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patrickc's profile
Patrick Collison
Patrick Collison
Patrick Collison
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@patrickc

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Patrick CollisonVerified account

@patrickc

Fallibilist, optimist. Stripe CEO.

patrick@stripe.com
patrickcollison.com
Joined April 2007

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    Patrick Collison‏Verified account @patrickc 28 Oct 2019
    • Report Tweet
    • Report NetzDG Violation

    We've been building an ML engine to automatically optimize the bitfields of card network requests. (Stripe-wide N is now large enough to yield statistical significance even in unusual cases.) It will soon have generated an incremental $1 billion of revenue for @stripe businesses.

    11:48 AM - 28 Oct 2019
    • 122 Retweets
    • 1,651 Likes
    • justinhj suneet Josh Barbour steven wong Tyler Tarsi John McDonnell fu Joshua Tabakhoff Andrew Chami
    29 replies 122 retweets 1,651 likes
      1. Patrick Collison‏Verified account @patrickc 28 Oct 2019
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        We love this kind of work: putting a team of experts on an arbitrarily arcane and specific problem… and creating platform benefits that make millions of businesses better off.

        5 replies 8 retweets 379 likes
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      2. Steven Schmatz‏ @StevenSchmatz 28 Oct 2019
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        Replying to @patrickc @stripe

        Hiring ML engineers?

        1 reply 0 retweets 10 likes
      3. Patrick Collison‏Verified account @patrickc 28 Oct 2019
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        Replying to @StevenSchmatz @stripe

        Most definitely!

        1 reply 0 retweets 27 likes
      4. 1 more reply
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      2. Ryan Petersen‏Verified account @typesfast 28 Oct 2019
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        Replying to @patrickc @stripe

        Nobody can understand what you’re talking about but $1B in incremental revenue for your customers is awesome, so nice job!

        5 replies 5 retweets 438 likes
      3. Matt Dyor‏ @mattdyor 28 Oct 2019
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        Replying to @typesfast @patrickc @stripe

        I had to watch the video, but it sounds like the banks that end up settling the payment have undocumented and maybe unknown requirements for incoming messages, so stripe constantly experiments to see which message format is most likely to avoid arbitrary rejection. Pretty cool.

        4 replies 1 retweet 68 likes
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      2. Hristo Vassilev‏ @hristo_vassilev 28 Oct 2019
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        Replying to @patrickc @stripe

        Team Stripe, can you explain in lay terms what Patrick means here, please? I assume this somehow lowers transaction costs?

        2 replies 0 retweets 7 likes
      3. ¯\_(ツ)_/¯‏ @adropboxspace 28 Oct 2019
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        Replying to @hristo_vassilev @patrickc @stripe

        when you put in your CC info into Stripe, Stripe takes the info, sends the data to the bank that will actually release the money. Each bank has its own unique dumb way of accepting the info, sometimes errors in this cause banks to reject legit transactions.

        2 replies 2 retweets 76 likes
      4. 1 more reply
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      2. Steffen Bunzel‏ @stbunzel 28 Oct 2019
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        Replying to @patrickc @stripe

        For those of us wanting to learn more - this seems related:https://youtu.be/upQiW3IUFAg 

        1 reply 4 retweets 134 likes
      3. Apercus Tosh‏ @ApercusTosh 28 Oct 2019
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        Replying to @stbunzel @patrickc @stripe

        Thank you, for posting the link to Stripe Session 2019: Tackling the conversion challenge with ML.

        1 reply 0 retweets 5 likes
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      2. Scott Buchanan‏ @thescottsb 28 Oct 2019
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        Replying to @patrickc @stripe

        How does optimizing bitfields increase revenue? Unless I'm wildly misunderstanding (very possible), it sounds like something that would decrease expenses and possibly therefore increase profit, but not revenue?

        2 replies 0 retweets 5 likes
      3. Feifan Zhou‏ @FeifanZ 28 Oct 2019
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        Replying to @thescottsb @patrickc @stripe

        I *think* the result is a marginal improvement in auth rates, which means more transactions go through that might not have otherwise. For marginal customers who wouldn't have retried their purchase, this captures that otherwise-lost revenue. Related:https://youtu.be/upQiW3IUFAg 

        2 replies 1 retweet 47 likes
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