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mlm

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Wed, Apr 17, 2013, 8:58 PM UTC
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21 items

About mlm

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Recent public activity

  1. comment
    Comment #22755167

    Notion | Software Engineers (Full stack, Backend/Infra, Mobile; all experience levels) | San Francisco, CA | Onsite Notion's goal is to create the general purpose work tool for a p…

  2. comment
    Comment #22550385

    This looks great, but it's also focused on people—what happens when more and more support is done via AI?

  3. comment
    Comment #16873470

    I’m sorry that you had this experience. We vehemently agree that any one signal (such as IP address or use of a proxy) is a pretty poor predictor of fraud in isolation. We are tryi…

  4. comment
    Comment #16871826

    In short, no. A little more color: Stripe’s incentives are aligned with those of our users in that we want to let through as many legitimate customers as possible. We keep a very c…

  5. comment
    Comment #16871730

    We’ve been working on Radar, and releasing updates and improvements, continuously since we first launched. What we’re announcing today is (1) a completely revamped machine learning…

  6. comment
    Comment #16870477

    The rough idea is that you look at all the decisions made by the fraud model (sample 1 is fraud, sample 2 is not fraud) and the world of possible "predicates" ("feature 1 > x1", "f…

  7. comment
    Comment #16870402

    We're working on it!

  8. comment
    Comment #16870244

    We’re really sorry that you ran into this. There are a couple things we can help you with: - We give users the ability to disable the default rules and mark transactions as safe if…

  9. comment
    Comment #16870117

    For any fraud detection scheme (or any binary classification scheme, really) there’s a tradeoff between false positives and false negatives. The Radar 2.0 updates—particularly Rada…

  10. comment
    Comment #16869948

    I agree that the lack of standards and baselines in the fraud detection space isn't ideal. One example: some fraud products will build models using human labels as the target to be…

  11. comment
    Comment #16869838

    Most of our ML stack has been developed internally given the unique constraints we have for Radar. Among other things, we need to be able to - compute a huge number of features, ma…

  12. comment
    Comment #16869308

    Engineering manager for Stripe Radar here. Today’s update has been almost a year in the making and we’re excited to help Stripe businesses fight fraud more effectively. Here's more…

  13. comment
    Comment #16869043

    Engineering manager for Stripe Radar here. Today’s update has been almost a year in the making and we’re excited to help Stripe businesses fight fraud more effectively. Here's more…

  14. comment
    Comment #13943526

    (I work at Stripe) We've thought about this a little, and while we'd be excited to make Radar available more broadly (i.e., even to businesses not using Stripe for payments), for n…

  15. comment
    Comment #10891254

    We've been thinking about (and working on) a lot of these issues--we're definitely aware that users would like (totally reasonably!) more visibility and control. If you have any mo…

  16. comment
    Comment #10890619

    (I work at Stripe.) For credit card processing, automated fraud prevention does in fact come standard on all Stripe accounts and takes into account a great number of signals includ…

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    Comment #8888567

    (I work at Stripe) Buyers won't have to contact Stripe directly, just as they would not contact a third-party fraud detection service directly. They'll contact businesses, who can …

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