IVM Markets – advancing the pre-auction process

IVM Markets was launched in 2018 by CEO Volodymyr Gubskyi (below) and CTO Ildar Farkhshatov (pictured), two former structured products bankers with close to 20-year experience spanning across Merrill Lynch, RBS and Deutsche Bank. Its AI SaaS Structured Product Suite aims to shift the power dynamic between issuers and distributors allowing the buy-side to find the most optimal structured product idea for their client’s portfolios before engaging with manufacturers for issuance.

Our AI powered search and recommendation engine can create more and better-quality idea flow for all the players in the structured products value chain - Volodymyr Gubskyi

The company’s software has a subscription-based fee model and is tailored to the needs of multi-issuer platforms, brokers, private banks, insurance providers, asset managers, advisors & wealth managers.

“Our AI powered search and recommendation engine can create more and better-quality idea flow for all the players in the structured products value chain,” said Gubskyi. “This idea flow goes from advisors to their executing marketplaces, brokers, asset managers and private banks to the issuer banks that manufacture the structured products resulting in more deals for everyone.”

Increased customisation

The SaaS company sees structured products as the ultimate vehicle for personalised investing because they are the only type of security that can adapt to different investment requirements and risk-reward profiles.

“In theory, it should be possible to have a personalised investment idea for every single client every single time they buy a structured product, but it is not possible practically with the old set up,” said Gubskyi.

As minimum ticket sizes continue to drop distributors are converting into multi-issuer platforms, which have facilitated electronic trading of structured products and enabled distributors to get prices from 20 banks within five minutes and click to trade to buy the final product.

The problem, however, is to establish what these distributors want to buy before they send an RFQ, according to Gubskyi.

“Imagine going to Amazon to buy shoes and you have millions and millions of products available, but you don't have any search or recommendation engine to search for ‘I want running shoes for wet surface’ and having to specify each shoe variation one by one until you find the correct one. It would not be an efficient process,” he said.

Using that same example, in the structured products space the only thing distributors can do is to try one and wait a few minutes for each structure being considered.

“That problem is being solved through manual human labour doing trial and error which is not efficient,” said Gubskyi. “And if you don’t have access to a multi-issuer platform you have to do the same trial and error one by one but now across 5-10-20 single issuer portal where each portal has a different price for the same shoe. It becomes simply impossible for a human to find the optimal combination with higher upside and lower risk.”

Improving pre-auction

IVM’s goal is to demonstrate to the buy side that it is impossible for a human to know, guess or memorise which combination of underlyings, terms and protection will deliver the highest upside with the lowest risk.

“With our analytical tool distributors can find higher upside simultaneously with lower risk products for their clients’ portfolios every single time a client buys which will enable the buy-side to negotiate better prices using data analytics and increase efficiency,” said Gubskyi. “We believe AI can provide a more effective way to access product ideas before and RFQ is submitted.”

Additionally, AI distributors can type in any natural language thematic question and IVM’s AI which uses search engines to incorporate analyst’s consensus and negative news checks “will find very quickly the stock / index list for the thematic and risk profile they are enquiring about and provide an explanation of why it fits into a particular profile”.

“If we think of an RFQ with 10 stocks, this [eventually] means more than 1,000 baskets/maturities / protections to price and to get the pricing on any variation on a multi-issuer platform will take around five minutes - by email it’s half a day,” said Gubskyi. “Therefore, finding the optimal combination is simply not possible for a human.

“With our technology, distributors can see each time that it is not possible to use a volatility screener or gut feel to know what will results in the best terms which can come from long maturity / short maturity or middle maturity.”

The same applies to barriers which may add value or not with the investor just taking risk and not getting paid for it; or certain basket which may produce a visually high coupon, but the stocks have a low analyst consensus target and experience drawdowns of 50-80%, which will expose the investor to money loss when the market turns.

“Most people use some volatility screeners, spreadsheets, issuer tools and search engines to get to that point,” said Gubskyi. “But there is a higher chance they will lose money when the market turns. Our technology aims at the highest coupon but with the highest protection too. The optimal result comes from using AI based stock research to arrive at a high conviction list of stocks that the client is comfortable with first.”

Once the initial selection stage has been completed IVM’s AI engine deploys “a powerful optimiser to choose simultaneously the combination of basket and maturity and strike and/or barrier and comparing all this with the analyst consensus target for the basket and the historical drawdown vs protection”.

“With IVM’s AI the buyside can arrive at a higher upside with positive analyst consensus and the historic drawdown being less than the protection chosen,” said Gubskyi. “This journey is what leads to higher upside and lower risk for clients, and clients are interested to see the journey not only that final price that they got from issuers. All these things you can find inside the IVM platform in no time.”