#31 Volodymyr Gubskyi - Optimizing Structured Products

The Nalu Finance Podcast

In this episode of Nalu Finance, we sit down with Volodymyr Gubskyi, Co-Founder and CEO of IVM Markets, to explore the evolving landscape of structured products design.

Volodymyr shares expert insights from 17 years in derivatives and structured solutions, including:

• Why structured products offer unique advantages in portfolio construction
  

• How tools and technology can uncover the optimal payout structure
  

• Why simplicity and clarity are key when communicating complex instruments
  

• How to balance customization with investor understanding and transparency
  

He also reflects on lessons from his time at Deutsche Bank and Merrill Lynch, and how IVM Markets is reshaping access to structured products.

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🎙️ Transcript:

Volodymyr Gubskyi: 00:11 There is a joke in the FX market. If a client came to you as a reverse inquiry, it means you already lost money. So don't even bother replying, actually.

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Stefan Wagner: 00:45 I'm here with Volod Gubskyi, co-founder and CEO of IVM Markets. IVM Markets provides independent structured product suite with direct access to structured product investment content. What I find most fascinating about the IVM solution is its ability to track the pricing of executed structured products across all platform users and leverage this data to enhance the accuracy of new product pricing. This feature is beyond the scope of any individual client and highlights the unique value of the IVM platform. Let's jump right in and ask you, you know, what motivated you to establish IVM Markets?

Volodymyr Gubskyi: 01:27 Hey, so great to be here. So what motivated me to start IVM was I always had a vision that equity structure products, they could be the ultimate vehicle for personalized investing. But over my nearly 20 year career in bulge bracket banks, I noticed that the big banks are much more interested in doing copy-paste industrialized issuance of the same thing over and over again.

Furthermore, the people who are best placed to create all this personalization, like the distributors, they don't have the right tools to optimize thousands and thousands of variations for every client every time there is a deal. So myself and my co-founder, we left Deutsche Bank to establish IVM, where we decided to put all the investment idea generation use cases for structured products into an online portal, which would be completely off the shelf and would empower the 200,000 financial distributors to provide a better service to their retail and high net worth clients.

Stefan Wagner: 02:41 So if I would ask you just what would be the top three benefits be of using IBM solutions by a structured products provider, high net worth or wealth management office or family office?

Volodymyr Gubskyi: 02:55 Sure. So an overarching benefit would be to transform your business from a copy paste sales approach to a personalized approach to structured products. But more specifically, three things. Number one, you can log in and immediately generate out of hundreds of possible variations, you can find top three best ideas in terms of highest coupon for a specific theme, like energy. We empower you to actually try those variations and don't cut your alpha just because you don't have time. Number two, the same thing but when you are generating role ideas, when you have an auto-call or a maturity. The final one is negotiate for higher coupons for your clients.

Stefan Wagner: 03:48 Can you maybe give an example how, I think you mentioned something on finding the best coupon, but there's obviously also other features that might determine what the best solution is for the client. Do you maybe have an example?

Volodymyr Gubskyi: 04:02 Yeah, sure. So imagine a client calls you and says, show me something in energy. And you're like, what should I show you? I don't know, maybe some income. Okay. Do you know which stocks you like? No. Do you know which maturity you want? No. Alternatively, the client actually says, yes, here are my 10 stocks, what do I do? Actually, most people, because they don't have tools, they don't realize that even from a short list of 10 blue chips, if you then maybe also throw in like three different maturities, one, two, three years, there's like a hundred combinations available. And the coupon disparity is not going to be 2%. It might be 10%, right? Even if you're operating just with 10 energy blue chips, for example, right? So in IBM, with like two clicks, you go from energy to the most optimal baskets to then in one minute seeing a grid of a bunch of optimal baskets, which are different between each other. We give you a broad menu, not just that one most volatile stock in all the baskets. And which one is better? One, two, three years. And you might actually be surprised that two years will have the highest coupon instead of three years and one year. All of that process manually, A, just nobody does, and they only pretend like they look for a best idea, or two, they do, but it takes them all day. In a game, you could do it in one minute.

Stefan Wagner: 05:39 And which is what, for example, these multi-issue platforms don't offer you. You can't go in there and start different iterations, or at least that's usually very, very difficult. If I get this right, and correct me if I'm wrong, IBM produces a price, yeah? But that's not a tradable price. The tradable price you can still only get from a bank or a structured products issuer, in a sense. How do you ensure that the price or the iterations on which the price is then based on coupons, maturity and everything else is actually as close as possible as it will be if when you start actually going out and asking the banks for a price that you can execute.

Volodymyr Gubskyi: 06:21 Yeah, this is a very important point. And this is the critical piece of our technology. So this is something quite proprietary, which we managed to build. Now, if we produced all those like hundreds and hundreds of iterations, but the end result, the prices were off by 4-5% in terms of coupon, they're basically totally useless, right? Because you go to banks, either you discover that the coupons were much higher, so you should have pushed further, or you discover the coupons were much lower, so you wasted your time.

So we actually, over several years, built a technology where, firstly, it's completely off the shelf, right? So the user doesn't need to think. All the trader adjustments are already done, unlike, for example, in some of these, you know, let's call them legacy quant libraries, right? Where they give you a calculator, but you need to run, you need to have a team of traders in-house to make all the trader adjustments. Right so all of that is already done in IVM but number two how do you go from let's call it a kind of walk away risky price to a price that matches each specific best bank for each specific basket, because for basket one, Goldman can be the best, but for basket two, Citi can be the best and Goldman the worst, right? So in IVM, our hundreds of variations across baskets and maturities are calibrated to the best bank risk appetite.

So this we achieve by collecting data across all of our users and also exchanges on executed transactions. Right. And then using those to recalibrate our spreads from offer on a regular basis. Right. So this way we actually capture the best risk appetite for each basket and maturity etc. Now we are never going to be the same as asking a trader but If you do a lot of ideation, you know that you're not supposed to ping a trader when you are trying things out. In fact, they get very angry if you try too many things. And this is what differentiates a high-quality salesperson from what I call copy-paste sales.

So you're supposed to try hundreds of variations by yourself and go to the trader with two. And now you also raised the point about multi-issuer platforms. So once you find those two, go to a multi-issuer platform if you have one. And we can, in fact, integrate with it as well. So you do 50 or 100 variations in a space of a minute in IBM, get two, and we can send them to your multi-issuer platform also.

Stefan Wagner: 09:20 Ah, I see. Is there other platforms you also implement with besides multi-issue platforms, like do lifecycle event monitoring or… Yeah, so exactly.

Volodymyr Gubskyi: 09:31 So we see IBM as a complement to pretty much all the platforms that are out there. So talking about lifecycle, again, very typical situation. So you are using one of the lifecycle platforms, I don't know, Luma or Lexi Field, which are very good in my opinion, right? But you get an auto-call notification and what do you do with it? Or the platform tells you, oh yeah, you are 30% underwater. Great. So at this point, you leave the platform and you go and send an email to the banks, show me some ideas, right? But then that part of the process doesn't work.

In IBM, you can actually store a replica of your portfolio, which is sitting in your lifecycle platform. And when you have ICNXYZ with a Noto call, with two clicks, you go to ICNXYZ in IBM and you fresh it to today, and you blow it up to a grid of optimal ideas again with two clicks. Right. You might stay in the same industry. You might change the industry because you are not bullish energy anymore. Now you are more bullish consumer discretionary. Right. And again, you know, 50 optimal baskets. You have a broad menu of maybe five with the best coupon across different maturities.

Stefan Wagner: 10:54 One other thing I want to touch on this is a little bit, you know, there's one criticism for structural products is often sort of it's complex. legal language that is used. I mean, I always made the joke when I was working also on that side, they know who actually reads these 50 page pricing supplements. I mean, but do you have something that helps as well people to better understand it? Because I think the beauty about the structure product is very predetermined what the payout will be. So it should be actually quite easy to understand. But then comes this huge amount of legal language. And you basically on page three, you give up of, you know, you give up the will to live of reading this.

Volodymyr Gubskyi: 11:32 Yeah, absolutely. But here there's even a more important question, basically. So first point, very complicated legal language, even forget about the pricing supplement, take the term sheet. Every term sheet is like four or five pages long, right? Now multiply this by 20 issuers, right? And by how many products, because each issuer likes to have their own way of awarding things, right? Obviously. And then the final problem is that the same product might be described differently or you might end up thinking that there are hundreds of thousands of products.

But actually, that's totally wrong. There are maybe four products and everything else is the basic product with a feature added to it. The feature can be described in one line because you say, this is an auto-call with feature one. This is not a call with feature two. So this is how our human language module works. If you are constantly using IBM to generate ideas, next to every single product that you are pricing, there is always a human language description. And then you end up seeing like four products, Auto Call, Principal Protected Note, Callable Principal Protected Note, and Non-Callable Growth or Income Note. But then you take the auto-callable product, and at the bottom, you see a whole bunch of features that you can add, each feature described in one line.

So in fact, when you're adding and removing features, you're not supposed to re-read the whole term sheet. It's irrelevant. You're supposed to think of these products as Legos. So you've got your Christmas tree and you're just putting on different toys on top of it. But this you only start to realize either A, if you are a complete expert, which most people are not, or it takes too much time to become one. Instead, if you're familiar with the basic product with pretty much everybody is, then you start to think in terms of features, each of them described in one line.

Then once you've finished generating the product, with one click of a button, we produce for you a summary which can fit in a WhatsApp message. We have this for every single product. That's cool. You might argue, why do I need it if I have a multi-issue platform? Okay, you might not use it to get quotes, but you might use it to share with your colleagues, a product person, because if you came up with an idea, adding and removing features, it's nice to have a very simple summary.

Stefan Wagner: 14:16 That's excellent. No, I mean, that's absolutely brilliant. You see a lot out there that's happening. You clearly see what all the users are pricing with your tool and which ones they're then also submitting for a execution price with the issuers. What kind of sort of trends do you see? Maybe even if you can distinguish it between the US, Asia and Europe?

Volodymyr Gubskyi: 14:40 Yeah, yeah, absolutely. So there are a number of trends. and they all kind of related to each other. But the main trend is digitalization, right? And there is very substantial growth that we are seeing as a result of multi-issuer platforms. So this is similar to when FX derivatives went electronic. So that's what's happening in structured products. In the U.S., the market was very, very small, but now it's growing like 100 percent per year. But it's still 100 billion of new issuance, new issuance per year as compared to like Europe at 500 billion and Asia at six or seven hundred billion new issuance per year in a seven trillion market. In Europe and Asia, the market is growing 30 percent, but the brokerage margins are dropping like a stone.

Why? It's exactly the same story like in the facts. And in the facts, basically, as soon as you went electronic over a number of years, the margin broker margins went to zero, zero or even negative in some points where you have too many brokers competing. In fact, there is a joke in the effects market. If a client came to you as a reverse inquiry, it means you already lost money. So don't even bother replying, actually. Right. But even in the facts. There are other people who do make money and they're growing the business, the clients are very happy, you know, the clients make money, you make money, but only if you're providing ultimate personalization.

Right. And unfortunately, what we are seeing in the equity structure product space is that some brokers, wealth managers, They already agree with us that you either need to become a multi-issuer platform yourself, not even rent one, but become one. You need to be the platform owner or you need to provide intellectual value. Otherwise, your clients are just going to leave over a number of years or you will make zero. But maybe 70 percent of the brokers and wealth managers still argue very strongly. What's the point of generating ideas? I'll just sit on my reverse inquiry. But I mean, I think that they will be very surprised when their clients will start leaving soon, basically.

So this is a very, very major trend. At the same time, what is amazing, you know, let's call it the sort of 30, 40 percent of the people who get it. They are complaining very adamantly about lack of software. This is the problem that we are trying to solve. And finally, there's a lot of talk about using AI to find the most optimal product for the client. So one idea that we are working on is basically don't ask the client what they want, download their portfolio, and have IBM formalize what products would be relevant.

And what is quite interesting, all that sort of human language model that we built just to describe products, turns out it speaks extremely well to AI. And AI is already able to understand our language, right? And based on that, you know, suggest similar products to the client's existing portfolios.

Stefan Wagner: 18:11 That's brilliant. Last question always, you know, Very insightful, Vlad. Thank you very much. I very much appreciate you taking the time. But if somebody else would like to get in contact with you, what's what is the best way to get in touch with you?

Volodymyr Gubskyi: 18:24 Sure. So the best way would be to write to me on LinkedIn. Literally drop me a message directly. I'll reply very fast.

Stefan Wagner: 18:32 And the website is IVMMarkets.com, isn't it?

Volodymyr Gubskyi: 18:36 IVMMarkets.com. Correct. Excellent. Thank you very much, Vlad. Thank you very much.