EP962: How better understanding of risk leads to better decision making

Rajiv Bhat, CEO, martini.ai

Describing itself as the world's broadest and fastest risk engine, martini.ai aims to redefine how financial professionals access and interpret credit risk data through a free, platform. CEO Rajiv Bhat is leading a movement toward open, transparent credit data as investors and lenders around the world seek real-time visibility into risk. Robin Amlôt of IBS Intelligence discusses how transparency and better data are reshaping credit, lending, and portfolio management with Rajiv Bhat of martini.ai.

Transcript

SPEAKER_01 0:00

I'm Robin Amler of IBS Intelligence. You're listening to the IBSI Views podcast. With me today is Rajeev Bat, Chief Executive Officer of Martini.ai, helping to redefine how financial professionals access and interpret credit risk data. We'll find out how in a moment. But let's start with the basics. Rajeev, underline for us, if you will, what the importance is of understanding risk and how everything stems from that.

SPEAKER_00 0:32

Thanks for having me here, Robin. Very excited. Risk is really the other side of the coin when it comes to returns in financial markets. So you've got to understand both the kind of return you can expect and the kind of risk you're taking on and make great decisions. Risk has a serious compounding effect. So if you get it wrong, you pay for it in billions and in orders of magnitude. Risk is also a fast-moving liquid quantity. There's not as much information as people would like. The less people understand risk, the more conservative they get, the more they understand risk, the better decisions they can take.

SPEAKER_01 1:06

Is it the case that things are getting riskier now? It used to be a relatively simple, if slow, process to quantify risk. But with technology, things seem to have got more complicated. Although I suppose perhaps we might look at AI and say that's making things simpler.

SPEAKER_00 1:27

Absolutely, Robin. Things are definitely moving much faster. So we are living in a world which is much more interconnected than ever before. And things are uh hitting us at uh much faster at a much higher impact than before. So then kind of weather events or financial events and other kinds of socioeconomic events that are happening now are much larger than anything that you would have seen 10 years ago or 30 years ago. The world is much more interconnected. For example, you might recollect that episode of a ship getting stuck in the Swiss Canal and traffic backing up and price of oil going through the roof. All of that happened in like hours, and now things are moving even faster. All it takes is for one stock price to drop, for markets to uh start reacting adversely. So, two parts to it. There's one part where everything is connected more than much more than before, and the second part is information is moving much faster than before. You're also absolutely right about the second part. AI and data is helping us understand this. Like it's helping us process the second order, third order FX, helping us process all the far-ranging impacts of small fringe events that are occurring and being able to pull all of that together and helping us navigate these, like you know, our raft through these white waters.

SPEAKER_01 2:46

You say it's helping us navigate, but in implementing AI solutions, we make assumptions. We make certain assumptions. How can we be sure that we are making the right assumptions?

SPEAKER_00 2:59

Oh, fantastic question. There are two parts to it. There is the design philosophy. Like uh at Martini, we are very careful to design solutions which are explicit, which all the predictions are local. You can trace where every element of uh risk prediction is coming from, and that physical explainability helps uh with building intuition around and verifying uh the risk. But the second part is in the ethos of verification, making sure that you're back testing, making sure that you're doing out-of-sample testing and making doing rigorous testing to make sure that your numbers are really what they are and they're computing the right quantity.

SPEAKER_01 3:41

Is this transparency and this and I'm making it I'm making another assumption here that the data is better? Is better data and transparency of themselves reshaping the way credit, lending, and portfolio management takes place? Absolutely.

SPEAKER_00 4:01

Earlier, the joke in the market used to be that the lender is the last person to know. And that has changed now because in this day and age, every single company, whether it be public or private, needs to have a significant digital footprint. And its presence is understood in so many different ways. And so this has helped both portfolio managers and lenders bring in an independent perspective to the credit that's taking on, uh, which is different from that provided by their own data, by the data that the uh borrowers provide. And this has helped portfolio managers make much better decisions, be able to move faster, be able to intervene in situations getting out of hand, and help uh ensure overall safer portfolios and safer returns.

SPEAKER_01 4:47

That would be the the the wish upon a star moment uh to have better portfolio management, to have better risk mitigation. How do you see the credit market evolving?

SPEAKER_00 5:01

As you might be aware, the private credit markets have been on a tear as the size of portfolio, it's in a few trillions of dollars now. And uh in the US, uh a lot of uh private credit has moved from banks to other financial institutions. And it has been it's been happening because they're just faster return, they are the the high yield, they're uh the private firms are faster to execute, the deal sizes have gotten bigger. Uh but uh more recently, uh, there have been a couple of hiccups. There have been a few high-profile cases which uh have gone south, and questions are now being raised on how are people thinking about risk, how are people monitoring risk? So uh yes, good and bad. I think the good is that as a market, private credits and credit itself has been growing massively, and the bad part is not the bad part, the careful part is where people are now saying, hey, look, the growth is great, but where's the risk? Where's the risk management? And how do we uh look at that?

SPEAKER_01 6:02

How do you look at it? We've been talking about risk, we've been talking about the management and mitigation of risk. You're the CEO of martini.ai. What's your business model?

SPEAKER_00 6:15

So at Martini, uh we believe that uh the world's changing fast and it's more connected than before. And there's machine learning and AI has come of age, the data is sufficient to understand companies outside. So we cover three and a half million companies, we provide daily probabilities of default credit risk and credit letter ratings for these companies. And uh the way we do it is we have a huge knowledge graph. Uh, every company is connected to hundreds of other companies. We pull in information uh from all over the place, and we pull in market risk information. So every single bond transaction, loan transactions, we pull in all of those, and then we run our graph attention networks to propagate the risk. Our thesis is that look, uh risk propagates in markets, companies are connected, and if you can capture, make a digital copy of those relationships and run algorithms on them, you can find where the risk is coming from and where it's going. And our business model uh is uh we have we have a free product that anyone can use. Uh so we've been very excited to see users from all over the world use her products on a daily basis to understand the risk associated with the companies they're dealing with. Then we have a pro product which helps customers monitor portfolios of companies, like tens to hundreds of companies. And then we have an enterprise product where portfolio managers or asset managers or even financial firms can plug in their entire portfolios and monitor them, run scenario testing in uh seconds, which is a capability which is not there anywhere else, or price, risk transactions extremely fast.

SPEAKER_01 7:52

Rajiv Batt, Chief Executive Officer of Martini.ai, thank you very much. Thanks for having me here, Robin.