Let's move on to the next topic in our last lecture, which is asset-management, a big topic. So let's talk about the lay of the land and course, very complicated. At least as complicated as the sell side, and perhaps more so. But roughly speaking, and this was at the end of 2017, there are 21 trillion dollars worth of assets under management in the US. About a fourth of that, or 4.7 trillion in Europe, you'll recognize many of these names. Obviously, BlackRock and Vanguard dominate right behind them, capital and fidelity. Then behind the BlackRock call out is actually Pimco. BlackRock got 6 trillion dollars of assets under management. The vast majority of that is passive or indexed and we'll get to that. The industry has become increasingly concentrated, let's imagine we line up all the asset managers globally from top to bottom, where top is the one with the largest assets under management, and then go down from there. Let's pick the top percentile off of that list. Well, that top percentile managed 61 percent of all the assets. That was at the end of the first quarter of 2020. As a multiple of the assets in total managed by the bottom 50 percent by size, that is 243. The top one percent managed 243 times the total assets managed by the bottom 50 percent. Where again, we're raking asset managers by AUM in descending order. That 243 multiple was 208 at the end of 2015 and it was 105 at the end of 2010. So I see this is an industry that's getting more and more concentrated. Let's talk a little bit about BlackRock founded in 1988 by Larry Fink, Rob Kapito, and others. It's separated from Blackstone, an interesting complex arrangement in 1994, but public in 99. Then 10 years later in 2009, did something that was utterly transformational, which was the acquisition of the Barclays Global Investors or BGI iShares business, and BlackRock leadership will tell you that acquisition put them on a completely different path. Going out to 2019, inside BlackRock, you'll see that there's a billion dollars in annual technology services revenue. Most of that is from licensing Aladdin. We'll get to in a moment, Aladdin is BlackRock. Description of Aladdin is it's an operating system for investing professionals and they've licensed it to nearly 240 asset managers who compete with BlackRock, including, among others, Vanguard, which is the largest asset manager we've just seen after BlackRock. Half the top 10 insurers in the world by assets use Aladdin to manage their assets alphabet, Apple, Microsoft, the Japanese Government Pension Fund, which is by itself 1.5 trillion dollars, are all wet and customers and that licensing revenue shows up in that technology services segment of BlackRock financials. Now, we look at all of the stocks and bonds in the world and is total them up by dollar notional. One could say that about 10 percent of the world's total stocks and bonds are managed on land. I put that in quotes, not 100 percent clear exactly what that means. Different asset managers using different parts of the lab and offering these different purposes, but if we look at those 240 asset managers and their assets under management and look at it as a percentage of the global total. You get to that 10 percent figure, which is an amazing market share. Many would say, I haven't said this but it's often said that Aladdin is to BlackRock as SecDB is to Goldman Sachs. Well, they share the feature that they were homegrown and they were ahead of their time. They were built originally to be an in-house platform, and they grew from there. There is a vast number of differences between Aladdin and SecDB. First and most obvious, SecDB grew up around the use cases of the sell-side, and Aladdin grew up on these cases of the buy-side himself. Obviously, hugely important distinction, they do different things. Reports that one consider essential in SecDB, we call it the P&L balance report looking at the change in mark-to-market of a portfolio from one day to the next, and attributing the dollar change to all of the different underlying drivers, spot price forward, curve, rotation, volatility, the mere passage of time. That report, which is of the essence for sell-side business might be less interesting than say, a drawdown report, which is of the essence for the buy-side and their myriad differences beyond that. In addition, I would say that even though both of those platforms have gone on to serve clients other than the in-house client that originally funded the development. Neither one is a true n-tier multi-tenant cloud service. Tiers meaning there was another tier of business-logic, at least one more tier, as opposed to the traditional client-server model, which usually jammed all the business logic into the client-side and made for these very vast clients. Both of them have migrated in that direction, however it's extremely difficult to migrate client-server two-tier architecture to n-tier architecture. You almost always find that you've rewritten just about all of it. Also importantly, in scaling properties, neither one was designed to be multi-tenant. BlackRock is really using what one would call an application service provider model. Each one of those asset managers will have a distinct installation of Aladdin that BlackRock hosts for the various asset managers. Obviously, there's a great deal of trust there. But it's quite different from an architecture such as Google. We don't know if different users of the Google search engine licensing their own installation of Google. All comers would go into the same multi-tenant cloud service. That's super important because you've different versions of the stock where you're maintaining different installations, you get completely different margins and economics with that approach. Suddenly, there is an opportunity to evolve both of these platforms to become truly financial cloud service providers. A ton of work needs to happen for that to actually occur. It's a journey. To put BlackRock in some context, the context I know well, it's pre-tax income was six billion dollars in 2019 versus Goldman's 10.6 billion. Its market cap was the other way around, BlackRock on May sixth had a 75 yards versus Goldman at 60 yards. Very different and both very successful companies, but certainly, that 10 percent figure is astounding. You can look inside the leading sell-side firms, JP Morgan, Goldman Sachs, [inaudible] , eBay among others. You'll see very large market shares in certain businesses that none of them has that 10 percent global market share for a technology component of their business, that's really BlackRock [inaudible] there. It's brilliant, and I admire [inaudible]. Let's talk a little bit about the move to passive asset management. You all heard a great deal about this. I don't have to define passive investing strategy for you. Index funds globally are nearly 10 trillion dollars, and there was a huge growth spurt after the financial crisis. That 10 trillion dollars of global passive AUM, you can put it in the context of previous slides. Let's see, let's back up. Have a look at that again. Roughly 26 trillion in US and Europe of assets under management, and passive funds globally 10 trillion. To put that 10 trillion in different context, it's twice as much as all the AUM total in the global hedge funds, plus private equity businesses. One of my favorite anecdotes, last year, Warren Buffett won a bet that he had made 10 years earlier. It was a lot of details and the bet was very precisely specified, but his bet was the Vanguards S&P 500 Admiral fund VFIAX, would beat the average return of five unzipped hedge funds. Funds of funds selected by Protege Partners [inaudible]. The S&P index won, therefore Warren Buffett won handily at returned 126 percent over the decade with a Cager being a half percent. While Protege Partners that basket returned 36 percent of a cager of three percent. Then, of course, you are not risk adjusting that Warren won the bet. With the graph, you can see exactly how the progression has occurred over that period of time. When I started it the business in 1993, barely heard of ETFs and index funds, and now they become utterly dominant and pretty much 50-50 splits of the passive AUM between those that are managed as ETFs. I'm sorry. I should say ETFs not EFTs [inaudible]. Those that are managed as, index funds. Of course, ETFs are a fascinating technology where there's a moving ticker price. Therefore you can get in and out. Whereas funds typically let you out of the funds at the net asset value at the end of the day. Let's look at the US asset managers by type. Of course, there's many different topologies. This is just one. Look at their performance over the period and the way their assets under management grow. In this particular topology, this is just US asset managers. We see that the single biggest group is still active funds at a little over 11 trillion. When there's private equity, which is a little over three trillion, the passive funds are pushing up to seven trillion. North American hedge funds are the smallest and this group of at 1.5 trillion. Now if we look at how the performance has broken down by these groups, you can see that the private capital, private equity performance has been 14 percent cager over the last decade. Which is amazing in sense way up here at the top. Greatly outperforming for instance, hedge funds and definitely outperforming passive and active funds. This is net of fees, which is a very important distinction to make. Then if you just look at how the AUM has grown, again, private equity is up there, but as we discern from previous slides, passive funds has grown the AUM even more rapidly. Hedge funds have grown and did the active funds at about the same pace, a little under six percent over the period. This again is just US asset managers. I have a hard time getting global figures. Now let's talk about another super important subclass of hedge funds, and these are the systematic hedge funds. You also hear them called the Client funds quantum mental, hear a bunch of different names. They call them systematic. Systematic hedge funds use a variety of numerical methods, including Factor Analysis statistics, non-linear pattern analysis, if you prefer to call it Machine Learning. Most of them use a variety of these techniques. I've listed some of the classic factors. You've often heard of value factor analysis. There we're just buying securities that are under-priced according to some model and selling securities that are over-priced according to some model emphasis. It's all model-driven. Momentum, you look at the trailing end month returns. You buy stocks that have high momentum and you sell stocks that have low trailing end month returns for some. There's anti-momentum, which is just the inverse of that strategy. You've heard defensive strategies. They mitigate losses by periodically reducing risk. Many of the great asset management systematic fund platforms are extremely disciplined about cutting risk. You've heard about the carry trade. Carry is the expected return on an asset, assuming that the price of the asset and conditions stay the same. Maybe the asset pays some stream of income, arts and dividends. The carry trade which you all have heard about is simply buy assets with high carry and sell assets with low carry. There's a number of critical components that you'll find in all the systematic hedge funds, which is, they all have data management and backtesting, quite sophisticated. They have a variety of trading signals closely guarded. That's their intellectual property. That's their Alpha, P&L tracking, and risk management, as you would expect. They're routing and execution sometimes quite sophisticated. We're seeing a trend to outsource that routing and execution, or large parts of it, smart order routing for instance, to the sell side. Really forcing the sell side to become proficient in that activity and providing efficiencies across the board. That being on a certain activity of trading custody being outsourced by the buy side from the sell side, we're going to come back to it. Now, this over here on the right is what fascinates me. If you look from 2009 to 2018, you'll get fundamental, classic equity, long/short hedge funds. I've got in here their growth in assets, and this is on levered so from 1.1 trillion to about two trillion over the period. These are global figures. Then, if you look at the systematic hedge funds, they have gone from 0.2 trillion to 0.4 trillion, but there's a super important difference, the systematic funds, because they're generally not directional, the longs and the shorts will generally equal each other. They get much more leverage from their prime brokers, generally 20-fold. They only really get stocked out when there's a loss of more than five percent. They actually use all of that, all of that leverage, and they will maintain their own global core liquidity funds by drawing the full value from their prime brokers. That number is levered much more than the long shorts, and so gives them a disproportionate impact on the market on the order of nine trillion when levered, that compared to six trillion for the fundamentals or the equity long shorts. There are roughly 17-20 large dominant funds that are of the systematic typology, and of those, there are three or four that dominate. This is not by any means a complete list nor a full description. They all merit full lectures independently. AQR is known for adopting factor investing early on, they systematically construct portfolios and they will tell you that they have great conviction on the process. They do not have conviction on individual stocks. Here's one of my favorite quotes from Renaissance. They say the computer runs itself and we hardly ever interfere. The machine tells us what we should do. Every experience we've had shows that humans mess up worse than machines. There's some deep thoughts and a lot of reality and experienced in that quote. Two Sigma over on the right, they're known for distributed computation and machine learning, a fascinating example of a group of brilliant people that have developed techniques that they could- and are beginning to apply on a variety of industries, and they just started with the natural services. So, let's talk about alternative assets, private equity and venture capitals. Now we're getting away from bond only stocks and bonds, and long/short global macro product and systematic and specifically private equity and venture capital. I consider venture capital to be a sub-segment of private equity. A personal view is that Alpha mostly exists in the private markets. Of course, we have the prohibition on insider trading, do not direct the purchase or sale of securities while in possession of material nonpublic information. That doesn't apply to private equity. What do private equity firms do? Well, there's a bunch of things they do, but here are five of the main activities. First, they raise funds from limited partners, the LPs. They Source opportunities, they choose companies to invest in performing diligence and valuation. They work intensively with those companies to develop them and enhance their enterprise value. Using multiple methods; selling, combining, sowing into public companies, listing the companies that they bought, they exit their investments and they return capital to their LPs. Over on the right, we can see that private equity firms hold significant dry powder, I love this chart, and so total AUM is just unrealized value of the investments that they're still in there, haven't monetized them yet. Plus their dry powder. You can see the dry powder in the light blue and you can see the unrealized value in the dark blue, and you can see that relative to the total AUM of about five trillion, there's a significant amount of almost two trillion dollars that is ready to be deployed. Of course, different funds are at different stages of having deployed their capital versus having dry powder left. We're going to consider a couple of segments of private equity, the mega funds, and the venture capitalists. So the Megafunds, let me move this, continue to scale, and there's a barbell distribution, it was hard to get the data. But these are Megafund cross strategy assets under management and these are one-stop shop multi strategy managers at one extreme, these Megafunds, Blackstone being the largest example, have broad product offerings, credit Infrastructure, hedge funds, distressed growth, pre-IPO crossover. Part of the driver of this growth is that some of the large institutional LPs explicitly want to have a small number of relationships. Building that relationship capital and acquiring and maintaining it is expensive and so they prefer essentially a supermarket to a specialty store. Here's an important question to ask, what business are you actually in? Are these firms investing on behalf of their LPs or are they accumulating AUM as a means to grow the risk-free management fees? Of course there doing mixes of both. You could argue from some of the parts analysis that the fee revenues are more valuable, and they're less volatile than the intermittent carry and performance fees. This would be an important question to ask Steph Cohen, Goldman Sachs chief strategy officer, as she talked recently at the Goldman Sachs investor day about this exact question. Now how has some of this growth occurred? Well, there's firms such as Apollo and Ares that have expressly taken advantage of US banks retrenching after the financial crisis. The various restrictions on banks, the rules and regulations that we've talked about in great detail mean that some of that business of holding loans and bonds has moved over to some of these firms that are non-banks and you could ask the question, I don't have the answer. Are they essentially systemically important financial institutions? One thing I will note, is there's relatively little fee pressure compared to public markets and you can see over here on the right there really hasn't been much of a change in the management fee margin for these companies over time, they've been quite stable. In the time of Covid-19, we're seeing specialty purpose vehicles or special purpose vehicles owned by the Treasury, therefore the US taxpayer as the equity owner financed by the Fed, buying the securities and the loans. You could ask yourself, who are the beneficiaries of that? Even before Covid-19, who knows now, there was a question, was private equity in a bubble as interest rates continued to remain near zero. The asset class is extremely attractive. Leverage continued to grow. Can it continue to grow past where it is, and the multiples are [inaudible] are already quite high, though there's important differences between now and the period before the financial crisis that would cause one to, you could make a credible argument that it's not as risky as it was in the bubble leading up to the financial crisis. There are questions one could ask about covenants light financing deals. They're basically no covenant deals. It's hard to see how covenants could get any lighter, they practically don't exist in the standard deals these days. It's also worth talking about family offices and sovereign wealth funds, they've become hugely important players. These institutions both they're becoming almost institutionalized. They're hiring their own internal teams with private equity backgrounds to source deals, manage their large portfolios. Bezos, Walton, Cascade, are some of the important family offices. Vulcan, of course, you see some connections to Microsoft in there in Seattle more generally. Then over on the right, the sovereign wealth funds have become hugely important. Norway Government Pension Fund Global of [inaudible] , the largest CIC of China, right behind it, Abu Dhabi, Kuwait, Hong Kong, and then in Singapore, GIC, and Temasek, and the AUM is staggering from the sovereign wealth funds, and they can be very patient capital and compared to private equity firms, generally they provide a better core structure, lower administrative costs, and lower internal management fees paid to their employees. Venture capitalist sub-segment of private equity gets outsized publicity, yet it's only about 20 percent or $1 trillion of the roughly $5 trillion we talked about in private equity assets under management. You will know the venture capitalists, I've listed a few in no particular order and leaving out many influential ones, but among others, Sequoia, NEA, Kleiner, a16z, ACCLE, Index, keep raising larger funds. They're migrating to later rounds of fundings including both late stage growth as a way of deploying additional capital into continuing to back their winners which seems like a good idea and probably is most of the time, not guaranteed to be. Again, we could ask what business are they in, so you reference to the megafunds. Are they in it to create value for their investors? Are they in it to collect staple management fees? Again, it's a mix of motivations. The SoftBank is a fascinating example. It has explicitly stuffed capital into selected companies. Its incursions dominate their markets and almost made it normal to have unprofitable revenue growth. There's been lackluster investment performance. There has been a couple of spectacular individual flame outs and that's given rise to activists' questions about governance. It's also the case that SoftBank, with its massive scale, single-handedly lowered the cost capital in the required rate of return in venture capital. That is by raising a $100 billion Vision Fund and providing extraordinary amounts of capital into early stage companies. The graph on the lower right shows the increase in AUM over time of the private equity business in total, and the light bar at the top is the venture capital portion of it. You can see, as I mentioned, roughly $1 trillion VC AUM compared to the total of $5 trillion of private equity AUM currently, and that's grown considerably just in the five years since 2015. We have venture capitalists investing in technology and having such a crucial role in the technology companies that we know so well and yet, these firms themselves are still really old school in the way they operate. It reminds me of how sales and trading operated 20 years ago. There's artisanal institutional knowledge and pattern recognition, which of course includes biases and that's really the approach generally, objective data-driven approaches are relatively rare. Deals are sourced over the personal network and that can be a huge challenge as these funds deploy more and more capital, because it's not clear on the personal networks scale, so of course, one would seek a platform-based approach, but they haven't yet achieved scale and they've had some instances of adverse selection. As I mentioned, the large funds know personal network artisanal approach don't scale, perhaps the best very New York SF centric, is that a durable long-term strategy for generating alpha is a question that poses itself. Now let's talk a little bit about disruption coming to the asset management business. Well, as in the sell side, we've got the rise of the quants and I talked about it a little bit, with the systematics. There's been a huge capital investment in technology that's increased liquidity, it saved time, reduced the bid-ask spread in high-volume market, that's especially the case in equities but also foreign exchange, and now increasingly in corporate credit. The algorithms are creating the alpha increasingly, and it's a lot less about traders' hunches. There's non-bank liquidity providers, market-makers, such a Citadel, we'll talk a bit more about them, and these trends have greatly benefited Citadel and others. The losers are old school sales people. If you are a salesperson who depended on that phone to ring because you're occupying that seat from the people before you even build that brand and so clients just call, and your version of selling is, "I got a potato, would you like potato?" Well, that's not the kind of sales that for instance, an Oracle Enterprise Software salesperson is engaged in. That person's building a relationship and identifying the client's pain and demonstrating to the client that only that salesperson can stop their pain. That's heavy duty sales. There are a lot of people on the sell side who didn't need to do that, the phone just rang. But these trends are moving much more to automated trading. Had been hard for the old school people. Then also for the asset managers, the growth of cost-effective passive investment strategies with performance fees in one or two basis points, that's compressed feeds dramatically for the active managers, putting of course, huge cost pressure on them. Let's talk about one of these companies, Citadel, it's sell-side. I don't know which side Citadel is on. Citadel is really on two businesses, got about 1400 employees. Citadel, the original business, is a $32 billion AUM alternative asset manager, so an impressive AUM base. It's very broad. They've got equities, commodities, fixed income, credit, and quant strategies. Then in addition, there is an NBLP, a Non-Bank Liquidity Provider, called Citadel Securities. It is a leading global market maker under this one brand. There's the founder, Ken Griffin, at the bottom. They've got these two very different businesses. Ken famously started trading convertible bonds out of his Harvard dorm room in 1987. I actually started at Harvard in 1985, I didn't know Ken at Harvard. His agreements and suppressants restricted investor's ability to withdraw capital and that made him a strong buyer in the 1998 Long-Term Capital Management, LTCM. But that he launched the market maker much later, Citadel Securities, in 2001. It's come to be the largest market share. Had the largest market share in US equity options, 25 percent market share by volume. It's hard to find very many businesses that have a market share more than 20 to 30 percent anywhere on the sell side or the buy side. It completes one-third of all stock orders from individual investors if you go back to Robin Hood in our module two. We had a discussion of Citadel's activities there. For the last five years, Citadel Securities beat out the Wall Street banks and is the largest interest rate swap trader, if you're counting the number of transactions. Of course, there's risk everywhere, and the asset manager almost collapsed in the 2008 financial crisis. It took a few years, but the flagship funds crossed their respective high water marks four years later, again in 2012. Let's talk about some of the secular trends in asset management. These are titanic forces that are evolving, some would say slowly, but if you step back and look at ten years, you see this in a huge way. The first is the outsourced Chief Investment Officer, CIO movement. There's a heavy reliance on technology and automated asset allocation strategy, reduces administrative costs and therefore it gains for investors. Any CIO, meaning, Chief Investment Officer, not information officer, who manages single-digit billions of AUM is unsafe, just because there would be the big asset managers who are saying, "Just give it to us and we'll do this for you, " and that's hugely attractive for a number of these funds. In the distant past, the only people who wanted an outsourced CIO were relatively sleeping pension funds. But this movement has really grown and now there's $2 trillion under management, and becoming outsourced CIO for the funds of others is a major thing for asset managers such as GSAM. Why wouldn't they want to take their approach and for a fee apply it across others' bonds? Now here's another trend, very different one, principally out of Japan and now Europe, and I absolutely expect it to continue into the US. Asset managers have begun to realize that they expensively duplicate and mirror the sell sides manual, voice-driven, chat room driven, trading workflows. There is a trader on the sell side, facing off to trader on the buy side, and there's lots of typing and there's lots of talking, therefore, all kinds of opportunities for operational error of various kinds. If you step back and think about it, the buy side is doing the opposite of what the sell side is doing, and it is all, if you take the cosmic perfect perspective, quite inefficient. There's a solution here, and the implementation of solution is nascent. It is to outsource the trading function altogether to the sell side. Where the sell-side is going to be much smaller number of sell-side firms, they're going to have scale, and then the asset manager develops some core competencies, puts all of its energy into first the raising of the pools of capital, in the first place, and then what is the asset allocation, and specify the asset allocation in an abstract way. We can call them risks, exposures, and then leave all of the gory details of how to implement that exposure, the trading, the risk management, and the custody to the sell-side. We're increasingly seeing this as a hugely important business for the Wall Street firms, where the Wall Street firms are implementing strategies specified by the buy-side or perhaps designed by its sell-side and marketed and sold to the buy-side of the sell-side is actually doing all the buys and sells according to some pre-specified plan in handling all the execution details and really bundling all of that. I expect this trend massively to continue its early days as of 2019 and 2020. Then surprisingly, Software as a Service comes to asset management. Most asset managers are not building their core software platforms anymore. If you look at US registered investment advisors, this is a staggering figure. They collectively manage 84 trillion dollars in assets for 43 clients and these asset managers, the RIAs, are definitively not building their own software. They don't have the scale and so they're relying on companies such as ADDEPAR, ORANJ, to do that work for them. ADDEPAR has two trillion dollars of AUM on its platform. Of course, you could think of Aladdin, as a SaaS business, that with this important description that BlackRock hosts an Aladdin instance for each of the asset managers. It isn't a single, multi-tier Cloud Service platform. Let's go back to the Data Science Revolution. We've talked a lot about it and of course, here I'm talking my own book. I've been quoted as saying, traders who can't code will become extinct. I must have said it. At some point, It sounds like the kind of management that I would say. By coding, I really mean the algorithmic problem-solving skillset, the disciplines repeatable skill-set. That's the essence to meet coding. It isn't the ability to type sentences in any particular programming language. That mindset has become crucial and it's only going to become more crucial. The core intellectual property now resides in software. Sell-sides increasingly less interested in sniff or instinct or guts or brains or smell that is all kinds of terms for it, avoid human traders have now, to say here, there is no substitute for world-class risk management skills and no human beings anywhere cause to the people that really built that skill. But the line-level desk traders skill that one's headed only in one direction. As the real bellwether of this trend, we mentioned Renaissance is not even sure why it buys or sells a particular stock. Human beings can't understand the decisions of algos and they don't understand the decisions of the algos. Got a picture of Jim Simons one of my heroes down there at the bottom. You could ask yourself the question, do the algos need to be able to explain themselves? Many, particularly regulators would say they absolutely do and increasingly, more and more people are convinced of the desirability of algos that can explain themselves. Now, private capital when I use that term generally to mean private equity as well as private debts, so it's just called private capital. Increasingly, firms are doing both equity and debt. They had successfully resisted technological disruption. It's like venture capital. Still, a profession of artists and mentors and apprentices, where the wisdom of great investors and importantly their networks is what's valued much more so than quantitative and analytical advantages. Well, here's a group of questions you could ask. Were those wise investors, those great investors merely writing a trend of falling interest rates. Interest rates are headed in one direction for 30 years, bonds are headed in the other direction for 30 years, assuming credit spreads are constant. Were they exploiting various regulatory and tax arbitrages or both? Now, there's reasons that these private capital markets have not embraced technology to the same extent or perhaps even resistant technology. The data required to make investment decisions is not standardized. It's hard even to get private company data and it's hard to aggregate and it's not normalized. The rules around disclosure and accounting are not standardized. Back to the point I made earlier when we started the software transformation of the trading business, we started with the business where the trades could be fully specified by five or six parameters that are incredibly simple. Yet when you aggregated them and simulated them and ask questions about all the things that could go wrong, that became immensely complicated. Well over in private capital, every financial model of every company is customized like a snowflake, each one has its own set of projections. The projections are not necessarily consistent. The standard practice is you construct all of your analysis from scratch, print out of the 10-K, or whatever you can get in the case of companies that are public, and get a bunch of expensively educated young people to start typing away in Excel. To this day, Excel is a dominant platform for portfolio management and risk management and re-underwriting even at multi-billion dollar investment funds, even ones net of $10 billion of AUM, you'll go and you'll find millions of spreadsheets and they all have names like XYZ analysis during 23rd V2 final 0.3. I once when I was Chief Information officer Goldman Sachs did an analysis in 2013 and determined that if you looked at all of the Outlook or Microsoft Exchange address space consumed by all of Goldman Sachs, 40 percent of that space was occupied by Excel spreadsheets that had been attached to e-mail messages. Then if you did a further look, you'd see that each instance of the spreadsheet was represented on average seven different times. This isn't even the least of the problems with Excel, Excel is a brilliant product, it's just the product that's been misused. The biggest problem with Excel is that it's intrinsically uneditable. You will get a cell when you can't tell what's going on inside it just by inspecting it, you actually have to click on it. It might have a value, it might have formula. It's easy to find over an Excel spreadsheet to change a formula, delete a row or a column, not know the difference, take a bunch of formulas. To do a little scratch calculation, you take the values of those formulas and then paste them back as values and you've lost the formulas. Well, now what happens is those formulas aren't formulas anymore and they're not updating. Then when you do eventually update it in the trading business, you always find that you lost some money and you never find that you gain some money, and I could go on. Yet in private equity [inaudible] are in there but to say that they're all globally consistent. So many of the features that were the 25 years ago at a cell site firm, you'd find very many different instances of the US dollar discount curve floating around the firm for the same day and those discount curves would have different numbers in them. So just having a uniform discount curve for the whole firm is hard and that was in the trading business, now we take it for granted. Now [inaudible] and other processes insist that there's only one version of USD discount curve and anything else. We don't have any of this existing in the infrastructure for private capital firms. Which leads me to my punchline which is, I think in private equity there is the greatest whitespace opportunity in all of Fintech by far. Now, for the first time, engineers data scientists have everything they need, the tools, the data, and the compute power to create complex financial models and software. Just as we couldn't solve interesting problems in health care 20-30 years ago, we couldn't solve interesting problems in private capital until very, very, very recently. But now we're on the doorstep of being able to do that. We're beginning to see models that support complex counterfactual analysis, much as we did in sales and trading 23 years ago. What if dollar or yen were to move to this value, how much money would I make or lose? We're beginning to be able to see that in private equity where the underlying instruments, unlike FX spot and forward are extremely complicated, they are companies. We're beginning to be able to apply machine learning tools, pattern recognition, and do something much more interesting, complicated, and appropriate for the real-world than the linear sensitivity analysis that we see and do all the time in Excel. Now, why am I calling it a whitespace opportunity? If there are some startups their very much in stealth mode or they are tackling really tiny components of the problem. They're primarily designed to solve operational, financial planning, accounting issues. They're really not built for private equity due diligence and valuation use cases. We are seeing a couple of firms beginning to do this work causal and contracts. Some of the larger firms are beginning to tackle the problem internally, in just the same way that Goldman began building SecDB for its trading business in 1993. Now Jeff insisted, that Excel also has an API. It is true, but nevertheless, go back to the previous slide and a lot of things that I said about Excel. Excel is a wonderful tool. It's just being tortured in the way it's used for private equity sourcing and valuation and diligence and re underwriting. There is a tremendous opportunity here. I cannot overemphasize it to build risk management and valuation tools, to model private companies doing for private equity and private credit what Goldman Sachs strats did a long time ago about the trading business. We are seeing some private market infrastructure players beginning to blossom, one of my favorites, a company I know well is Carta. Many of you who hold stock options IN startups will know that you're issued your options grant on Carta, card assaults and ancient problem. I've been investing in startups for a long time and I can tell you that in the 5-10 years it took between when I was an angel investor and when there was an exit for startup, every time I managed to lose the stock certificate and there's a scramble to find the stock certificate, and if you don't find it, you have to get stocks certificate reissued. It's painful, and then of course, Carta just came in and said, "Why don't we dematerialized those stock certificates and let's handle option grants as well in a variety of management and valuation functions and really simplifying it." In no time at all, Carta has become absolutely dominant solving a problem for everybody and Carta has announced its aspirations to liquefy these markets. There has been the ability to trade these private equity shares in a secondary market, extremely hard and episodic to get liquidity. It's a tough problem in auction design and incentives and Carta is working on it, and to the extent that private equity continues to increase in size and you've seen from the previous slides how it's grown from 3-5 trillion in not very many years, five years. As that continues, the desire to create liquidity of that market hits another huge whitespace opportunity, another brand new asset class, of course, with immense technical problems in the way of making it liquid and a large number of regulatory concerns to address as well. PeerStreet, very different business. It's a real estate investment platform and now there's a new way to share models, and it isn't people in suits exchanging blue books and Excel files and calling each other on the phone, but it's actually happening on a platform. We're going to see more of this. In summary, software's eating the world, if you were a skeptic at the beginning, I hope I have convinced you of that and certainly eating the financial industry. As that's happening, Wall Street economics in parts of the business are becoming Silicon Valley economics with data and APIs everywhere. There's immense strategic complexity in this business and the current ecosystem, evinces all complex relationships which you can call co-opetition, or you could call a nuanced among the large financial players. No one on the sell side knows whether to consider citadel a client or competitor and really the only sane answer, it seems to me is to say that they are absolutely what superposition state or both. Now, what we've said that there's the sell-side and buy-side, that's been the case that JP Morgan has been providing payments and custody to almost everyone, and if those payments services go away as they did for a couple of banks in the financial crisis, that's the end of the bank. Then just hiding right there in plain sight, Goldman Sachs is a Top 3 liquidity provider to JP Morgan Asset Management and JP Morgan is a Top 3 liquidity provider to GSAM. So JP is actually a hugely important client of Goldman Sachs and vice versa. Those trends have been in place for a very long time and software has been a huge part of the financial industry for a very long time. I also have convinced you that APIs are the future of finance. I haven't proved it, I have given you many examples of the encapsulation benefits provided by APIs. You've seen the exits of companies most recently [inaudible] that appear APIs. You've seen the dominance of [inaudible] with its 30 some billion private market cap as a pure API play, so there's more and more examples. When we look at some of the newer offerings of firms that have been around for a long time, such as Goldman Sachs, Marcus, or Marquis, they export APIs themselves and they are themselves stitch together from a variety of services that are in turn packaged as APIs. Hence, my thesis that you better be a producer of a differentiated API for everything else, you want to be an astute consumers and student means you really understand the complexities, the service level agreements, and you've got detailed understanding and modeling of the operational risks that arises when you're stitching together all of these point of APIs. The product simplicity that you get when you have an API encapsulation allows players to achieve scale and dominate their markets. This is what Intel did with its Android and chipsets. Google has done with its standard in maps. We're seeing in finance the concept of the developer as an end user or customer. It's a huge and it's a massive trend. You even hear Goldman Sachs talking about the developer as a new customer and its investment in its investor day. Now, you like to think that you start off with the standard and that creates volume, but we know that's not the case. When you've got the volume that's those are the people who have an opportunity to set the standards. Certainly at Goldman Sachs, we would say that it would be a true sign of success if others who are regarded as competitors were to copy our APIs. We would love it if clients would tell our competitors at Goldman Sachs, "Would you please just give us that service in exactly the same API format as Goldman Sachs, so they wouldn't have to change any of our software, and then you'll get your share of the business." This is a famous quote on we get standards from Andy Grove, another one of my heroes and is quoted all the time from our strategy professor at the GSB, Robert Burgelmampn. I believe this one with all of my heart. I would advise all of you who were going to build new fintech businesses to think about how you can build them by combining third-party APIs in new and interesting ways. This was certainly the approach of the golden offering behind the Apple credit card as well as in Marquis, and we're seeing it all over the business. The digital transformation continues, so we're seeing banks and other large financial institutions becoming software firms. People at Goldman Sachs, leaders at Goldman Sachs and say this years ago and get a lot of raised eyebrows. Not really giving those raised eyebrows nearly so much. Today, we're seeing the banks learn from Silicon Valley and they're moving away from product aligned every firm was organized the equities trading desk, fixed-income trading desk, and even within their subsets, cash equities, the volatility or options desk and we're seeing that painful move over to who is our customer and what are the persona's among those customers base in New York, or even using that term persona, absolutely borrowed from Silicon Valley. The idea is that we should make all of the offerings of the firm available in a way that makes sense to the persona's of all of the client and all the client organizations that are going to be working with us. The old chasm, the cultural and operational contradictions between the two are eroding. I like to think I contributed in small way to that, simply by being someone who had worked in both and both millionaires. I'm a huge believer in going back and forth, and not getting caught up in doing things in a particular way. We all have a lot to learn from the other side because definitively, the case that all of the large financial institutions have embarked on their own digital transformation journeys. I think relatively, few are seeing themselves as providers of software services or providers of data, but increasingly they are and we certainly gave the examples of BlackRock and Goldman Sachs, but there are many others, including in custody, for example, State Street and Bloompberg, which had always wanted to offer its services through the Bloomberg terminal, is increasingly making everything available as an API. I hope I've convinced you that regulations matter. There was a time, 10 years ago, move fast, break things and apologize later. That is not an approach that I would recommend or anything having to do with health or money. The regulations have worked. They're imperfect, but I think you have to take your hats off to the regulators after the financial crisis and just look going into the current crisis at how stable the financial system has been when it's been under great stress. Maybe some of the calibrations were too tight, needed to be rolled back. Those are details, I can say working on implementation of the rules and the post-2008 period, an experience I'll never forget. It was intense and painful and not all of the regulations to my mind equally valuable in creating systemic safety and soundness. But at the core, upgrading all of the systems bank so they could introspect and become software businesses with software models of themselves and then demonstrate to the Fed, using those software models that they had sufficient capital and liquidity to continue when they're making markets in adverse scenario selected by the Fed. That becoming a software business has been at the foundation, at the core of making the system safer and sounder. One thing that we knew all along and we would advise the regulators on this is just be wary [inaudible] of the potential for creating such complexity and cost and regulation that you effectively create a deep and wide [inaudible] around established players. It's really hard in 2020 to start from scratch any kind of bank capital and compliance [inaudible] , just to get the charter can be prohibitive. You could ask, is that optimal in some social-political trade-off? We did an extremely broad survey, and I'm sure it shows where I lived and breathed deeply, part of the business and other parts where I'm an avid student of the business but haven't lifted myself. Even though this was extremely broad, we left out an awful lot. It was a survey based on my experience at [inaudible] and most of my experiences in banking, trading, and private equity, especially trading. There was no way I could have intended and I didn't, or even hope for it to be a deep dive into all corners of finance. There isn't anyone I had ever met who could credibly do that and certainly not me. Also, you'll notice at the very big picture level, I had a lot to say about baking and nothing to say about insurance because insurance is so boring. Of course, it's not boring, I just know very little about it. Once upon a time, I worked on some variable annuity strategies where there were options edges that banks would provide to insurance companies. I gained a tiny little bit of knowledge of insurance companies and appreciation for the past complexity and nuance and titanic importance of that industry and just notice a little bit about it that I couldn't even begin to be a student of it. My apologies to all those actuaries and insurance people who are watching this. Those apparently are Bermuda shorts. There are a large number of players and business models that are arising in this business and there's disruption going on there and [inaudible] is a rapidly growing sector. Unfortunately, I don't have the expertise to talk to you about it. I hope that you will gain from all of this. I don't know how many of you will enter the financial industry. I imagine there'll be some percentage. I'm estimating based on my conversations with you, maybe 25 percent. For the 75 percent of you who don't enter the financial industry, you'll know a lot more, maybe more than you wanted to know about what happens when you swipe your credit card or you buy something online, or you use a firm to set up an installment payments, or your $4,500 dog villa, that is a very lucky dog. You will be thinking about all of these things when you think about [inaudible] , you'll have a way of thinking about them. Sure, I left you with the sense of the complexity of the financial system, when you feel good or bad about that complexity and what you're going to do about it is up to you. This has been an interdisciplinary journey. This is my first time, and I'm sure it shows teaching at business school course. I didn't go to business school myself. I have only a vicarious understanding of the business school disciplines. I've taken great liberties and traveled all over the pace, talked about philosophy, computer science, history. We talked a little bit about intersubjective realities. We talked about ledgers or medium of account versus medium of exchange. We've talked about risk, we've talked about skeptical empiricism. I even frame Bitcoin for you as a particular solution of a problem in theoretical computer science, the Byzantine generals problem, and we had some amusing do of the year all on the way. I certainly enjoyed the journey immensely. It helped me synthesized a lot of my experiences, and do a lot of cogitating on some new ideas. If you are listening closely, and reading between the lines, I think I've made it very clear where at least one man thinks huge opportunities are ahead. I can say the opportunities I see are ahead in finance are greater than any of the opportunities that I've seen in the past. It's an immensely exciting time. I hope I've also shown you that finance matters across the board. Of course it matters during a crisis. Even leaving aside those crises, the financial system is more influential than we think. It's an intersubjective reality that affects everything. Economic growth, inequality, domestic policies, geopolitics and nothing that's important can get done without considering all of those interacting affects. I've also lead you with the sense of how complex the process are. Let's just say it broken, that complexity arose. Is it necessary? Is it good? Is it appropriate? We've seen examples of how if you go catastrophically, cataclysmically wrong, which is why I spent some time going into the nitty-gritty of some of the numerous complicated systems within the financial industry, including unit economics of credit card processing. You'll see that up at the top work hard on that particular graphic. Just to understand all the pieces myself. We talked about all the trading workflows for stocks and bonds. Then we talked about the settlement workflows, which are in many ways even more complicated. I just have to say it again. If only there were a uniform back-office fabric that extended across all of the cells site firms, to the buy-side firms, encompassing the exchanges and clearinghouses, and other critical pieces of market Infrastructure, and if only all of that could be rationalized into an N-tier, multi-tenant cloud service provider was an absolute intense opportunity to create value their. Value that all of the incumbent players would greatly appreciate. There's really no competitive advantage in mostly competitive disadvantage in the repeating moralists badly across all the firms on the same back-office process. But doing it in a random bespoke and customized way. See you end up with a lot of snowflakes. One of the things I've been particularly excited about was the opportunity to share with you, many of my friends who've taught me a lot, some cases they would say that I taught them or they grew up under my sponsorship. But really over time, the tables have turned and learning is all going the other way. I know you enjoy it as much as I do. The opportunity here from Darren Cohen, and Juan Benitez, and Brian Armstrong, real life founders and operators. Really had an amazing roster of guests and I'm grateful, immensely thankful to all of them, and also enjoyed your questions. We don't get smarter only asking and answer the questions we'd been having in our live sessions. It's been immensely gratifying to me. There's so much that's broken. But instead of looking at it as broken, just think about it as an immense opportunity to create software that improves the financial industry. Because that industry effects everything we do, it's important. It matters. I never spent a quarter century of my life working on it. At every moment, I was sure that I was doing something that made the world a better place. Because finance is so pervasive, it's the root, it's the fuel, it's the driver of so many things. I have faith that you are going to go out and you're going to fix those problems. But more importantly, you're going to do it by transforming those systems. To me, the thing that gets me out of bed every day is transformation. Transformation of myself, of companies, of groups of people. If in any way I have inspired you to go out and create that transformation, I've done my job. I've loved teaching you over these last nine weeks. Be well, and I will see you in class. Let's step out.
