S1|Ep66 Wealth Management 2.0: The AI-Powered Investment Revolution No One is Talking About

Let’s dive into the next generation of Wealth Management and discuss The AI-Powered Investment Revolution No One is Talking About, together with Stijn Ceelen (Belgium), a Seasoned & result-driven C-level leader in Banking & WealthTech, Managing Director, CEO of Alkiemist Advisors, Advisory Board Member (Banque Thaler (Genève, Zwitserland)), COHERRA (Copenhagen, Denmark and others), Chief Investment Officer of a single family office. 

Key Topics Covered:

✔ AI in Wealth Management: Key trends, disruptions, and what the future holds for asset managers, banks, and investors

✔ How AI is Redefining Financial Strategy: From high-net-worth exclusivity to the democratization of smart investing

✔ Bridging Traditional Finance and Digital Assets: AI’s role in connecting stocks, bonds, cryptocurrencies, and tokenized assets

✔ Top Investor Pain Points: What challenges investors face today - and how AI is solving them

✔ AI-Powered Risk Management and Decision Support: Handling market volatility in both traditional and crypto sectors

✔ Next-Gen AI Wealth Solutions: An exclusive look into a tested AI-driven wealth management system and what makes it innovative

✔ The Human and AI Advisor Model: Will financial advisors stay relevant in the era of predictive and personalized AI?

✔ Emerging Trends (2025–2030): Wealth preservation, tax optimization, asset allocation, and how AI reshapes each layer

✔ Actionable Advice for Financial Professionals: What investors and advisors need to unlearn, embrace, and build for the AI-powered future

Connect with Stijn Ceelen on LinkedIn: https://www.linkedin.com/in/stijnceelen/
Learn more about the CxO Section (Brand Leadership Community, Denmark)

Chapters

• 0:00 Introduction to Digital Transformation and AI
• 2:05 Stijn's Journey in AI-Driven Investments
• 3:54 Trends in AI Wealth Management
• 13:31 Democratizing Financial Strategies
• 17:31 Bridging Traditional Finance and Digital Assets
• 21:44 Pain Points and AI Solutions
• 33:20 AI for Enhanced Risk Assessment
• 37:56 Stijn's AI-Driven Investment Model
• 41:32 Future of AI in Wealth Management
• 47:26 Key Advice and Closing Thoughts

Transcript

Speaker 1: 0:00

Hello and welcome to Digital Transformation and AI for Humans with your host, amy. In this podcast, we delve into how technology intersects with leadership, innovation and, most importantly, the human spirit. Each episode features visionary leaders who understand that at the heart of success is the human touch nurturing a winning mindset, fostering emotional intelligence and building resilient teams. Let's dive into the next generation of wealth management and discuss the AI-powered investment revolution no one is talking about. I'm happy to welcome my fantastic guest from Belgium, stan Seeland. Stan is a seasoned and result-driven C-level leader in banking and wealth tech. Managing director and CEO of Alchemist Advisors, an advisory board member at banks in Switzerland and Denmark and chief investment officer of a single-family office. Welcome, stan. I've been looking to discussing today's topic for a very long time. How are you?

Speaker 2: 1:07

I'm doing fine and really looking forward to this discussion.

Speaker 1: 1:12

Fantastic. Let's start the conversation and transform not just our technologies but our ways of thinking and leading. If you are interested in connecting or collaborating, find more information in the description below, subscribe and stay tuned for more episodes. I'd also love to invite you to get your copy of AI Leadership Compass Unlocking Business Growth and Innovation the definitive guide for leaders and business owners to adapt and thrive in the age of AI and digital transformation. Find the Amazon link in the description below. Stan, let's start this conversation. I would love to hear more about your journey, about your latest recent achievements, about your vision for the future.

Speaker 2: 2:01

Also looking forward to talk about these kind of things. My latest achievements and I think it will also be one of the topics that we will discuss later in this podcast is in fact that while I was using AI in the early days as a supportive tool to do some of my tasks, basically I was completely intrigued by AI and also machine learning. So basically I wanted to learn more about AI but also how it could help me to detect certain price patterns in the markets and to make some kind of patterns in the markets and to make some kind of predictions about the markets. So basically I jumped into some courses and I developed my own machine learning model just for individual stocks to see what the most potential paths are in the next couple of months and, based on that kind of information, to decide whether or not to invest in that specific stock. But I guess we will talk about it much more in in-depth later in this podcast, but I think if I need to mention one of my biggest achievements, it's that one.

Speaker 1: 3:26

I'm so excited. It sounds absolutely amazing and, of course, I want to hear more about it. So we're going to come back to this topic. As the chief investment officer managing assets for one of the biggest family offices in Europe and a board advisor for one of the Swiss banks, what latest trends and challenges do you see in the AI-driven era of wealth management?

Speaker 2: 3:54

It's basically it's a very, very good question, but I also want to mention, by the way, that the single family office I'm working for has just launched a new private equity fund, basically investing in software companies that embed AI as a driving force in their business. I was also asked to be part of their advice reports and basically they asked me the same question because they have a couple of pillars next to let's call it fintech. They also include medtech industrials, so robotics and stuff like that. But if you talk about AI in fintechs and welltechs, for me one of the biggest strengths is hyper-personalization.

Speaker 2: 4:49

Today, if you go to a bank and you become a client, you always have to go through these standardized risk profile questionnaires. They all look the same and basically in the end, they assign you to a certain risk profile and basically that's it. They don't ask you about personal preferences, they only ask you about how you think about financial markets. But basically, if if I talk about hyper-personalization, it's more about AI analyzing your true risk profile and not your static one, and the difference is a static one is basically asking questions and then, based on the outcome, they will decide what kind of risk profile you have. They will decide what kind of risk profile you have. Your true risk profile is basically based on how you really behave during I don't know market drill downs, but also how you behave for market are pretty, pretty well. So basically they capture how you really behave in the markets instead of asking some questions or hypothetical questions about the markets, and I think it's one of those things that will really contribute to hyper-personalized portfolios. But it's not only risk profile, it's also your spending habits, because spending habits are also not static. They can change throughout your life, and it's these kind of data points. Spending habits are also not static. They can change throughout your life and it's these kinds of data points that can really deliver hyper-personization investors. And then, last but not least, it's also behavioral patterns. It's quite new in AI, but they can really tailor your investment strategies in real time, so how you act as a person, but also how you behave as a person, but also to avoid the typical behavioral biases that we all have. So, rather than relying on traditional portfolio models and most of the time banks offer, per risk profile, a typical portfolio basically you will get a very personalized portfolio that can change throughout your life because, yeah, data owns can can change the way you spend money can change, but also the way you look at risk can change, but also your behavior can can change and basically you will get, yeah, an investment portfolio that will continuously adjust allocations based on market conditions, live events, but also your individual preferences. I think that's one of the biggest shifts. Yeah, I think it was last year. I also followed a course at MIT about AI and one of the professors was doing really research on this kind of hyper-personalization. So today we all use some kind of index, can be the MSCI role. That was the first step. What we see today is that you can also have some personalized indices, but they really want to go one step further. It's like your own inbox of stocks that really fits your personality but also your behavior, and that's something really really new that AI can help us with to develop. So that's one thing. And then, of course and that's a very short shift Now I will talk a little bit more about robo-advisors, because robo-advisors more or less work in the same way as traditional banks.

Speaker 2: 8:41

They try to capture your risk profile and, based on your risk profile, they give you a portfolio and once in a while, this portfolio is I don't know reallocated back to your risk profile, because you always have some kind of market drifts. But what you see today is that these kinds of platforms are becoming much more sophisticated. I think even Betterment Wealthfront. They're really experimenting a lot with AI. They will integrate alternative data sources, taking into account, for instance, sentiment analysis, macroeconomic trends, the geopolitical risks as we face today, just to optimize your investment decisions. So it's making professional-grade wealth management accessible to a much broader audience, reducing the reliance on human advisors for basic financial planning. Then a third one is more on the institutional side, where AI is driving real-time risk management, but also predictive analytics. So wealth managers are leveraging AI to detect market anomalies, hedge against inflation and provide, for instance, much more dynamic asset allocation strategies. So AI is also enhancing tax optimization and estate planning by identifying the most efficient ways to structure investments for long-term wealth preservation.

Speaker 2: 10:18

Now, for me, these are the three most important things I see, and they're very beneficial to all of us. However, all these advancements come with challenges, and the biggest one is, of course, regulatory uncertainty. That remains a key issue, because AI-driven decision-making raises concerns about transparency, and decision-making raises concerns about transparency, accountability, but also complies with investor protection laws, especially in Europe. And what we see today is that regulators are really struggling to keep up with the fast evolution of AI-powered financial tools, which could lead to potential inconsistencies across jurisdictions, because Europe is moving at a different pace than, for instance, the US. But again, we are all global people and we don't want to stick to a single jurisdiction.

Speaker 2: 11:19

The other challenge, in my humble opinion, is data privacy and security, because AI-driven world management relies heavily on personal and financial data, which can make cyber security a major concern, and ensuring that AI models are ethical, unbiased, but also resistant to manipulation will be crucial for maintaining trust in AI-powered investment platforms.

Speaker 2: 11:49

So, at the same time, while AI enhances a lot of automation, I still believe that the human element in wealth management is still critical, especially in Europe, where people are a little bit more conservative. They want to rely on let's call it robotics or AI-driven investment models, but in the end, they still want to talk to human beings, and I think it's a task of human beings to also explain to clients what happened in their portfolios, but also to make the link between the changes in their portfolio compared to the way they behave Some live events or nature live events that could have changed their portfolio allocation, and things like that. I'm always a believer of a hybrid model where AI can help a lot, but in the end end, we're still humans and humans love humans and they still love talking to other human beings.

Speaker 1: 12:51

I absolutely love your developed answer with so many interesting details and explanations, and I totally agree humans are humans and it would be amazing to keep humans front and center, no matter how fast technologies are developing. Let's take a closer look at the accessibility, because you already mentioned it, but I would like to hear more about it. Wealth management has traditionally been reserved for high net worth individuals. How do you see AI making sophisticated financial strategies more accessible to a wider audience?

Speaker 2: 13:31

It will definitely allow let's call it wealth management strategies more accessible to a wider audience. Traditionally, personalized financial planning and advanced investment strategies were reserved for high network individuals, but most of the time due to the cost of human advisors and, of course, if you have a huge portfolio, it's much more easy to to have a certain fee but also to pay for all those human advices. However, ai-driven platforms are really democratizing access by automating complex financial analysis, which was previously done by human beings, but also indeed reducing the costs of let's call it more advanced financial systems and portfolio management systems. And that's what I also said before is you can already see it. You have those AI-powered robo-advisors which offer personalized investment strategies based on real-time data based on your risk tolerance that can change based on certain market circumstances, but also your financial goals that can change based on certain market circumstances, but also your financial goals that can change throughout your life. So you can already see there that portfolios become much more personalized than they were before. These platforms use a lot of machine learning to optimize asset allocation, tax efficiency and rebalancing. It's not only a service anymore for exclusive to private banking clients. It's now already accessible to people that really are starting with investing with a small portfolio.

Speaker 2: 15:16

Another game changer is, of course, the integration of alternative data into AI models.

Speaker 2: 15:22

So, instead of relying only on traditional I don't know credit scores, income levels, ai can assess your financial health using broader data sets, making wealth building strategies more inclusive for those who might not fit the conventional criteria. But again, as I mentioned before, there are pros, but there are always some kind of challenges, and I think one of the biggest challenges is financial literacy, because, basically, if those gaps are still there, it will prevent people users from fully benefiting from AI-driven tools. And the other one is, of course, regulatory oversight. As I mentioned before, you're using personal data points and basically, especially in Europe, there could be some kind of conflict with compliance rules that banks should implement in their systems. So what I believe? In the coming years, ai-driven wealth management is likely to become a more standardized offering, bridging the gap between let's call it ultra-high or high-network individuals, but also everyday investors and those who embrace AI tools early will have access to smarter, more efficient financial planning, which will help them build wealth in ways that were previously out of reach.

Speaker 1: 16:56

That sounds very promising and I like this part of things, but let's keep bridging the gaps. As you already mentioned it, then I want to hear more from you about bridging the gaps intersection between traditional finance and digital assets. How is AI helping bridge the gap between classic investments, like stocks and bonds, and newer asset classes like cryptocurrencies and tokenized assets?

Speaker 2: 17:31

For me, one of the biggest contributions AI is making nowadays is multi-asset portfolio optimization. So traditional investors are now incorporating crypto and tokenized assets alongside stocks and bonds, and AI-driven platforms are helping balance risk and return across different asset classes, and I think that's indeed the main advantage of of ai. So, by analyzing historical correlations, sentiment data and market trends, ai models can adjust allocations dynamically, while before it was more, yeah, statically, not really dynamically. Most of the time, allocations or reallocations were done once a month, once a quarter, which ensures, of course, better diversification while also managing volatility in your portfolio. That's, for me, one of the most important things where AI can contribute. Another one is, of course, predictive analytics. Another one is, of course, predictive analytics. So AI models can process huge amounts of data, including new sentiments, macroeconomic indicators, but also blockchain activity, to forecast market movements across both traditional and digital assets, and this will enable investors to make better and more informed decisions in real time, but also reducing uncertainty and the volatility of cryptocurrencies that we could experience the last couple of weeks. Tokenization, I think, is one of those emerging trends. That is also one of those game changers.

Speaker 2: 19:19

Just let's take the example of private equity. Nowadays, private equity funds are, most of the time only accessible to ultra high network individuals, some private banks. They have some master feeder structure where you can access it from 250,000 euros or dollars whatever, excess it from 250,000 euros or dollars whatever. But basically for smaller investors, private equity was not always accessible unless you buy some listed private equity funds on some of the exchanges, but then again you depend on private equity funds.

Speaker 2: 19:56

Now tokenization could help people to invest directly in private companies that are not listed, so basically, you can easily buy a piece of equity in a private company as well, but it could also allow you to sell your assets much more easily than before. That's also one of the big disadvantages of private equity. Once you commit your capital to a private equity fund, most of the time your money is stuck for 10 to 12 years. With tokenization, you create, in fact, a new secondary market where you could more easily sell some of your shares in private equity funds to other investors. So again, it will democratize investing in general and it will allow also smaller investors to have access to yeah, let's call it asset classes that are nowadays only accessible for high or ultra high net worth individuals.

Speaker 1: 21:06

When I'm listening to you, I'm just thinking about how fast things are changing in the area of wealth management and fintech and fintech and it's not always easy and, of course, it must cause a lot of stress and all those shifts they are pushing you into the new territories. So, stan, I'm thinking what are the biggest pain points investors face in wealth management today? How does AI solve these challenges, and where do you see the most significant improvements happening?

Speaker 2: 21:44

There are a lot of pain points and I think I already mentioned a couple of them. I think the first one is, of course, financial literacy. Now, today, there are still a lot of people not investing, basically because they perceive investing as speculation, while that's not always the case. It depends on how you look at investing. Even trading is not, by definition, speculative. It's just how you look at it. If you define entry levels, stop losses, profit taking levels up front and you stick to your plan, it's not more risky than I don't know doing something else in life. But that's one of the things. It's financial literacy. It's still the misperception about investing and trading. Also, complexity it's not always easy and, to be honest, regulators don't make it always easy to banks and wealth managers because they have to comply with a lot of rules. They have to provide a lot of questionnaires that people need to fill out, not always in plain English or whatever, but basically it's still perceived as very complex.

Speaker 2: 23:04

Then, of course, it's risk management. If you don't have the right risk management tools or you don't have the right risk management attitudes, you can still see that people can lose a lot of money. But it's all related to each other. But it's all related to each other. If you don't have the right degree of financial literacy, then there might be a good chance that you don't have the right risk management tools in place to help you I don't know to manage your own stock portfolio or portfolio, taking into account stocks, bonds, etc. And then, of course, course, fees. Some fees are still way too high, and successful investing also relates to fees. The lower the fees, of course, the higher the returns in in the long run and the more easy you will I don't know you achieve your financial goals. And then, last but not least and I think that's one of the most important parts it's emotional decision making A lot of people that make decisions based on their emotions. They just see the stock market falling a couple of days and they start panicking and they start selling some of their stock positions, probably at the worst timing ever. But that's how it goes. And there's where AI can definitely help, because it can automate processes, it can enhance data-driven decision-making instead of emotional decision-making, and it can also make much more sophisticated strategies more accessible to a wider range of investors, as I mentioned before.

Speaker 2: 24:48

So for me, one of the major issues is, of course, the complexity of managing a diverse portfolio, especially as investors look to balance traditional assets, like stocks and bonds, with newer asset classes such as crypto, tokenized private equity and other tokenized assets. And AI can simplify this by providing real-time portfolio optimization, continuously analyzing risks, adjusting allocations based on market conditions, but also your personal risk preferences. And that's what we already see is that AI-powered robo-advisors are making it much more easy for everyday investors to access dynamic asset allocations, once they are reserved for higher network individuals, once reserved for higher net worth individuals. The other one that I mentioned was risk management and volatility, especially in unpredictable markets, and the good thing about AI models is that they can analyze a lot of financial data, new sentiments, macroeconomic indicators, also to detect risks before they even escalate. And it's those advanced AI-driven tools that can help hedge against downturns by identifying optimal risk-adjusted investment opportunities. So if an AI model tells you, okay, there's a higher risk of a severe market drawdown, then it can also suggest maybe to go out a little bit more out of equities to balance your portfolio more toward bonds or even cash. But also when it detects that let's say, okay, there is a very negative sentiment and the negative sentiment is potting out, it can also tell you. Now it's time maybe to buy stocks again in your portfolio.

Speaker 2: 26:43

And then the third one was, of course, fees, so high fees, but also inefficiencies in wealth management services. So traditional financial advisors and portfolio managers. They charge significant fees, often making sophisticated financial planning inaccessible to smaller investors, and ai platforms can reduce these costs by automating portfolio rebalancing, tax loss harvesting and other high value services. So I can definitely add a lot to the table for more investors. And then, as I mentioned, it's all about emotional investing, and that's also why I developed my own machine learning model, because it takes the emotions out of the equation. We're still human beings. I know that machine learning models they don't have the same capacity of the human brain. Humans are still smarter than most machine learning models. The only thing what machine learning models don't have are emotions, and it's most of the time our emotions that can really ruin our performance in the long run. So relying on those kind of new models can help you to take your emotions out of the equation and to have much better investment results in the long run much better investment results in the long run.

Speaker 1: 28:10

I'm thinking it's definitely not obvious to incorporate the stoic principles into your investment habits and strategies. And of course, we are emotional creatures and we are prone to feel the pain when we see our assets just melting in front of our eyes. So the rule buy on red and sell on green just disappears. It gets out of picture when sometimes you see what's going on. So this is definitely something really good to hand it over to the technologies, which have no emotions and human thing of audience mechanisms that kick in whenever we see a red number and uh, and that's.

Speaker 2: 29:02

And that's the problem. It it's emotions are taking over the rational decision-making process and basically we become blind of all the alternatives there are and the only thing that we want to do is avoid pain. And the best thing to avoid pain at this moment is just to hit the sell button. But from a rational point of view, and most of the time when the rational decision making process kicks in again, then we start realizing like oh, I made a mistake, why did I sell? But it's clear, it's just the pain avoidance mechanisms in our brains that are making us blind for all the potential paths that the equity market could have. We are only seeing one path and that's going down. And yeah, the best thing to avoid pain at that moment is to, as I've told you, is to to hit the, the cell button just get rid of the pain and then you will get better, but unfortunately, it gets only worse oftentimes.

Speaker 1: 30:07

so, yes, and about connecting back to the literacy, because when you are lacking knowledge, lacking experience, and those emotions are so overwhelming, of course, it is easier to take wrong steps and move in the wrong direction, and that's why so many hit the liquidation point recently, because the market has been so volatile as well.

Speaker 2: 30:40

Yeah, but it also has to do with our beliefs. Basically, most people start investing believing that markets are only going up. But basically, from the moment that you buy a stock, you should be aware of um of the risks and you should be aware that from that point the market can go in any direction. And then the other one is because it's also something here a lot is that people say something like yeah, the market is against me. No, the market is quite I don't know neutral in that respect.

Speaker 2: 31:16

The market is not against you, but it just means that people are fighting the markets and they're not taking responsibility for their own investments. It's like if you hit the buy button, it's your responsibility and you have to take responsibility and you have to and you have to take in mind that the market can go in any direction at that moment. And if you truly incorporate the belief that the market can go, is first of all neutral, can go in any direction, and that investing even I don't know bond investing is risky business, then of course you will be able to to neutralize your emotions a little bit better. But we are human and emotions can always take or can suddenly boil up. But then again, just walk away, don't do anything in your portfolio if you feel your emotions are getting too strong.

Speaker 1: 32:25

That's a really good advice, and it makes me think about one of my friends' philosophy, and he's saying if you are not ready to lose, don't invest. Invest only what you are ready to lose, because the market can go in any direction, and that's how it is. Markets, both traditional and crypto, can be unpredictable, and we've already discussed a lot of this. But how does AI enhance risk assessment and help investors make more informed decisions while balancing volatility, if we take a look at the situation where we are still in the driver's seat as human beings, and AI is some kind of support mechanism without giving over all decision power?

Speaker 2: 33:21

If I look at AI and its biggest advantages. Ai and its biggest advantages it's the ability to analyze not only historical but also real-time market data to detect trends and anomalies. If you just look at traditional risk models, they often rely on static indicators, but AI, in fact, is continuously learning from evolving market conditions, making it more effective in predicting downturns, price swings, but those even I don't want to call it black swan events, but major, major markets downturns, because AI can scan financial reports, economic data, even alternative data sources like social media sentiments, in such a quick way that it can assess risk from multiple angles and provide investors with early warning signs before the market shifts occur, with early warning signs before the market shifts occur. And so, while traditional risk management is more based on static data, most of the time only looking at historical prices, ai can do much, much more, can use much more data sources, but also learns from certain evolutions, so it's constantly learning from its own outputs. So that's why I believe that AI is definitely a big contributor to risk management. But also, what I said is that AI can also optimize your portfolios much, much quicker. Instead of using simple diversification rules, ai-driven models can adjust investment strategies dynamically, not statically based on market sentiments, also macroeconomic indicators, even liquidity conditions, and this allows investors to balance risk and return more effectively, whether they're trading equities bonds or even digital assets trading equities bonds or even our digital assets. Now, if it comes to crypto markets, which are definitely more volatile even more volatile than equity markets I think ai can can play even a bigger role. It's like all those ai power trading bots and automated risk management systems help mitigate sudden price swings by executing stop-loss strategies, detecting potential pump and dump schemes, but even predicting market movements, based on blockchain analytics. So, basically, ai can use much more data in real time and can use a model that is learning continuously from its own outputs and gives us much better insights in the risk, or what's called implicit risks, in the markets.

Speaker 2: 36:18

Another key area where AI is making quite big impact is what I also told you is behavioral risk management. So many investors make emotional decisions. They're panic-stalling during downturns or they chase in hype-driven rallies. Think about all those meme stocks, but also meme points. People get in at the top and then suddenly they lose a lot of money when uh, when it is uh dance and those, those ai driven tools. They provide data-backed insights to help investors stay disciplined and avoid a cost of mistake. So, basically, ai is taking care of your rational minds and helping you that your emotional mind is not taking over. So, ultimately, ai is not eliminating risk, but it's helping investors manage it more effectively. And, by offering real-time risk assessments, dynamic portfolio adjustments and predictive analytics, ai empowers investors to make smarter, more informed decisions, even in highly unpredictable markets.

Speaker 1: 37:36

Sounds dreamlike, so I feel that we can't wait any longer. Stan, could you tell us about your AI-driven wealth management solution that you developed and successfully tested? What makes it unique and how does it improve investment decision making?

Speaker 2: 37:56

I don't know if it is unique, but at least it helps me to make some decisions. So, basically, it is a momentum-based machine learning model, so based on let's call it, the stock evolution that. I give you an example nvidia. Based on the price patterns in the past, it gives me a couple of indicators. It's not giving me one future price in the future. No, I want the model to give me a range of future price points in the future with the highest probability.

Speaker 2: 38:36

So it is using different paths, giving me different potential outputs and based on the outputs, I just define okay, what is now the median, what is the skew? And I prefer stocks with, of course, a positive median return, but also with a high positive skew, because it means that the model is predicting even scenarios where the price has a much higher probability to end up above the median results. So that's how I select stocks. So I'm not using a model that gives me one data point, because models can be wrong as well. But it is built in such a way that it gives me a potential of the most likely path in the next coming three to six months and, based on these outputs, I just can calculate okay, what is the most likely scenario. That's a median, but also it has much more upward potential than what the median suggests potential than what the median suggests. And based on those numbers, it gives me some insights whether to buy or not to buy stock in portfolio.

Speaker 1: 39:54

Smart sounds really good. I wonder is it your secret weapon and you're using it just on your own, or are you sharing it somehow with the world? Are you using?

Speaker 2: 40:07

it just on your own or are you sharing it somehow with the world? No, it's just my secret weapon. I'm not commercializing at the moment, I'm just using it together with some other models I'm using. So one of them is, of course, the model to see which stocks could be bought. But then again, I still do a technical analysis on all the selected stocks, because ai can be wrong as well. But at the same time, I'm also using some some other, what I call my market bottle model, just to see what kind of bubble score each of these stocks have, which is a completely different. And just the combination of all the models gives me some very good insights whether to buy and not a certain stock.

Speaker 1: 40:56

Sounds so good. Congratulations. It's fantastic that you are using all the opportunities and technological advancements to succeed in your role and grow your and others' assets. Stan, with AI-driven advisors and predictive analytics, how close are we to fully personalized, ai-powered wealth management? Will human advisors still play a key role, or will they stay relevant in this game at all?

Speaker 2: 41:32

um, first of all, how close we are. I think pretty close, to be honest. I think we are really fast approaching a future where ai powered wealth management is highly personalized, which can offer tiered investment strategies, real-time risk assessments Just look at me. I just built a model myself. I also know companies that are really focusing on risk models, taking into account a lot of data points and making I don't know risk preferences much more natural than the static risk questionnaires that most traditional banks are still using. But again, also, banks are not just sitting there Basically, they're also working on these kind of things and most of the time I also mentioned it before if you have those robo-advisors using AI to dynamically adjust your portfolio, taking into account your risk tolerance and all these kind of things, I think we're pretty close to a world where a lot of decisions are automated and based on your financial goals, your risk tolerance and of also market conditions. I think we're not that far away from a world where AI can play a huge role in wealth management.

Speaker 2: 42:57

Now, to answer your question about human beings, again, I believe that advisors still play a very important role, but of course, their function will completely change and will evolve. Ai in contradiction with a typical human being can process a lot of data, can execute trades with precision, but also it lacks human touch. And sometimes, if you need to talk about complex financial planning, trust building but also helping people navigate major life decisions, I think that's one of the most important roles for human beings and you can still see it, it's like high network individuals. They rely heavily on human relations because they know it's like empathy is still this kind of human characteristics. It's not a characteristic that I've already seen in AI and it's that human empathy that can make a huge difference and that's why I truly believe it will be a more hybrid system where AI can do a lot of analytics, but again, we still need to rely on human beings, especially for the empathy angle.

Speaker 1: 44:28

Exciting times ahead and really empathy I'm so happy that you are mentioning it because it is crucial and human centricity. It is everything. No matter how strong technologies we have, it is made by humans, for humans, so it is really important to keep it human centric. Let's fast forward this story and look ahead, Continuing our futuristic discussion. What are the biggest trends in AI-driven wealth management over the next three to five years? What role in wealth preservation, growth or even taxation strategies will GenAI play over time?

Speaker 2: 45:23

Yeah, basically, I will just repeat what I told you before. I think one of the most significant shifts will be the move to hyper-personalized investing, where AI will tailor portfolios in real time based on your individual financial goals, your risk tolerance, market conditions, even behavioral patterns. So, unlike static portfolio models as we still see them in the market today, ai-driven strategies will continuously adjust allocations, ensuring optimal performance in both wealth growth and preservation. Another major trend and it's also something that we discussed during this podcast is advanced risk management and hedging strategies. So AI is already improving risk assessments by analyzing alternative data sources not only market data, but also macroeconomic trends, geopolitical risks, but also real-time investor sentiments and I'm not talking about the CNN fear and greed index, which is still based on market data. No, I'm here talking about what people are saying on social media about investing, so the true investor sentiments. That's one of the things that AI can easily capture.

Speaker 2: 46:42

In the coming years, I believe, ai will provide more predictive risk analysis, allowing investors to make adjustments before market downturns occur. So it will warn you about a potential market drawdown, so then you don't have to wait until it happens and then start panicking and pushing the sell button. Ai can help you in doing that, and it will also indeed be very valuable in preserving wealth during volatile economic cycles. And then, last but not least, ai will also play a bigger role in tax optimization. Instead of simply managing investments, ai-driven systems will analyze tax laws, track capital gains just tax-efficient trading and asset allocation strategies in real time. Nowadays it's not really implemented, but I guess if AI knows the rules that it can easily say okay, maybe it's better to sell this stock instead of that stock, because then you will have lower capital gain, just minimizing the tax impact of allocation decisions in your portfolio.

Speaker 2: 47:56

So features like automated tax loss harvesting, cross-border tax planning, I think will become much more sophisticated, helping investors maximize after-tax returns with minimal manual inputs. So I definitely think that AI can make a huge difference in those three domains.

Speaker 1: 48:16

Thank you for sharing with us your vision. I see the future is bright and I'm sure many listeners and viewers are going to recognize those patterns and get a chance to prepare better to what's next to come. If you could give one piece of advice to investors and financial professionals preparing for the AI-driven future of wealth management, what would it be?

Speaker 2: 49:06

I think the advice I'm going to give is maybe a little boring to your audience, but maybe some new people will listen in as well. But for me, the most important advice is to embrace AI as a tool and not a threat. I think the future of wealth management will be defined by those who leverage AI to enhance decision-making, optimize risk management and provide hyper-personalized financial strategies. Investors, but also financial professionals, who integrate AI into their workflows will definitely gain a competitive edge. I know AI can process a lot of data at a huge scale, but at the same time, don't rely only on AI, so also the human insight remains invaluable.

Speaker 2: 50:09

I told you before, ai doesn't show any empathy, but for me, the key is to strike the right balance. So let's embrace AI. Don don't fight it, but embrace it. And let ai handle data, heavy tasks, automate certain strategies, while human beings can focus on strategic thinking, client relationships and long-term financial planning. So again, those who continuously adapt, learn, but also integrate ai driven models will not only stay relevant but, honestly, they will thrive in this fast evolving financial landscape it's all about balance and wisdom.

Speaker 1: 50:59

Thank you so much for sharing your advice and I couldn't agree more. It's been such a pleasure having today's conversation. I'm sure our listeners and viewers are going to apply your golden nuggets in their practice and get in place those pieces which are probably missing and bridge all the gaps to succeed in the future. So thank you so much for being here today and sharing with us all your experience and those invaluable vision and advice.

Speaker 2: 51:41

Thank you for inviting me. You're more than welcome.

Speaker 1: 51:46

I just want to remind that there are many other episodes where Stan is sharing his experience and his advice with all of us, so you are very welcome to go through the list of episodes and find those touching the topics of fintech, banking technologies and wealth management, and you can find more advice and wisdom from Stan in those episodes. Thank you for joining us on Digital Transformation and AI for Humans. I am Amy and it was enriching to share this time with you. Remember, the core of any transformation lies in our human nature how we think, feel and connect with others. It is about enhancing our emotional intelligence, embracing a willing mindset and connect with others. It is about enhancing our emotional intelligence, embracing a willing mindset and leading with empathy and insight. Subscribe and stay tuned for more episodes where we uncover the latest trends in digital business and explore the human side of technology and leadership. Until next time, keep nurturing your mind, fostering your connections and leading with heart.