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走进谷歌风投“机器”

其他国际资讯

走进谷歌风投“机器”

大多数风险资本家希望获批进行新的投资时,会向合作伙伴寻求帮助。而谷歌风投(GV)的风险资本家想进行新投资的时候则会向"机器"(The Machine)求助。

公司(原名谷歌风投)多年来一直使用一种算法来有效评估新投资和后续投资,决定是否通过。

  1. "机器"利用各种市场数据进行编程,工作人员将各种交易细节输入"机器"中 ,就会得到类似交通信号的结果。 绿色表示通过,红色表示不通过,黄色表示需要谨慎行事,但消息人士表示,黄色的意思与红色相当。
  2. 最初设计和使用这一程序的初衷是为了完成尽职调查的辅助工作,结果也不是决定性的,但根据三个消息来源,"机器"已逐渐发展成为事实上的投资委员会。

背景:GV成立于2009年,是首批聘用技术工程师的风险投资公司之一,他们的主要工作是与投资组合公司合作,应对技术挑战。 但是早期并没有太多的投资组合公司,因此工程师们的首要工作是研发名为"Vortex"的交易流管理工具,然后研发"机器"。

  1. 另一个推动力是早期大多数GV投资者都没有投资经验。 因此,"机器"将利用公司的优势(工程学)防范其薄弱之处(已证实的风投经验)。
  2. 还要求工程师们开发"The Machine",使其具有帮助源交易的功能,但是结果不太理想。
  3. 2013年初现端倪,当时的GV首席执行官Bill Maris向《纽约时报》透露:"我们能够访问能想象到的世界上最大的数据集,我们拥有有史以来最大的云计算基础设施。不利用起来就盲目投资,这样的做法太不明智了。"
  4. Maris在那篇文章中没有明确提及的是色标编码系统,一方面是因为当时还没有完全编码化。

输入"机器"的信息包括投资周期、辛迪加合作伙伴、既有投资者、行业部门以及先前估值与当前估值之间的差异,然后算法会按10分制对交易进行排名, 8分或更高就会显示绿色。

在预测准确性方面,存在一些问题。 首先,据了解一些GV投资者尝试利用机器赌博,操纵输入以获得理想的结果。 其次,该软件的每个后续版本都可以改变现有投资组合公司的得分,使后续投资流程变得复杂。

  1. 但最大的问题可能是风投就像科学一样是一门艺术,直觉和深思熟虑同样重要。 但是,几位GV投资者表示,"机器"让他们变得胆小,放弃了可能获利丰厚的机会(特别是一些风险更高的机会,企业往往会从中获利颇丰)。
  2. 目前,GV并不是唯一一个使用算法完成尽职调查工具的公司。 据说欧洲的EQT Ventures使用名为Motherboard的工具,而深陷困境的Social Capital一直致力于尽可能消除人为因素。 但似乎都没像GV一样与软件紧密联系在一起,尽管第四个消息来源坚持表示,"机器"只是"向导","伙伴关系"拥有最终决定权。

GV拒绝对此发表评论。

When most venture capitalists want approval to make a new investment, they go to their partners. When venture capitalists at GV do it, they go to something called "The Machine."

What we're hearing: Axios has learned that the firm, formerly known as Google Ventures, for years has used an algorithm that effectively permits or prohibits both new and follow-on investments.

  1. Staffers plug in all sorts of deal details into "The Machine" — which is programmed with all sorts of market data, and returns traffic signal-like outputs. Green means go. Red means stop. Yellow means proceed with caution, but sources say it's usually the practical equivalent of red.
  2. It was initially designed and used as a due diligence assistant that could be overruled but, according to three sources, it has evolved into a de facto investment committee.

The backdrop: GV was formed in 2009 as one of the first venture firms to employ engineers whose primary job was to work with portfolio companies on technical challenges. But, in the early days, there weren't too many portfolio companies yet, so the engineers were tasked first with building a dealflow management tool dubbed "Vortex," and then with what would become "The Machine."

  1. Another impetus was that few of the early GV investors had much, if any, investing experience. So "The Machine" would leverage the firm's strengths (engineering) as a bulwark against its weakness (proven VC chops).
  2. The engineers were also asked to have "The Machine" help source deal opportunities, but that wasn't viewed as a terribly successful effort.
  3. The first hints of this came in 2013, when then-GV CEO Bill Maris told the NY Times: "We have access to the world's largest data sets you can imagine, our cloud computing infrastructure is the biggest ever. It would be foolish to just go out and make gut investments."
  4. What Maris didn't say in that piece, in part because it wasn't quite so codified yet, was the color-coding system that virtually took "gut" out of it entirely.

Inputs into "The Machine" include round size, syndicate partners, past investors, industry sector and the delta between prior valuation and current valuation. The algorithm then ranks deals on a 10-point scale, with green said to represent 8 or above.

There have been some pretty predictable problems. The first is that some GV investors have been known to try gaming the machine, manipulating inputs to get the desired results. Second, each subsequent version of the software can change the score of existing portfolio companies, which complicates follow-on investment processes.

  1. But the biggest may be that venture capital is as much art as science, intuition as calculation. But several GV investors tell me that "The Machine" has ripped out their guts, possibly costing them lucrative opportunities (particularly some of the more risky bets that often turn into venture's biggest wins).
  2. At this point, GV is not alone in using algorithms as a due diligence tool. EQT Ventures in Europe is said to have something it called Motherboard, while beleaguered Social Capital has been on a mission to largely remove the human element. But none seem as tied to the software as GV, even though a fourth source insists that it's "just a guide" and that "the partnership" still has final say.

GV declined comment for this story.


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