Upstart CFO Sanjay Datta Goldman Sachs Communacopia & Technology Conference

Great. Thank you, everybody. We're just about to get started. So welcome to the upstart presentation at the Goldman Sachs, the CommuniCopia and Technology Conference. I have the privilege of introducing Sanjay Datta, upstart's CFO. Prior to joining upstart in 2016, Sanjay was the VP of Advertising Finance at Google. My name is Mike Ng. I cover upstart and FinTech here at Goldman. And we have about 35 minutes for today's presentation inclusive of Q&A. So if you have a question, please feel free to raise your hand and we'll get a mic runner over to you. So for Sanjay, thank you so much for coming to participate in our conference and being with us here today. Thanks for having me.

非常好。谢谢大家。我们马上就要开始了。欢迎大家参加高盛、CommuniCopia和Technology Conference的upstart展示。我有幸介绍Sanjay Datta，upstart的首席财务官。在2016年加入upstart之前，Sanjay曾在谷歌担任副总裁，负责广告财务。我叫Mike Ng，我在高盛负责upstart和金融科技。今天的报告和问答时间为35分钟左右。所以如果你有问题，请随时举手，我们会派一个工作人员过去给你传递麦克风。所以对于Sanjay来说，非常感谢您参加我们的会议并与我们共度时光。感谢邀请我。

So maybe to kick things off with a higher level strategic question, upstart has made a tremendous amount of progress in unsecured personal loans. It's expanding into auto with your indela-ship offerings. Could you just talk about your five-year view, what does success at upstart look like, what are some of the key milestones and initiatives that you're watching and pursuing as you kind of undergo continued growth at upstart?

也许先以一个更高层次的战略问题开始，Upstart在无担保个人贷款领域取得了巨大的进展。它正在通过您的分期购车计划扩展到汽车贷款。您能谈谈您对未来五年的看法吗？在Upstart取得成功的情况下，有哪些关键里程碑和倡议是您正在关注和追求的？作为Upstart持续增长的一部分。

Sure. Five to ten years, well, let's see. Well, I would say our fundamental vision of AI and lending is unchanged in the sense that I think that all flavors of credit, all segments of credit will benefit from more predictive risk models. And we believe that in a ten-year timeframe, almost all lenders will be using some versions of these technologies in all segments of credit. I think the technology thesis is pretty incontrovertible. And the economic value you create by getting better risk assessment and credit is pretty massive. So it's pretty, it's pretty cord-ar belief that that's a change that will happen over a ten-year timeframe.

当然。五到十年，嗯，我们来看看。我认为我们对人工智能和贷款的基本愿景在某种程度上是不变的，我认为所有类型的信贷，所有信贷领域都将受益于更具预测性的风险模型。我们相信，在十年时间内，几乎所有的贷款人都将在所有信贷领域使用这些技术的某些版本。我认为这个技术论点是相当不容置疑的。通过获得更好的风险评估和信用，所创造的经济价值是相当巨大的。所以我们非常坚信这是一个在十年时间内会发生的改变。

In terms of hurdles, well, the technology cases sound, we believe, I think the economic model of better risk within lending is also compelling. I think to get there, there's going to be a lot of regulatory conversations, obviously. I think the general sort of discussion around AI and machine learning and how it gets applied to sort of more and more use cases in the world is a hot topic right now. I think it's particularly acute in an area like lending where there's a lot of regulation. I think there will, there's some adoption curve of this technology on the funding side of the ecosystem. So banks and other lending institutions, other types of institutional investors have to get comfortable with the performance of that technology. And I think there's some, you know, around that some resiliency and supply chain of capital that supports all of this, obviously. We've seen in the past a couple of quarters, you know, the supply chains that are currently underpinning this current model are not as resilient as we would have wanted them to be. So I think those are some things that come to mind. But they're a little bit, I don't want to call them on the margin. I think the core things around the technology and the economic model to us have been proven already. So it's just a question of, you know, some of those more larger conversations around how regulatory would think about this stuff.

从障碍的角度来看，技术案例听起来很有前景，我们相信在借贷方面，更好的风险经济模型也很有吸引力。我认为要实现这一点，显然需要进行大量的监管对话。目前，关于人工智能和机器学习以及如何将其应用于更多的用例的讨论是一个热门话题。在借贷领域，这种讨论尤为严重，因为该领域受到了许多监管。我认为在这个生态系统的资金方面，这种技术有一定的采用曲线。因此，银行和其他借贷机构以及其他类型的机构投资者必须对该技术的表现感到满意。显然，这方面还涉及到一些资金供应链的韧性和支持。我们过去几个季度已经看到，目前支撑这种现有模式的供应链并不像我们希望的那样具备韧性。所以，这些是我脑海中浮现的一些问题。但它们有点边缘，我不想称其为边缘问题。我认为对我们来说，技术和经济模型的核心问题已经得到了证明。所以问题只是一些更大的监管对话方面的问题。

Great. That's a great overview. And, you know, as you mentioned, artificial intelligence and AI has never been, you know, more top of mind than it is now. And, you know, much of the upstart competitive advantage has been related to the AI-based algorithm that the company has built and, you know, trained data on. Could you talk a little bit about, you know, upstarts underwriting model, how it may compare to, you know, utilizing FICO and other, you know, more traditional underwriting models, you know, what ultimately makes, you know, upstarts platform, you know, unique and, you know, more difficult to replicate.

太好了。这是一个很好的概览。而且，正如你提到的，人工智能和AI从未像现在这样受到如此关注。公司的许多创新竞争优势与基于AI的算法以及训练数据有关。你能否谈谈一下，关于Upstart公司的信贷模型，它如何与使用FICO和其他更传统的信贷模型相比较，最终是什么使Upstart平台独特且难以复制？

Sure. Yeah, AI is definitely bandied about in the press a lot these days and in the investment circles, of course.

当然，是的，如今AI在媒体和投资圈中的确被频繁提及。

The core concept in credit is pretty simple. The technologies used to predict risk in credit up until very recently. And, you know, the core of it has been this idea of a credit score. I guess, like, as an input, they're not particularly sophisticated compared to what we have in other sectors of the world, like consumer internet, in that they are, they tend to be linear models. They have a lot of restrictive assumptions that make it such that their ability to predict outcomes are less sophisticated. And of course, if you look at the outputs, if you try to correlate credit outcomes to FICO scores, you won't find a very strong correlation.

信用的核心概念非常简单。直到最近，信用评估中使用的技术一直都比较落后。核心就是信用评分的概念。相比于其他领域如消费者互联网，在输入方面，它们并不是特别复杂，通常采用线性模型。而这些模型有很多限制性的假设，导致它们在预测结果方面不够复杂。当然，如果你尝试将信用结果与信用评分进行相关性分析，你不会发现很强的相关性。

And so we had the simple idea of taking a lot of the technology that was being adapted for initially other uses. I mean, you think about things like email spam filters and search engines and, you know, consumer recommendations. Those are all using nonlinear predictive models, predictive models that relax the assumptions of interdependence between input variables that have been enabled by compute power. Like, that's all machine learning really is. It's a linear regression and is a machine model. The machine model is just taking amounts of data and training model to predict outputs. But they have a lot of constraining assumptions. And when you relax those, you need a lot of compute power. We now have the compute power to be able to explore nonlinear surfaces. And so it seemed obvious to us and many of us at the company come from a technology background. It seemed obvious that they would be a better prediction engine than essentially a linear regression.

因此，我们有一个简单的想法，即利用最初用于其他用途的许多技术。我的意思是，你可以想象一下电子邮件垃圾过滤器、搜索引擎和消费者推荐等等。这些都使用了非线性预测模型，预测模型放宽了输入变量之间相互依赖的假设，这是由计算能力实现的。换句话说，机器学习本质上就是线性回归和机器模型。机器模型只是利用大量的数据训练模型来预测输出。但是这些模型有很多限制性的假设。当你放宽这些假设时，就需要大量的计算能力。我们现在拥有足够的计算能力来探索非线性的表面。因此，对于我们公司中的许多科技背景的人来说，这似乎是显而易见的，非线性回归引擎应该比线性回归更好。

You know, what makes it unique and difficult to replicate? Well, the unique part is very simply, I think, for a long time, we were the only ones applying this to credit. Even today, I think there is very few, if any, parties out there that are applying modern machine learning at scale to the problem of credit prediction. Why is that? I mean, some of that is regulatory. I mean, historically, there is a lot of regulatory risk in lending. And so if you want to apply new models to lending, you have to invest a significant amount of resource in engagement with the regulatory bodies. And some of it is just, frankly, because of what I said, this stuff is pretty difficult. And it's non-native to financial services. I mean, most of this stuff was developed in the consumer and digital internet sphere. And there needs to be a cross-pollination of technology over time. A lot of the people who traditionally build these types of models, and it's not a massive labor pool, are coming from the big tech companies.

你知道，是什么使之独特且难以复制呢？嗯，我认为其中的独特部分非常简单，很长一段时间以来，我们是唯一将其应用于信贷领域的人。即使在今天，我认为几乎没有其他人在大规模应用现代机器学习来解决信贷预测问题。为什么会这样呢？我的意思是，其中一部分原因是监管方面的。历史上，信贷借贷领域存在着很大的监管风险。因此，如果你想将新的模型应用于借贷领域，你必须投入大量资源与监管机构进行合作。另一部分原因纯粹是因为我之前所说的，这种技术相当困难。而且，它对金融服务行业来说是非本行业的。我是说，大部分这些技术都是在消费者和数字互联网领域发展起来的。随着时间的推移，技术需要进行跨界相互借鉴。传统上构建这些模型的人员并不多，而且大部分来自于大型科技公司。

Now, why is it difficult to replicate? It's not impossible to replicate, of course. But credit has this unique thing, which is that in order to build these models, machine models require what's called training data, which in the case of credit is just historical examples of whether you got paid back or not. And in order to accumulate that training data, you need to lend a lot of money to a lot of people, and then sit around and wait to see if they pay you back or not. And that happens month over month, quarter over quarter. There's no real great way to accelerate that process. So it's not like other applications where you can just ingest a bunch of historical training data. It's not that people haven't been lending for the last 10 years as we have. But no one has collected against those repayments where the applicants went to school, what they studied, where they worked. So ultimately, you want to price new and alternative variables that are not considered by credit score. And so we now have 10 years of history and of data around how to think about how to price where someone went to school or where they're working. What does it mean to work at Goldman Sachs versus one of your competitors or versus a different industry? What does it mean to be a research analyst versus a banker versus a wealth manager? All of those roles and functions and areas of study have different implications on risk. And we've learned a lot about them. So for someone to try to replicate that, and in particular to do it while now competing against us, who's developed, I would say a lot of insight about that stuff can be very expensive and unpolatable. And it just takes time. There's no shortcutting at them. So that's I think the difficulty of others that will come down the path and what they will have to replicate over time.

现在，为什么复制这个很困难？当然，复制并非不可能。但信贷有一个独特的特点，就是构建这些模型需要机器模型所需的训练数据，而在信贷的情况下，训练数据就是关于你是否被还款的历史案例。为了积累这些训练数据，你需要向很多人借很多钱，然后坐等看他们是否还款。这种情况会持续一个月、一个季度。并没有什么好的加速这个过程的方法。所以不能像其他应用程序一样，只需导入大量历史训练数据。并不是说在过去的10年里没有人借款，我们有。但是没有人对那些还款中的申请人的学校、专业、工作进行过收集。因此，最终，你要定价新的和与信用评分不考虑的变量。现在我们有了10年的历史数据，关于如何考虑某人所在的学校或工作地点的定价。在高盛工作和在你的竞争对手或不同行业工作有什么意义？做研究分析师与做银行家或财富经理有什么不同？所有这些角色、职能和学习领域都对风险有不同的影响，并且我们对它们学到了很多。因此，对于其他人来试图复制这些内容，特别是在与我们展开竞争时，需要投入巨大的成本，并且难以复制。这需要时间，不能走捷径。所以我认为其他人会面临的困难就是他们需要随着时间去复制这些东西。

Great. That makes a lot of sense.

太好了，这样很有道理。

You talked a little bit at the beginning of our discussion around the resiliency of capital. Over the course of this year, I've started to announce several new long-term funding partnerships to build more resiliency into that funding model and ensure that the platform can continue to operate well even in more challenging cycles.

在我们讨论开始时，你稍微提到了资本的弹性。今年的过程中，我已经开始宣布一些新的长期资金合作伙伴关系，以在资金模式中增加更多的弹性，并确保即使在更具挑战性的周期中，平台仍能正常运作。

First, could you just talk a little bit about how Upstart's funding model has evolved over time? And what does the optimal funding channel mix look like for Upstart if there is one?

首先，您可以简要谈一下Upstart的资金模型是如何随时间发展的吗？如果有的话，对于Upstart来说，最佳的资金渠道组合是什么样的？ 而今，Upstart的资金模型经历了一些演变。最初，公司主要依靠风险投资（Venture Capital）来获得资金支持，并依赖于企业家和个人投资者的资金注入。然而，随着时间的推移，Upstart开始向其他资金渠道寻求多样化的融资途径。 现在，Upstart不仅依赖于传统的风险投资，还通过银行合作和证券市场进行融资。通过与银行合作，Upstart可以通过以平台为中介，将金融机构的资金提供给借款人，从而获取利息和佣金收入。此外，Upstart还通过证券市场发行债券来筹集资金。这些债券通过出售给投资者，将投资者的资金与贷款借款人匹配。 对于Upstart而言，寻求更优的资金渠道混合是重要的。这意味着公司需要通过多种资金来源，如银行与证券市场，来实现融资的多样化。这种多样化的资金渠道可以提供更稳定和可持续的资金支持，并降低Upstart对单一渠道的依赖。通过优化资金渠道的组合，Upstart能够实现更灵活、高效的资金管理，并更好地满足业务发展的需要。

Let's see. Well, historically we've had two notional channels for funding. One is involved essentially giving our technology to banks and credit unions. They would use that to originate for their own balance sheet. As the originating bank, they tend to predominantly be interested in primer borrowers or lower risk borrowers just by the regulatory construct of what a bank is. And then for what I would call the torso of the borrowing base, we've historically had the origination done on our behalf with a partner and then sold that asset to the institutional world. You can think of private credit funds canonically.

让我们来看看。嗯，从历史上来看，我们有两种资金筹集的方式。一种是将我们的技术授权给银行和信用合作社。他们会将其用于发放贷款，资金主要来自他们自己的资产负债表。作为发放贷款的银行，他们通常更偏向于优质借款人或者风险较低的借款人，这是由银行的监管构建所决定的。而对于贷款基础的核心部分，我们过去通常是与合作伙伴代表我们进行贷款发放，并将这项贷款资产出售给机构投资界，你可以将其视为私人信贷基金的经典模式。

The third sort of funding construct that you're describing which are these more long-term committed structures, I would say, are a sub-variant of the second category. They're sort of a type of an institutional relationship but with a capital partner that has the ability to think over a more fulsome investment cycle, they're not as reliant on leverage and trading as some of our existing partners. And they are structures in which we will contribute some modest risk capital.

你所描述的第三种资金构筑，更倾向于长期承诺的结构，我认为可以视为第二类别的一个亚类。它们是一种机构关系的类型，但资本伙伴能够更全面地考虑投资周期，不像我们现有的一些合作伙伴那样依赖负债和交易。在这些结构中，我们也会提供一些适度的风险资本。

So those are, I would say, how they were new and a bit different than some of our existing relationships. Ideal mix, I think that over time as we rescale the business, I think these more permanent, durable partnerships could form something like half of our funding base. I think that would be probably a nice base of durable capital that will create a bit more or buffer the volatility of the external markets a little bit more. And of the remaining, I think banks will always be the dominant competitors for very prime borrowers, just because of the cost of their capital is quite inexpensive, although it's changing. And I think there will always be a remaining, so maybe call it 30% banks and there will always be a place for what I would think of as the spot market. So funds coming in and out and trading out well, they create price discovery, they create liquidity. So that's maybe, I would say, an unsecured lending and ideal mix. As we expand to more and more secured products, I do think banks will remain the predominant funding sources for those products. Things like auto lending and residential lending. Those are lower risk products for which banks have very efficient funding chain.

因此，我会说，这些合作伙伴与我们现有的一些关系有一些新颖和不同之处。我认为，在业务规模得到重新平衡的过程中，这些更持久、更稳定的合作伙伴关系可能占到我们融资基础的一半左右。我认为，这将是一个稳定资本的良好基础，它将在一定程度上缓解外部市场的波动。而剩下的部分，我认为银行将始终是非常优质借款人的主要竞争对手，仅仅是因为他们的资本成本相对较低，尽管正在发生变化。而且我认为股市始终有着存在的空间。资金流入和流出，并且交易良好，它们能够创造价格发现和流动性。这可能是无抵押贷款的理想组合。随着我们扩大到更多的有担保产品，我认为银行仍然将是主要的资金来源。像汽车贷款和住房贷款这样的产品是较低风险的产品，银行拥有非常高效的资金链。

Great. I'd love to explore the new committed capital partnerships a little bit more in detail. You mentioned a little bit about the co-invest structure. So I was wondering if you could just talk a little bit about the economic impacts on upstart business model from some of these new funding structures. What tradeoffs are you making, if any, to bring more stable funding into the mix and what does a typical co-invest structure look like?

太好了。我很乐意更详细地探讨一下这些新的可靠资本伙伴关系。你刚刚提到了共同投资的结构，我想知道一下这些新的融资结构对创业型企业模式的经济影响。如果有的话，你为了融入更稳定的资金而做出了哪些权衡，并且一个典型的共同投资结构是什么样的？

Sure. Well, a typical structure is pretty straightforward. You could think of it as a partnership or a JV where we have a counterparty that is the majority partner. We will bring some very modest single digit percentage of the overall partnership as our own equity. But it's important because it demonstrates alignment of interest with someone who's committing forward over a term of one, two, three years. And so they want to know that our motivations a year from now will be aligned with theirs. So that's important. It also demonstrates us standing behind or eating or cooking, I guess you might say. And that's an important aspect of what essentially is a very deep strategic partnership. It's not a transactional relationship as we've been maybe more used to in the past. That structure, of course, may include some financing as well. That structure will be a sort of a lone buyer on our platform.

当然。嗯，一个典型的结构非常直接。你可以把它看作是一个合作伙伴关系或合资企业，我们有一个协议方是大多数合作伙伴。我们会作为我们自己的股权带来一小部分非常适度的百分比。但这很重要，因为它表明我们与那些在未来一两三年承诺向前推进的人的利益是一致的。因此，他们想要知道我们一年后的动机与他们的一致。这很重要。它还表明我们支持或承担了承诺，我想你可以这么说。这是一个非常深入的战略伙伴关系的重要方面。它不是我们过去可能更习惯的交易关系。当然，这个结构可能还包括一些融资。这个结构将是我们平台上的唯一买家。

The economic impact is interesting. It sort of depends on a couple of things. One is the extent to which this structure is targeting a return that may be higher than what you might think of as being delivered on the spot market. If there is a premium being delivered to that structure, it needs to come from one of two places. It may be passed on to the borrower and or it may be absorbed by our take rates. And the extent to which it's one or the other will depend on the elasticity of the borrower demand.

经济影响是有趣的。它在某种程度上取决于几个因素。其中之一是这个结构是否针对的回报高于你所认为的即时市场的水平。如果有额外的回报，那么它需要来自于两个地方之一。它可能会传递给借款人，或者可能会被我们的费率所吸收。而其中选择的取决于借款人需求的弹性程度。

So for example, in an environment like today where demand is very inelastic, there's not a lot of alternatives out there. There's a high demand, a high fundamental demand from borrowers for credit right now. You might believe that a lot of that premium to the extent it exists is getting absorbed by borrowers. You might imagine a world where that goes back to a very competitive world from a from a from a lender standpoint. And you might imagine that some of that will be absorbed into our take rate. So that would show up as contraction of contribution margin. But it's probably worth saying that what gave us the insight and the inspiration to do this to begin with is that if you've been following our financials through what's been a very tricky, it's a difficult period for a lending platform, we've flexed our contribution margins and our take rates up quite a bit in ways that I think a bit nonstandard in the lending world. And the reason is because in difficult periods like now, a lot of the lenders, a lot of the platforms and the issuers tend to hyper compete over very prime borrowers. And if you have the type of risk models where you can still decision risk in maybe the torso of the borrower base, there's still a lot of margin to play with. The fact that we've been able to flex our margins and our take rates up a lot has made us ask ourselves the question, huh, would we have traded some of that in exchange for more durable, more resilient funding base? And the answer is of course yes. And so that's what led us to sort of put some of our economics, I would say at stake in a relationship where the underlying funding, you know, the tradeoff is a much more resilient supply chain of capital.

例如，在像今天这样需求非常不弹性的环境中，很少有其他选择。当前借款人对信贷的基本需求非常高。你可能会认为，存在的大部分溢价都被借款人吸收了。你可能想象，从贷方的角度来看，世界可能会回归到一个非常竞争的状态。你可能会想象，其中一部分将被吸收到我们的费率中。因此，这将导致利润贡献率的缩减。但值得一提的是，最初让我们产生这个想法和灵感的是，如果你一直在关注我们的财务状况，会知道对于一个贷款平台来说，这是一个非常棘手的时期，我们通过一些非常非常标准的方式增加了利润贡献率和费率。原因是，在像现在这样困难的时期，很多借款人、许多平台和发行人倾向于对非常优质的借款人进行超级竞争。如果你拥有能够在借款人基础的中间层中进行决策的风险模型，那么还有很多利润空间可以利用。我们能够大幅提高利润贡献率和费率，这让我们自问自己，呃，我们是否愿意用更持久、更有弹性的资金来源来换取其中的一部分呢？当然是肯定的。因此，这促使我们在一种关系中把我们的一些经济利益置于冒险之中，其中底层资金的折衷是更强大、更有弹性的资本供应链。

Great. And you know, I appreciate the comments that you made around, you know, how the target yield for some of these committed capital partners can be funded either from the borrowers or your sales. I was wondering if you could talk about how the funding mix may be different in different economic environments as well. So for instance, you know, if the ABS market or demand for hole loans pick up a lot, would you see like that part of the funding mix grow dramatically, you know, set differently are some of these more durable capital solutions, more of an interim solution. It doesn't sound like it is, but we'd just love to hear you talk about funding.

太好了。你知道，我很欣赏你在论述中对于一些有承诺资本合伙人的目标收益如何来自借款人或者你们的销售方面的评论。我想知道在不同的经济环境下，资金混合方式可能会有所不同。例如，如果ABS市场或全款贷款需求大幅增加，你会看到资金混合中的这部分增长迅猛吗？换句话说，这些更持久的资本解决方案会更多地作为临时方案吗？听起来并不是这样，但我们很想听听你对资金方面的看法。

This is meant to be a long term strategy that will set us up for the next macro shock, whatever the current macro shock with some combination of the lockdown and the stimulus from the perspective of a lending business. The next one, God knows what it'll be. When we're back at scale, like I said, I mean, I think 50 plus percent of our funding base at scale we would like to be in this sort of committed form. And then the banks call it 30 and maybe the spot market 20. And the next time the next time a macro shock hits the spot market will contract as we've seen in this sort of most recent version.

这是一个旨在为我们在未来发生的宏观冲击时做好准备的长期策略，无论当前的宏观冲击是什么，这些都包括封锁和经济刺激的角度，对于一个借贷业务来说。下一个宏观冲击是什么，只有上帝知道。当我们恢复到规模的时候，我认为我们希望50%或更多的资金基础都以这种承诺的形式存在。而银行可能占30%，现货市场可能占20%。在下一次宏观冲击发生时，现货市场将会像我们最近看到的那样收缩。

The bank money is more resilient, but they, you know, they're going through their own industry specific things. And the 50, what is at scale 50 percent of our funding base should remain in absolute dollar terms the same. And that's kind of the point. There's other funding channels that have other interesting characteristics but are not durable and they will flex with the economy, but the committed funding base should not. And that's why it needs to be a long term strategy. It wouldn't make sense to have a long term committed sort of vehicle that is not a long term strategy, obviously. Then it's not, it doesn't have the kind of velocity. If we were just relying on that to sort of recover from the current, you know, lending environment, it wouldn't be the ideal way to do that in my opinion.

银行的资金更加有韧性，但他们却正在经历着自己行业特定的问题。而我们资金基础中有50％应该在绝对美元金额上保持不变。这就是关键点。还有其他一些有其他有趣特征的资金渠道，但它们并不持久，会随着经济而变动，但已承诺的资金基础不应该变动。这就是为什么需要一个长期战略的原因。显然，如果一个长期承诺的工具不是一个长期战略，那就没有意义了。那样就没有这种速度。如果我们只依靠它来恢复当前的借贷环境，我认为这不是理想的方式。

Okay. That's very clear. So can you talk about whether or not funding is still a constraint on origination growth? You know, it was at one point and obviously you guys have done a lot in improving your funding position. Are you, you know, actively seeking more committed capital partners or is the funding and the demand from the borrower side more aligned right now and you don't need that? Just, could you just mark the market on that?

好的。非常清楚。那么你能谈谈资金是否仍然对贷款业务的增长构成限制吗？你知道，曾经是如此，显然你们在改善资金状况方面做了很多努力。你们目前是否正在积极寻找更多承诺的资本伙伴，或者说目前借款方需求和资金供给是否更加协调，使得你们不需要更多资金支持？只是，请你简单回答一下这个问题。

Yeah. I think if you were to talk to the team like today, what they would say is the funding we've put in place is not the constraint on our business right now. The constraint is that it's just, it's very, very hard to approve borrowers right now for a bunch of macro reasons we can get into. And so finding the next borrower and being able to approve them is the constraint on the business. You know, that said, that can turn very quickly. There's a bunch of macro behaviors happening right now on the consumer side that can change quickly and mathematically, they're almost going to have to change. And when that happens, we're going to want to have the funding available. So there's still teams going out and continuing to pursue discussions with the capital sources. We probably can't put their dollars to work tomorrow, but a month or a quarter from now we probably will be able to and that's why we need to have that sort of ready.

是的。我认为如果你今天去跟团队交谈，他们会说我们目前的业务并不受到资金的限制。限制在于现在非常非常难以批准借款人，这是由于一系列宏观原因造成的，我们可以详细讨论。所以寻找下一个借款人并能够批准他们是业务上的限制。不过，要说起来，这种情况可以很快发生变化。现在在消费者端出现了一系列宏观行为，这些行为可以很快改变，从数学上讲，它们几乎必须改变。当这种情况发生时，我们会希望有可用的资金。因此，我们仍然有团队继续与资金来源进行讨论。也许明天我们还不能将他们的资金投入使用，但一个月或一个季度后，我们可能就能够了，这就是为什么我们需要做好准备的原因。

That's really helpful. I just want to make a follow-up question. I just want to make a follow-up in the background just to make a sort of a constraint. When I go to sort of your screen.

这真是太有帮助了。我只是想提一个后续问题。我只是想在背景中进行一种后续操作，以形成一种限制。当我前往你的屏幕时。

Oh, hi. Does this work? Yeah. So following on from your last point, Anon took about that constraint. Have you thought about linking up with PAGAYA technologies in order to increase loan origination because when I analyze sort of your volume growth, I think it would be a good tie-up in the sense that you're not competing because they're not beat to see. And it feels like you could increase your volumes by say probably like 20% with an attractive 5-core score and attractive returns. Is that something you've thought about it?

噢，嗨。这个工作吗？是的。所以继续你上次提到的那个问题，匿名讨论了那个限制。你有没有考虑过与PAGAYA科技合作以增加贷款业务，因为当我分析你的成交量增长时，我认为这是一个很好的合作机会，因为你们并不是竞争关系，因为他们也不是针对同一客户群。而且感觉上，通过提供吸引人的5核分数和回报率，你们可以增加大约20%的成交量。你有没有考虑过这方面的事情？

Yeah. So we know the PAGAYA guys well. They're another example of a company that does a lot of the same things we do. As you say, they're in a bit of a different business model than ours. Also this, we talked to them regularly. I think that the uplift they're able to find with other platforms in their kinds of programs is largely because their models are very differentiated and many of the issuers have very sort of credit score centric models. So they can create huge uplift. With us, the type of model they pursue is that like if the platform doesn't want the loan, they'll send it to PAGAYA and PAGAYA can price it. I don't think they can create a 20% uplift on our approval, on our models. We do experiments with them and we sort of are in a good-natured partnership with them and we try to learn how our models are different. And there may or may not be a point in the future in which we sort of find a way to work together. But it's certainly, I don't think, for us or for them, we create the kind of economic benefit that they have when they work with someone who has a very traditional model which is sort of the point.

是的，我们很了解PAGAYA的团队。他们是我们的一个典型例子，做了很多和我们类似的事情。正如你说的，他们的商业模式与我们有些不同。此外，我们经常与他们交流。我认为他们能够在其他平台上找到的增长主要是因为他们的模型非常独特，很多发行商的模型也非常以信用评分为中心。所以他们能够创造巨大的增长。对于我们来说，他们追求的模型是这样的：如果平台不想要贷款，他们会把它发送给PAGAYA，然后PAGAYA会定价。我不认为他们能够在我们的批准和模型上创造出20%的增长。我们和他们合作进行实验，并且友好地互相合作，试图了解我们的模型有什么不同。也许在将来我们能够找到一种合作方式，但对于我们和他们来说，我们不会像传统模型一样创造出他们与其他人合作时所拥有的经济利益，这也是问题的关键点。

Great. You mentioned some of the impacts from the macro. You can just talk about how you see the current macro environment impacting your business, what your outlook for the third quarter and the rest of the year assumes. And I think it'd be helpful if you could touch on what you're seeing from the upstart macro index, the UMI and how the company uses that to guide credit decisions.

太好了。你提到了宏观经济对企业的一些影响。你可以简单地谈谈你对当前宏观环境对你的业务的影响，以及你对第三季度和整个年度的展望。我认为如果你能谈谈你对新兴宏观指数UMI的观察以及公司如何利用该指数来指导信贷决策，会很有帮助。

Yeah, so there's a bunch of topics in there. The macro is a very strange thing right now as you know. There's a lot of, there's a very wide distribution of opinions on it even more than usual. There's anxiety, at least recently, around inflation and rates. Seems to be subsiding a little bit.

是的，所以其中有很多话题。宏观经济现在是一件非常奇怪的事情，正如你所知。关于它的观点分布很广，甚至比平常还要多。最近，人们对通货膨胀和利率感到焦虑。看起来焦虑有所减少。

On the other hand, the labor market is as strong as it's ever been. Consumption is as strong as it's ever been in real terms. And so it's a bit hard to know what to make of it. Our view, from the perspective of how it's impacted lending, our view is very clear.

另一方面，劳动力市场一如既往强劲。实际上，消费也是空前强劲的。因此，很难说该如何看待这种情况。从对其对借贷业务的影响的角度来看，我们的观点非常明确。

A lot, so it's been a turbulent time and almost all of it is attributed to the stimulus. And in particular, the stimulus did two things. And it did a lot of things, but from the perspective of someone who wants their loan paid back, it did two very particular things.

很多事情发生了，所以这段时间非常动荡，几乎所有的事情都归因于刺激措施。具体来说，刺激措施做了两件事情。它做了很多事情，但如果从想要借款得到归还的人的角度来看，它做了两件非常具体的事情。

One, it, I think it was a very significant, if not the most significant factor in the inflation we have. There's supply side stuff as well, but like, you know, if you pump $5 trillion into the economy, unsurprisingly, it's going to contribute to price inflation.

其中一个因素是，我认为它是通胀中非常重要的，如果不是最重要的因素。当然，还存在供给方面的因素，但你知道，如果你向经济注入5万亿美元，不出意外，它将促使价格上涨。

And the other thing it did was it caused a relatively sizable, after the volatility of the lockdown, it caused a very sizable increase in real consumption, relative to income. And of course, that was, you know, it's funded by the stimulus. And when the stimulus ended, the consumption didn't go back down. Instead, what happened was consumers have run their personal balance sheets down to a level that's razor thin. And I don't know why they did that. I have theories. But that's, those are the facts.

另外一个影响是，封锁带来的震荡之后，相对于收入来说，实际消费出现了相当大的增长。当然，这是通过刺激措施提供资金支持的。当刺激措施结束时，消费并没有下降，相反地，消费者将个人资产负债表压缩到了非常薄弱的程度。我不知道他们为何这样做，我有一些理论，但这就是事实。

If you look at the savings rates in the economy, if you look at the deposit base and how it's contracted, and that's really at the root of a lot of the problems we see in the banking sector, it's just, it's created this different sort of pattern and behavior in how consumption and income play together, such that everyone's balance sheets and particularly those who are less affluent are much thinner than they were pre-COVID. And the combination of the inflation and the fact that even in real terms, people are essentially living on a relative basis beyond their means compared to what we were pre-COVID has meant that, what, defaultiness in the credit world has gone up, it's gone up a lot.

如果你看一下经济中的储蓄率，如果你看一下存款基础及其收缩的情况，这实际上是我们在银行业出现许多问题的根源，它创造了一种不同的消费和收入相互作用的模式和行为，从而导致每个人的资产负债表，特别是那些较不富裕的人，比COVID前更为脆弱。通胀和事实上，人们相对于COVID前生活在相对不切实际的基础上，导致了信贷世界中的违约率上升，上升得很多。

You mentioned the, we call the UMI, the macro, upstart macro index, is essentially our best expression of that. It's nothing more than, it's an index which tracks losses in our loan book after controlling for all changes in borrower characteristics over time, and all changes in our underwriting models over time.

你提到的，我们称为UMI的宏观指数，实质上是对此的最佳表达。它不过是一个指数，跟踪我们贷款账本中在借款人特征以及核准模型改变后的所有损失变化。

So it's a, it's a mix suggested, apples to apples view of how the same borrower is defaulting, at least in our book, but we have a very broad book over time due to the economy, or I guess well, due to things that are extraneous to us. And it would show you that, you know, if that, if that index read as a 1.0 pre-COVID, with all the stimulus, it went down to 0.5 or 0.6, which means losses are half or 60% of what they were pre-COVID. So they were very good.

所以这是一个建议混合的视角，就仿佛我们的书中的同一借款人违约情况，但由于经济原因或者说是超出我们控制范围的事情，我们的书在很长一段时间内非常广泛。它可以向您展示，您知道，如果在COVID-19前，该指数读数为1.0，经过所有的刺激措施后，它降至0.5或0.6，这意味着损失减少了一半或者百分之六十。因此，它们非常出色。

And that index is now sitting at 1.7 almost. So it meant that, you know, after the stimulus ended, savings rates plunged to the lowest level since the World War. Like, if you look at the, the history of the personal savings rate, which is printed by the Fed, it's somewhere between 3 and 15 percent since they started printing the number, and it's currently at 3.

现在该指数已经达到1.7水平了。这意味着，在刺激政策结束后，储蓄率降至自第二次世界大战以来的最低水平。例如，如果你查看由美联储发布的个人储蓄率历史数据，从开始统计以来一直在3%至15%之间波动，而目前则为3%。

So that, you know, coincided with this index now sitting at a level which is 70 percent higher than it was pre-COVID for these borrowers in this particular product. So that's, that's, I think, how we would best express the economic lens from the perspective of a lender, certainly in the unsecured world, and a little bit about what we think is at the root of it.

因此，你知道的，这与目前这个指标达到的水平同时发生，这个水平比COVID前对这些借款人在这个特定产品上高出70％。所以，这就是我们认为从贷款人的角度最好地阐述经济视角的方式，尤其是在无担保世界中，并且对我们认为其根源的一点见解。

Yeah, great. Why don't I sneak one more question in before I see if there are any other questions from, from the audience. But I, I do want to ask about your outlook on U.S. unsecured personal loans. Obviously, your, your most established loan product. The market was about $170 billion in 2022. You know, what's your view on the potential growth in that unsecured personal lending market?

是的，很好。在回答观众的问题之前，我可以再提一个问题吗？我想问问你对美国无抵押个人贷款的前景如何。显然，这是你们最成熟的贷款产品。2022年的市场规模约为1700亿美元。你对这个无抵押个人贷款市场的潜在增长持什么看法？

What's driving the demand is upstart, you know, helping to grow the market by, you know, helping to lend to these underserved borrowers, or are you taking share from, you know, established players, or both? Well, neither in 2022. There is a, the extent that the pie grew, we were not at the root of that. We've, we've reacted to this severe increase in default rates by reducing approval rates and contracting.

是什么推动了需求的增长呢？就是这些新兴的公司，你知道的，通过帮助这些未被服务到的借款人，促进了市场的增长，或者说是夺取了那些已经建立起来的竞争者的份额，或者说两者都有？嗯，在2022年都不是。虽然市场规模扩大了，但我们并不是驱动这一扩大的根本原因。我们对严重增加的违约率做出了反应，通过降低批准率和收缩规模来应对。

But if you want to talk about it in more of a secular level, yeah, you know, unsecured lending is a very young product. It was sort of, it was birthed by the internet. It was very hard, it was, it was very hard to do an unsecured loan for $10,000 if you're in a bank branch. So as a result, banks had the product, but they didn't push it. It wasn't economical for them. And you sort of had to like know about it and go and ask the manager. So there was no real unsecured term loan category before the digital players started making it economically feasible. And it's obviously been on quite a growth clip. Pre-COVID, it was the only flavor of credit that I think had significant growth. Now that, you know, the numbers have all changed a little bit. But it was growing because it's a useful product.

但如果你想以更加世俗的角度来谈论这个问题，是的，你知道，无担保贷款是一个非常年轻的产品。它在互联网时代诞生了。如果你在银行分行要申请一笔1万美元的无担保贷款，这是非常困难的。所以，虽然银行有这种产品，但他们并不推广。这对他们来说是不经济的。你只能事先了解并去咨询经理。所以在数字化平台开始使其在经济上可行之前，真正意义上的无担保贷款类别是不存在的。显然，它一直在以惊人的速度增长。在COVID疫情之前，我认为这是唯一增长显著的信贷品种。现在情况有所变化，但它之所以增长是因为它是一个有用的产品。

I mean, I think it's, it's, it's easy to obtain. It's digitally, it's digital native. And in many cases, the pricing was getting good enough such that, you know, the benefits you were to get on pricing from getting a secured loan like a HELOC or even an auto loan in some cases weren't worth the extra sort of trouble you had to go through in the liens and notarizations and all this stuff. And so it started, I think, on the one end, eating into the credit card market and on the other end, eating into the secured market like places like HELOCs and such. And, and yeah, I think a big part of how we participated in that was the growth of the market.

我的意思是，我认为它很容易获得。它是数字化的，是数字原生的。而且在很多情况下，定价足够好，以至于你知道，通过获得像HELOC这样的抵押贷款或甚至是汽车贷款得到的价格优惠不值得额外的麻烦，比如抵押和公证等。因此，我认为它开始侵蚀信用卡市场的一方面，在另一方面侵蚀像HELOC这样的抵押贷款市场。是的，我认为我们参与其中的一个重要方面是市场的增长。

The way we think about market share, by the way, wasn't, wasn't as us taking from a fixed pie. If you think about us at our peak volume when credit was really good post stimulus, our conversion rates, by that I mean, of all the people who applied for a loan, how many got one, it was about 20%. Right now it's about 10%. So our political rates have pretty much halved. But of the 80% that we're looking for a loan and didn't get one from us, you know, you can see in their credit reports, they didn't typically get it somewhere else. If we couldn't approve them, they probably weren't getting the loan or if they didn't like our offer, they weren't getting a better one elsewhere, by and large. So it meant that 80% of the market was unconverted, even at our, the peak of our volume. And our growth was really a story about improving that conversion rate. When we were improving our conversion rate, we were essentially pulling people into the market. So the 100, I think you had a 170 billion dollar number in 2020. That's the 20% of the market that's converting. There is a group of people four times that size that are looking for the product have applied for it and either not getting approved or the rate was just too high and they were like, that's not, I'm not, it's not good enough yet. Right. And the risk models getting better are what's going to improve both the approval rates and the acceptance rates because it's going to be pricing down. So I view it as a giant unconverted market that we will convert through better risk pricing.

顺便说一下，我们对市场份额的看法不是从一个固定的饼上获取。如果你想到我们在信贷环境良好的刺激措施后的高峰期，我们的转化率，也就是申请贷款的人中有多少人得到了贷款，大约为20%。现在大约为10%。所以我们的批准率几乎减半了。但在那80%中，他们寻求贷款却没有从我们这里得到的人，你可以在他们的信用报告中看到，他们通常也没有从其他地方得到贷款。如果我们不能批准他们，他们可能就得不到贷款，或者如果他们不喜欢我们的报价，他们就不会在别处得到更好的报价。所以这意味着即使在我们的产能高峰期，市场的80%仍然没有转化。而我们的增长实际上是通过提高转化率实现的。当我们提高转化率时，实际上是把人们吸引到市场中来。所以你在2020年提到了一个1700亿美元的数字。这代表了市场中的那20%正在进行转化。还有一个四倍于此规模的群体正在寻找该产品，并已经申请了，但要么没有获批，要么利率太高，他们觉得还不够好。而风险模型的改进将提高批准率和接受率，因为它将使定价降低。所以我认为这是一个巨大的未转化市场，我们将通过更好的风险定价来进行转化。

Great. Any questions from the audience? We got one up here, please. Just the mic's just going to go. Sure. What's the progress on auto loans and also on getting more dealerships there on board with your software?

好的。听众有任何问题吗？我们这边有一个，请。可以传话筒。当然。关于汽车贷款的进展以及与您的软件合作的经销商是否有更多加入的情况怎么样了？

Great question. So yeah, auto loans was I think the next big thrust for us when I think the market became a stiff headwind and I would say that as a result, the business itself and the scaling of the lending in auto is a little bit subject to the recovery or to the sub the moderation of those headwinds.

很好的问题。是的，当市场变得困难时，汽车贷款是我们接下来的重要推动力，我想说，由于这种情况，汽车贷款业务及其规模的发展有点取决于市场的恢复或缓解这些困难的程度。

I think under the hood, our strategy involves a couple of things. One is getting more and more dealers to use our software to sell the car, not to finance it. So it's nothing to do with lending, but we want more and more dealers to use our software to sell the car. So we've got some software package that's trying to modernize the car buying experience for the user and the dealer at the point of sale for anyone who's bought a car in a dealership recently. It's a pretty archaic process from a systems perspective. And so there's a couple of companies out there including us that are trying to modernize that. One of the companies that's in the lead in terms of getting OEMs and dealership groups to modernize their stack. And then of course, within that, we introduce our lending product. So it's a bit of a Trojan horse strategy.

我觉得我们的战略中有几个方面。首先是让越来越多的经销商使用我们的软件来销售汽车，而不是为其提供融资服务。所以这与贷款无关，但我们希望越来越多的经销商使用我们的软件来销售汽车。所以我们有一套软件方案，旨在为最近在经销商购买汽车的用户和经销商提供现代化的购车体验。从系统的角度来看，这是一个相当古老的过程。因此，包括我们在内的一些公司正在试图现代化这一过程。在获取原始设备制造商和经销商集团进行现代化方面，我们是领先的一家公司。当然，在这个过程中，我们还会引入我们的借贷产品。所以这是一种类似特洛伊木马的策略。

I think the number of dealers using our software now is somewhere north of 800. It continues to grow nicely. The penetration of the lending product into that 800 sits at about, I don't know, Jason, I want to say like 60. What are the public numbers? 40. So it's a very small penetration of the overall base. What's gating that is the availability of the capital. So auto lending segment right now is an area where a lot of the funding sources are very conservative. Lots happening with used car prices. A lot's happening with subprime auto default rates. And so I think we have a lot of interested funding parties, but they're all waiting to become comfortable with the macro when they do. And they're ready to start lending at volume. We'll start rolling out the lending products to more and more of the 800 installed base and we'll continue to try to grow the 800.

我认为现在使用我们软件的经销商数量应该超过800个。它持续不断地增长。贷款产品在这800个经销商中的渗透率大约是60%，具体数据我不清楚，Jason，你知道公开的数字是多少吗？是40%。所以相对于总体基数来说，渗透率非常低。造成这一情况的原因是资本的可获得性。目前汽车贷款领域的资金来源非常保守。二手车价格发生了很多变化。次级汽车违约率也在发生很多变化。所以我认为我们有很多有兴趣提供资金的方，但他们都在等待宏观环境变得稳定后才会开始大规模放贷。我们将开始向更多安装了我们软件的800个经销商推出贷款产品，并继续努力扩大这800个。

So all that to say from the perspective of our financials, not much looks different than last quarter. But I think under the hood, there's more and more spring loaded potential energy waiting to be unleashed once there's a sort of a cooperative funding market.

所以，从我们的财务角度来看，和上个季度相比，几乎没有什么不同。但是我认为，在背后，还有越来越多的潜在能量正在等待释放，一旦建立合作的资金市场。

Any other questions from the audience? Sanjay, maybe in the last minute that we have, I was wondering if you could talk a little bit about what's most top of mind for you as we navigate through the current climate. We've talked a lot about funding capacity for auto funding for personal loans, improving the top of funnel R&D. There's a lot of things that are certainly top of mind for investors. So what are you most focused on?

听众还有其他问题吗？Sanjay，在我们最后一分钟，我想知道你在应对当前环境时最关注的是什么。我们已经谈了很多关于汽车融资和个人贷款资金能力、改进研发的顶层漏斗等等，这些无疑是投资者最关注的事情。那么你最专注于什么呢？

Yeah, at a notional level, I think there's a lot of amazing progress in our business that is not seeing the light of day because of the macro environment, but will. And so the notional philosophy right now is just to continue making the business as good as possible, knowing that at some point it'll manifest itself. In particular, the spirit of never wasting a good crisis, I think we have and will continue to get much better at understanding and reading and reacting to macro shocks. Historically, that was not our focus as a company. We used to try and focus on borrower level evaluation and relative ranking of risk across a borrower pool. We'll never be in the business of predicting the next macro shock, but I think the ability to react to it more quickly than anyone and more precisely than anyone I think is within our capabilities.

是的，在概念上，我认为我们的业务已经取得了很大的进展，但由于宏观环境的原因并未见光，但这一切将会改变。所以现在的概念性的哲学就是继续提升业务水平，知道总有一天它会显现出来。特别是在从危机中汲取经验的精神方面，我认为我们已经并将继续在理解、分析和反应宏观冲击方面取得更大进步。在公司的历史上，这并不是我们的重点。我们过去曾试图集中精力评估借款人的风险和相对排名。我们永远不会从事预测下一次宏观冲击的业务，但我认为我们有能力比任何人更快速、更准确地对其做出反应。

Creating a much more resilient supply chain of money so that the next time some macro shock happens and it will, we will have a more resilient supply chain. I think that's area make progress and continue to. And then the other area, frankly, which has always been a huge opportunity for us as a machine learning company that we've never put much focus on is in applying those models, those predictive models to servicing and collections. And because that's become a very important topic right now, we are putting the extent we're doing any net hiring and resource application it's in that area. You can imagine how predictive models might be very useful in that sort of activity. Those are areas that have not been traditional focuses of the business that we're taking this opportunity to really shore up so that when we come out of this, we're going to be a much stronger company.

我们正在创建一个更具弹性的货币供应链，以便下一次发生宏观冲击时（因为必定会有），我们将拥有一个更具弹性的供应链。我认为这是一个正在取得进展并将继续发展的领域。另外，坦率地说，作为一个机器学习公司，我们一直未能在应用这些模型（即预测模型）到服务和催收方面上下足够的功夫，而这一领域一直是一个巨大的机遇。由于目前已成为一个非常重要的议题，我们会将任何招聘和资源分配的重点放在这一领域。想象一下，预测模型可能在这种活动中非常有用。这些都是业务中传统关注的领域，我们正在抓住这个机会，真正加强这些领域，以便在度过这个困境后，我们将成为一个更强大的公司。

That's really exciting to hear. That's a good way to cap off the session. So, Sanjay, thank you so much. It's been such a privilege to be able to share the stage with you. I'm pleasure. Thanks, Sanjay.

听到这个消息真的很令人兴奋。这是一个很好的方式来结束本次会议。所以，Sanjay，非常感谢你。能够和你一起分享这个舞台真是一种荣幸。我很愉快。谢谢，Sanjay。