Rishi Khosla: Keeping the entrepreneurial flame burning - Be Inspired

Julia: Good morning. I'm Julia Hoggett, the CEO of the London Stock Exchange, and I'm here in OakNorth's offices with the CEO, Rishi, to talk about the journey that OakNorth has been on over the last several years and where it's going next. Rishi, firstly, thank you for having us. Rishi: Thank you. Julia: Let's start with the journey of how we got here. So this isn't your first rodeo. You started building a data and analytics company. And one of the things that interests me about all of the journeys I've seen of entrepreneurs, is they've identified an issue that needs fixing. In this case, it was access to data and analytics products, for investment banks and other intense users of those services being provided not just in the UK, but all around the world. That then led you to have challenges in how you thought about growing your business, that directly contributed to what you're doing now. I'd love to get a sense of that journey because it's so exciting. Rishi: Sure. So the first one, which was a data analytics business, Copal, we set up when we were 26 our mid-twenties. We, I'd started my career in investment banking. My business partner started his in consulting, and you sort of go through, like these analyst programs. Julia: I went through one myself. Rishi: There we go, joyful days, right? And we said to ourselves, we've done this for a while but you know what, there's a better way to look at this, right? You can systemise this, you can productize this, you can actually drive so much more efficiency, number one, but also accuracy in terms of like how all that analysis is done. And that's what spurred us to start our first business, Copal. That experience was very much driven by us having done the job on the other side and saying there's a better way to do this, a better way to think about this. And then with OakNorth, in a similar way, when we were building that business, we raised very little capital, to build the business. We had very little capital, let's say like basically nothing. And we were at a point where we were growing like a weed, and we had very little working capital in the bank at any point in time. Right, so we were down to like 3 or 4 weeks of working capital, so if a client is not paying on the day, you're like how do you make payroll? So we said to ourselves, it'd be a luxury if we can get a small line of credit, i.e an overdraft from a commercial bank. Just just in case to keep us going. So we spent a few months with with a couple of banks over here, and had a very undelightful experience. Julia: I was wondering, what word you would use. Rishi: And a few months after that, we went to one of our clients, one of our investment banker clients, into their sort of institutional special situations desk. Julia: Yeah. Rishi: And they structured a loan for us which was a 100 times the amount of lending to dividend out to shareholders. So we couldn't get... Julia: Working capital. Rishi: We could get a 100th of the amount as working capital, but we got 100 times to take out as a dividend. And we said to ourselves, wow, something's like askew here. And what we clearly identified is the way commercial banks look at businesses, analyse businesses and therefore lend to businesses, is so different to the way that larger, corporate institutional players do. And the number of other entrepreneurs that almost dismiss commercial banks as even like a thing to help them grow their businesses in terms of access to capital. And we said to ourselves, you know what? There's something here. There's something here where we can actually help businesses grow in a way which at the moment they are constrained to do. Julia: And that brings us to OakNorth and why we're here today. So let's talk about the the proposition that OakNorth was founded to create. And it's sort of two limbs, isn't it? It's the capability to understand the story, which is one part of your business, and then the capability to thereafter lend to the story. Rishi: Right, exactly. Julia: So how, you how you frame it, how talk about the construction of both and then how both interact together. Rishi: Yeah. So, so again, it is very much interlinked with our story from the previous business. So we were looking at credit from so many different like, aspects. And when you put that all together, that just gave us a view on a framework and toolkit which could then, you could take from the larger institutional mark and apply down to smaller commercial companies. And our view was, if we could do that then we'd both understand the businesses, and we'd understand actually how much debt capacity they have within them, and therefore we should have the confidence to lend on that basis. Right. Julia: Can I ask a question on that? So there's the model piece. Understanding the business models, understand the stories, understanding, thinking about the credit. There's also the data piece. Rishi: Yeah. Julia: Which is actually understanding the individual dynamics of individual companies. And what you're articulating I think gives you the model and the high-level piece. How did you then get to the data at the individual, lending by lending component? Rishi: So you're absolutely right. So number one is the model and the framework. And then you have to fill the container with something. And some of that is the company's own data. And some of that is other data of comparable companies, the industry, the sector etc. So the latter place is where the great companies like yourselves, your group as well, the LSEG group. Rishi: Exactly. Come into play, so i.e data providers. And what is interesting is when you look at sort of the investment banking world, the investment banking world are massive consumers of third-party data. You look at commercial banks, commercial banks are very, very small. But the fact that they own and take the data in shows they're not actually using a lot of data, right, to make their decisions. So for us it was, okay, let's use the same sort of institutional model. Take and be massive consumers of external data. And not just market data, but obviously industry data, regulatory data, whatever data you can find like, you know, you sort of you end up in this position where you’re bringing hundreds and hundreds of data sources in. And you do that to jigsaw together a picture which is richer than you otherwise can get. Julia: Yeah. Rishi: So that's all we do in terms of external data. And then the company data, we literally, I mean yes, we will go to external sources which have data on a company but like you know, for smaller private companies. Julia: There isn't a great deal of it. Rishi: So that we have to get from the companies. But again we make it less painful in terms of we're not giving the companies like these massive templates to fill out. Julia: And one of the things that I think you've done is focus on particular sectors and segments? Rishi: Yes. Julia: In a way that maybe more unusual compared to a commercial bank. And then presumably that's also coming from the model piece which is, the more that model gives you the confidence around a particular sector, the more you've got confidence in the lending approach you take in that sector? Rishi: So our approach was to say, okay, you've got you've got an economy. Normally most institutions will split an economy into 10, 12, 18, 20 individual industries. Julia: Yeah. Rishi: And when you look at each of those, and that level of aggregation, there's a lot captured, a lot of very varied businesses captured. Julia: Yeah. Rishi: So we started with, okay, if we flip this on its head and say, okay, at the most granular level, how many industries would you split the economy into to get a more homogenous, more homogenous not homogenous, within each of those cohorts? And that number was X. Let's just put that, and then you sort of say, then where can I actually get data in that granularity? And that's Y. Julia: Yeah. Rishi: You put that X and Y together, and our answer was 274. Obviously. So we split the economy into 274 industries. And for each of those industries, then we maintain a statistical model, which is your ML model, which looks at historic correlations, etc. And then we have a fundamental model which is identifying what is happening at that industry level, that 274 industry level, which actually could cause this industry to not follow historical correlations? And we see how many breaking correlations there have been, especially in the last four, five years. So we marry those two together. And then through that, we've got the ability to effectively fire out forward cashflow models on a new company on the fly. And then we have different macro scenarios, and those macro scenarios again, will then disaggregate down to those 274 industry level. And therefore you have your scenarios also on the fly. Julia: And then you can actually look at how you would do portfolio construction as well, because you can understand the sector exactly within it. Rishi: That there you go. Julia: Yes that makes sense. Rishi: And then you say to yourself you've got something cool here, let's go and give it some other banks because you know it probably has value to them. And so that was that was the second step of what we did at OakNorth. Julia: So what you have at OakNorth is a is a software company, which is doing all of that analytics that builds and drives the portfolio that you're prepared to provide as a bank. But also you've got the banking service that you do directly and you've sold that software to other providers? Rishi: Yep, exactly. Julia: So let's talk about the business of the bank itself. You've had a full banking license since 2015. Rishi: Yep. September 2015. Julia: And where have you been so far? I'd love to get a sense, actually, of the impact piece. How do you measure that impact in terms of the number of companies that you've lent to, the number of employees and product or services that's enabled them to do? Rishi: So one thing that Joel, my co-founder, and myself were very clear about when we when we sold Copal, and were thinking about our next business, is that we wanted a business which is going to have real impact. And let's be clear, we wanted to build a business, but one which actually does good. When you look at growth companies, scale up companies, they generally in most communities are the key drivers of employment and GDP growth for those communities. So you look at the productivity which they drive, it's outsized in comparison with the productivity in either a micro business or in a large company. Julia: And in the incremental income that it generates in that area. Rishi: Exactly. So our view was supporting these growth companies is actually really good for communities. And that's always been an underpinning for us, and a driver for us. So if we look at over the last, eight and a half years now, we have lent over £10 billion in the UK. We've helped create about 40,000 new jobs through that, through that lending, and obviously there's a massive multiplier effect. So playing into both of those aspects I think at least for us, feels like we're on mission. Julia: Can I just ask, going back to the software bit, so you're now providing that software and that analytics to other banks? Do you think it's changing their behaviour and their appetite for the very same sector that you're seeking to have an impact on as well? So do you think there's an even bigger multiplier effect? Rishi: Yeah. Julia: Which means the growth of what you can do at OakNorth is a really important driver of that. So what's your plans for the future from here? Rishi: So look we've obviously spent the last eight and a half years sort of bedding down and in a way proving that we've got the, earning our stripes in terms of like yes, you know, Julia: Proving it out. We can analyse the model like you said, and we can actually lend to those businesses and we can actually drive good outcomes for those businesses. And again have the impact that, you know, we could have only dreamt of when we, when we started the business. So when we look at what our customers are asking us for, many customers have sort of said to us over the, over the last years, which, like you lend to us in such a different way and we have such a different relationship with you than we have with our normal bank. Why can't you do more of, Julia: Of all of it? Rishi: Of all of it. So we're working on doing more of all of it. Julia: So there's big, big plans ahead? Rishi: There we go. Julia: But it proves that fundament of identify the problem, work on the model, prove out the model, apply the model. Rishi: There you go. Rinse and repeat. Julia: Now my last question is more about you actually. So you mentioned hunger earlier actually and that sense of that hunger and that drive that entrepreneurs have. How do you keep that hunger and that iteration, that evolution going? Because I don't sense any lesser drive in you now, than there would have been when you started your first business. Rishi: So, but going to your point about hunger. Look most entrepreneurs have something askew with them. So I've got quite a bit askew with me. But when you're used to being the underdog and you're used to sort of being the person who is sort of, you know, you're always, you're always the person in the trenches, right? That just creates something in you where it's energising. It drives you, and I still view ourselves today as the underdogs. We very much are, I mean look at the size of OakNorth compared with any sort of larger financial institution. We're like, you know, we hardly register. So we're fully the underdog. And that whole sense, and the businesses we're supporting, they're all the underdogs. Because they're going in there trying to like change and do something innovative and etc. and disrupt it. So when you've got that mindset, it's sort of like you're always on this like fight, right. You're always on this thing to you know get to that next level. Julia: I suspect even if you were the size of HSBC, you'd still be fighting though. I think that sense of a purpose of lens is critical to businesses. And OakNorth exemplifies it, so it's been a real pleasure speaking. Thank you very much. Rishi: Thank you.