播客28.与帕斯卡尔米尔豪斯谈的网络核武器,Cyber​​ Cube Ceo,关于为网络承销提供控制增长

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播客


在这一集中,Matthew Grant在美国访问他的英国办公室的Cyber​​ Culaire of Cyber​​ Millaire探讨了建设保险定价和投资组合管理的网络模型的挑战。  

Cyber​​ Cube. 于2018年推出作为赛门铁克的旋转。由于推出以来,Cyber​​ Cube已向客户签署了主要的保险公司和经纪人,包括CNA,Chubb,慕尼黑Re,Guy Carpenter和JLT Re。

根据Pascal的说法,问题并不缺乏数据。这只是数据很难通过,难以清洁和难以理解,以便有人试图承担风险,或管理网络聚集。他讨论了从赛门铁克等合作伙伴那里获得防火墙数据访问的好处,以及在趋势成为索赔之前提供前瞻性风险的前瞻性观点。

2018年10月,Cyber​​ Cube也是Instech伦敦网络活动的发言者之一,以及从夜晚的活动和视频的完整细节 可以在这里找到。

这里 科技前沿播客28.它也可以在iTunes上提供, Spotify., 和 讲话

有关开发网络市场的更多信息,请阅读Matthew Grant的文章 网络风险:保险黑洞还是大量机会? 

要找出我们在未来甲型伦敦活动中提出的东西,并阅读我们在每周通讯中所说的内容找到我们 www.科技前沿。

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此播客的成绩单

00:09 Matthew Grant:您好,欢迎来到科技前沿播客。这是Matthew Grant,伦敦举行的伙伴之一。今天,我们很高兴为您带来与帕斯卡米尔豪伊的采访。 Pascal是Cyber​​ Cybube快速增长的网络建模公司Cyber​​ Cobe的首席执行官,他在去年已经与一些主要的保险公司和再保险公司签订了合同,包括慕尼黑Re,Chubb,CNA,以及几个经纪人,这样作为盖伊木匠和jlt。

00:45 MG:Pascal,欢迎来到伦敦,感谢加入甲型伦敦播客。你自己是播客听众吗?

00:51 Pascal Millaire: You know, I'不。我唯一听的播客是纽约时报,每天。但我怀疑在这次采访结束时,我'll also be subscribing to your one.

01:02 MG: Good, well so, CyberCube, you sort of came out of, I guess, stealth mode last year. You'在赛门铁克的背景下了。听到你的是你是有帮助的'重新关注在网络上的关注're offering to the marketplace?

01:18 PM: Sure. Well, perhaps we'LL从一点上下文开始,这是2015年的明显,即网络保险是在数十年中出现的最快的保险。这种增长没有表现出缺陷的迹象。所以,赛门铁克作为世界'最大的网络安全公司,想知道赛门铁克是否有机会参与这种增长。特别是,鉴于公司运营世界之一's largest civilian intelligence networks with a lot of data, the CyberCube business unit was set up in 2015 to try to make sense of that data with some of the hardest problems that insurers were facing as they were seeking to insure, to underwrite, and to model this very new risk.

02:08 MG:鉴于网络周围的所有注意力,虽然我再次想回到缺乏的缺乏,在过去几年中的大型CABS网络事件以及市场上的意思。但最近有一份报告从威利斯重点关注网络,它有70家公司在那里列出。有趣的是,我认为它错过了两个主要的竞争对手。但是,当您在市场中定位自己并与在此空间中看到很多活动的保险公司时,您如何区分网络碳纤维,以及您在某种程度上做的事情,即您实际上可以参加这些组织中的决策者?

02:45 PM: We play a very, very specific and quite niche role that we think is really critical to the future of this entire industry. We're not an MGA. We'重新开始旨在扰乱现任者的启动保险公司。我们'重新在该生态系统中扮演一个非常独特的作用,我们通过我们的软件作为服务分析平台的角色实际上能够在现任保险公司和再保险公司中实现受控增长。所以,当你看看这个景观时,我认为你看起来这一点'继续扰乱保险业,我觉得毫无疑问会有破坏,但同样在那里'对于像Cyber​​ Cube这样的公司与现任保险公司和重新保险公司合作,并在我们的案件中扮演的致命作用使他们能够以受控的方式增长,以他们的最快增长,最重要,最重要的风险之一're going after.

03:55 PM: And I think we'在一个非常独特的位置,以非常鲜明地做到这一点。而且,我认为,任何良好的建模真的都是具有非常好的数据的基础。因此,Cyber​​ Cube继续拥有独家,从赛门铁克等合作伙伴的防火墙数据访问,这意味着我们'在趋势成为索赔之前,重新能够提供风险的前瞻性观点。然后'真的,如果他们为保险公司做的真的很重要'重新尝试建模这种风险并了解它。我想在网络空间中'不够依赖历史索赔。它's lots of near-miss data, if you like, coming from the cybersecurity landscape, that I think is really very, very important.

04:52 PM: One of my pet peeve topics in this space is when people say that the big problem with cyber insurance is the lack of data. And I really disagree with that point because I would argue there'实际上从来没有是一系列保险,P&C保险,提供更多数据。问题是't a lack of data. It's just that that data is really hard to come by, really hard to cleanse, really hard to make sense of in a way that someone trying to price this risk, underwrite this risk, or manage cyber aggregation needs to do.

05:37 MG: If it'可以通过这种方式缩小它,您认为保险公司要求您解决的一个或两个关键问题?它'没有MGA,显然你'没有表现为分布,你're not looking at their capital, but what are they hoping that you can help them solve or make better decisions on?

05:58 PM:今天对网络保险公司的两件事非常重要;第一个是承保或单风险选择。保险公司正在转向Cyber​​ Cube,以帮助他们真正看看更具技术和数据驱动的风险分析,以帮助他们选择为谁提供网络保险,而且价格如何?并且批判性地,让他们了解他们可能希望在他们正在销售的网络保险政策之上划分的后处理风险或猫风险负荷之间的差异。所以我们真正帮助保险公司的第一件事是单一风险的承销。

06:49 PM:二是企业资本管理。我认为随着保险公司销售1000,10,000,数万美元的这些政策,还有真正的积累风险,并保险公司需要数据驱动的工具,以便能够了解他们自己的内部报告,监管机构的聚合和积累,用于评级机构,用于再保险转移目的。因此,这些是两个领域,承保风险和建模灾难性的网络聚合,我们正在帮助保险公司。

07:33 PM: And I would say that equally important is to serve insurers on those topics, we'真的发现保险公司唐 't want separate tools to run and manage this risk, in the same way that perhaps for other lines of business, you can treat cat risk separately from some of those more attritional losses. This is a space where you really need the same data, the same assumptions, the same models, and you need to make sure that that data is delivered, and those analytics are delivered to that enterprise risk management individual, or that underwriter, in a form that they can understand, which is often not the kind of technical data and technical analysis that a cybersecurity or technology company might be feeding to an insurer. Because the insurance industry really needs very different things packaged in very different ways.

08:29 MG: Yes, because ultimately, it'对承保的关键投入;您需要给予人们可以做出决定的信息,所以您可以提供尽可能多的数据。但如果他们可以'实际上是关于它的决定,然后他们'实际上没有好转,或者甚至更糟糕的话,而不是如果他们没有't have that data. Just to come back to you, you talked earlier about behind-the-firewall. Can you just explain that a little bit more, about what that means versus the other ways of people characterising cyber models?

09:02 PM: Sure. So one of the more common ways to access data that I think startups and other technology companies are starting to use in this space is outside-in, publicly-available data scraped from the internet and from IP traffic, for example. And we think that'S建模非常重要的组成部分,它'肯定非常有助于能够从外面看一些东西。这么说,我们也相信'S根本不足以可靠地模范空间。因此,作为一个例子,您需要实际地落后于防火墙并从内部查看信息。给你一些例子,给出了大约一半的声称,我们的客户今天看到了电子邮件 - 电子邮件网络钓鱼 - 你只需'T有一个透视电子邮件网络钓鱼攻击和趋势,而无需看到电子邮件后面的电子邮件数据。所以我们'重新幸运是赛门铁克的独家数据合作伙伴,扫描了世界的相当大's enterprise emails every day.

10:21 PM:同样,当我们看看猫事件和灾难性的网络事件时,最终,一些非常糟糕的事件是终点的感染:恶意软件,自我复制和迅速传播的病毒。嗯,如果你真的想了解它的模型,你需要从那些帮助你辨别到攻击的那些端点的那些端点的后背 - 防火墙数据,以及如何在它开始时模型恶意软件的传播传播。因此,我们认为防火墙数据背后是可信地建模这种风险的真正关键部分。我们非常幸运地现在与赛门铁克的不仅仅是一个数据伙伴,以帮助我们可靠地为保险公司造型。

11:19 MG: And that behind-the-firewall, and the resolution of data you get there, is that important because underwriters are now looking to do individual account-based underwriting, and they want to know, for example, what is the risk to BMW? Or is there something different that's发生在重要的数据中,这较少针对个人账户承销?因为我认为任何构建模型的任何人的风险之一就是在投资组合层面上的余额,是否会在投资组合中使用它,而不是他们将它用于风险选择?两个非常不同的方法,两种不同的资本都会落后;猫风险与整个投资组合。所以在你的意思方面 're offering for CyberCube, are you giving people the ability to go into that individual account level, or are you more at the portfolio level?

12:13 PM: So we offer both. And I think some of the most distinctive analyses for us end up coming at the micro-segment level. Because what we'能够与我们的建模有关,就是说,"好的,吧让'看看像在线零售商这样的特定行业。让'看看像德国这样的特定地理国家。让'看看一个特定的收入乐队。因此,收入超过1亿美元。然后让我们'看看那个微段,真正从防火墙的角度来看,在多大程度上是对手瞄准的一段?例如,在多大程度上是一个具有真正良好的修补节奏的细分?"而且我认为微段信息如果你是绝对关键're an underwriter, trying to understand this risk and trying to understand the differences between perhaps another micro-segment like a West Coast United States hospital system, for example.

13:31 PM: So, I think at CyberCube, we endeavour to provide information at all levels. I would say one of the challenges is always differentiating the signal from the noise. We have a lot of data points that are available on an outside-in, publicly-scraped basis, rather than at that behind-the-firewall micro-segment basis, about companies. And a lot of that we do think is noise, frankly, but there are also signals that we think are very, very important in terms of differentiating single risks and single companies. For example, if you'我想了解公司的相对网络安全,我赢了't tell you it'非常容易,但当然,那里's a very, very direct link to the observable SSL security of the web assets that they have, and the security posture of the website of that particular company.

14:45 MG: I'对不起,只为任何人's not familiar with the terminology – SSL - what does that stand for?

下午14:51:右,所以基本上是一种安全,加密的互联网流量的形式。

14:58 MG: How do companies assess the right choice? There's在工具的功能上选择,那里有一个选择'围绕业务声誉的选择,但这些日子的许多公司都雇用了聪明的人,有时他们实际上建立了模型。您如何帮助您在您的客户中教育您的客户'真的在做什么?您如何在您揭示的信息和可能是专有或机密的事情之间的平衡如何,因为你不'不希望它进入竞争激烈的市场?因此,您如何为人们提供足够的信息,以便能够理解您的信心're doing? And in particular with modelling, understand the assumptions -  they don't expect them to be right - but not give away too much?

15:43 PM: Right, I actually don'认为这是一个主要问题,在这个特定的空间中放弃太多。因此,透明度对我们的投入和产出来说非常重要。我想我们是什么'找到了,与你在哪里相反'在揭示什么方面,重新与那个问题进行了一些问题'专有的专有,我们向我们的保险客户和重新保险客户展示的更多层,以及他们看到令人难以置信的工作量,以至于我们的建模'再做,我们从中拉的令人难以置信的数据来源,以及模型的复杂性,他们发现他们绝对没有'T想自己做到这一点,实现我们的价值're providing. So, actually, we take quite the contrary view of actually, really going very, very deep into our models, as deep as our clients wish to go in terms of those inputs and outputs.

16:45 PM: Saying that though, I think it'对于客户真正自己的风险观,也很重要。因为最终,如果你 '重新承担溢价数亿美元的载体,在溢价中进行数十亿美元,数十亿美元的总量被保险,你真的需要了解你的工具'重新使用。因此,一些硅谷公司喜欢谈谈提供解决方案,我真的很害羞地远离这个词。我实际上想考虑我们的东西're providing as a tool and a set of tools, but ultimately, carriers need to understand those tools, understand how to use those tools, understand the limitations of those tools, and really develop their own capability in-house to really get up to speed on what is a very, very important new risk.

17:46 PM: And so one of the first things that we do when we on-board clients is, we'在世界各地的多达10个不同城市飞往我们的方法,我们的数据来源,我们的假设,让人们所知,让人们知道'进入模型。它'还为什么我们为他们提供能力,在输出方面,进入大量的粒度细节,特别是在我们的灾难模型上,这样这件也是如此'一个黑匣子。他们可以通过模型的模拟运行,看看年损失表,切片和骰子不同的成本指标,甚至在单一公司级别看损失。所以我认为那个开放性和透明度,也有时谦卑地说模特可以和可以'要做或它的局限性是非常非常重要的。有时候,我发现人们如何自信地谈论他们理解和塑造这种风险的能力之间的反向相关性,以及他们对它的理解。因为这是非常困难的,它非常快速,而且它'我们真正与客户合作的人,了解如何充分利用我们的大部分工具've created.

19:11 MG: Yes, that makes a lot of sense, certainly in my experience of working with people who are buying the tools, I guess, they often can build models, have built models, and one of the most important things for them is a understanding of the assumptions and awareness, as opposed to somebody having over-confidence, which just scares anybody who knows how to build these things. One of the themes we'再次听到很多关于人工智能,并且实际上完全远离承销的潜力,基于你的算法是正确的。你是否看到了一个时间,或者甚至这就是你今天的地方,你提供工具,你've got the work that's gone into building these in a way that helps the client, so do you see the opportunity moving more and more to that kind of ‘detached’ use of tools, and underwriting no longer needs an underwriter, and as CyberCube gets better, help people just push the button and the results will come out?

20:15 PM: So I think about artificial intelligence a little bit differently than many of my Silicon Valley peers. And I think there are a lot of misnomers around artificial intelligence, including when I hear people talking about it, I hear people having implicit assumptions that artificial intelligence is about using really expensive computers to solve really hard problems that are simply too complicated for the smartest human beings on the planet, when the reality is actually often the opposite. Artificial intelligence exists and is being deployed today, not because, or not with very expensive computers, but because computing power is cheap and abundant. It'不是最好的总是用非常困难的问题部署。它'S实际上非常适合非常容易存在的问题,并不总是最复杂的,但经常对人类来说太单调的问题真的很烦扰。事实上,人工智能的一些最佳应用aren'解决世界的问题's smartest human can't solve, but rather solving problems that a fifth-grader might be able to solve, if you had armies of fifth graders. And therefore those are some of the best-use cases for artificial intelligence.

21:55 PM: And it'对我来说很好奇'最近一个术语变得非常时尚。但如果你回到赛门铁克的历史,只需使用一个例子。赛门铁克成立于20世纪80年代,在财富500强企业中,它在硅谷的某些恐龙,但其实际上是在斯坦福人工智能研究所建立。人们谈论机器学习,1983年,赛门铁克从赛门铁克境内的机器智能公司旋转。实际上,人工智能是一个术语'已经过了很长一段时间了,最​​近恰好恰好变得更加流行。所以,虽然在网络核库中,我们正在使用人工智能,这是解决一些非常有趣的问题。例如,我们're using AI to train our models to pair lost data and claims data on the one side, to very, very large security datasets on the other, and have some wonderful data scientists doing that, developing world-class models. But actually a lot of the applications of AI within CyberCube end up being for very, very simple problems for which computers are actually a better way to solve very easy problems of scale.

23:39 PM: So to give you an example, our Enterprise Intelligence Layer, (I was about to say EIL but that would have been my second acronym so I avoided that one) is used by insurers, and it might have 10,000 cyber-insurance policies maybe 30,000 or 50,000 cyber-insurance policies. And they want to match the companies that they'将网络保险销售给一些相对基本的数据,在那里'重新尝试使用该行业的SIC4代码增强数据。然后'实际上是一个相对基本的问题要做,即使是谷歌搜索,还是一个'实际上是一个非常良好的应用程序,有些可能称呼人工智能,或者一个我'll also just talk about, modern computing techniques.

24:35 PM: So to come back to your original question though, so what does this mean for an underwriter? What does this mean for a cat modeller? Are they going to be replaced in the future? I think absolutely not. I think what'如果发生的是,那些角色的大量单调将会自动化。他们'重新有更好的工具。所以实际上是猫谟制动者或作为承销商成为一个更有趣的职业,当你的工具're using really allow you to do a lot more and engage your brain in really difficult and interesting problem-solving and teasing out the ‘so-whats’.

25:20 MG: So that'对任何人听力的人都有巨大的信心,谁是一个莫德勒或承销商,那么肯定是Cyber​​ Cobe赢了'T将它们从他们的角色移位,即时。也许那个'S也是,Pascal,部分原因在您的客户方面,您'在过去的12个月里,在过去的12个月内,在过去的一些人方面迅速增长've signed up. It would be interesting just to hear a couple of stories really about why, for example, a big organisation like Munich Re, they make decisions very carefully, often very slowly, have chosen to embrace CyberCube? And also, are you seeing companies going down the multi-model route? Or are they deciding quite carefully who to go with in this area, and then essentially being a single model operator?

26:09 PM: So it'我可能是一个陈词滥调的人在我的立场来说,但我们当然不仅想卖给我们的客户,他们是世界之一'最大,最先进的保险和再保险机构,其中一些人对我们谈论了,我们'重新讨人喜欢。但是我们真的已经完成了,我认为,与客户合作的伟大工作。我们 '从组织的最高级别,从最高级别的级别来看,这是一个越来越多的入门级别的承诺者。这样'从C级别,在CUO,CRO水平上,真正帮助他们与他们最具战略性的主题之一。让我们像一个人一样'实际上将于6月份在伦敦在伦敦进行,与UC BERKELEY为世界经济论坛开展的工作,以真正挑剔网络 - ESQUE,全球网络保险的影响,我们'与他们在世界上一些世界的大代表团合作's largest cyber insurers and reinsurers at the RSA Conference last week, all the way down to frontline users that were putting on webinars, user events and training.

27:37 PM: So we'如果他们使用一个型号或多种模型,就真的与客户合作,如果他们拥有自己的内部能力和自己的内部模型,或者他们'修复自己的内部模型,在与我们的产品平台上提供大量价值。而且,也可以通过所有方式与这些客户合作,并尽可能地支持它们来向他们提供价值。是的,在多模型问题上,我觉得它's important that insurers build up their own capabilities internally.

28:21 MG: Well, congratulations, Pascal, because like I said, you came out of stealth last year and are making some really strong headway. Just changing tack a little bit, but just as you look at what'S让你成功,看看那里的其他公司正在成长,你对别人有什么建议's starting up a business and trying to grapple with some of these issues, both about how to engage with clients and also how to actually recruit and build business themselves?

28:50 PM: Well, recruiting is the single most important thing that we do. And once people arrive at CyberCube, as a leadership team, we'致力于创造一个吸引,保留,兴奋的环境,使他们能够做出他们的最佳工作,我意识到这是一个非常崇高的目标,但我们持有自己的巨大目标。在这个空间对我们在Cyber​​ Cube的挑战,是为了解决我们的问题'重新尝试解决,我们需要有精算背景,网络安全背景,软件工程背景,数据科学,商业保险,我们拥有多个网络经济学家和人民,以良好,基本的问题解决技巧。然后'非常非常非常难以在所有这些域中获得最佳和最聪明的人。但我想我们've done a really good job of creating a culture at CyberCube that allows those domains to work well together.

下午29:58:所以,建议我将永远招募。说到哪个, info@cybcube.com., C-Y-B-C-U-B-E.com, see if can you edit this out at the end as a promotional plug, but we are always looking for new talent, for people that have a passion for solving some of the hardest problems in insurance, and people that can work in a cross-disciplinary way. And I think my biggest advice is really to pay an inordinate amount of attention to your people proposition and the culture that you'创造。因为最终,如果你有一个强大,高运行的团队'经过一个艰难的问题,这'魔法发生在哪里's why it's one of the most important things that we do.

30:51 MG: Great. Pascal, it'S巨大的赶上你,不,我们不会编辑你的招聘电子邮件地址。你'Ve是科技前沿的一个大支持者'我们最不可能。我们'LL实际上甚至把它放在节目的音符中。它非常感谢你 's been great to catch up. Thank you again for your team support at InsTech London, we had Ollie talking there last year. And we have to see you there or certainly get more of a team there again. But thank you, and safe travels back home to California.

31:20 PM: Wonderful. Well look, it'太棒了在伦敦的芦苇社区的一部分。我认为使硅谷特别的事情之一是存在使其他公司成功的不同公司的生态系统。我认为让伦敦真正特别作为芦苇枢纽的事情之一以及为什么我们'在伦敦投资的是生态系统。而且我认为instech正在成为该生态系统的核心部分,所以它's an absolute pleasure to be a part of it.

31:53 MG:好,非常感谢你。