in your lives. Conceive, believe, struggle, thrive and achieve. Uh, for me, it is goodbye. And of course, from the man, the myth and the legend, student Professor Eric Chu, cfa. It is also a good path.

Speaker B: Thank you very much. Have a good one.