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I was at a loss for why Sift was collecting data like this from companies like airbnb / etc, I worked a project using them around curbing some pretty gnarly lev

I was at a loss for why Sift was collecting data like this from companies like airbnb / etc, I worked a project using them around curbing some pretty gnarly levels of credit card fraud. I think it must be that these companies are utilizing their user content fraud scanning (“content integrity”) systems. I don’t know about calling this a consumer score though, but it is truly frightening if that’s how companies are utilizing that technology. I really enjoyed working with them — so I might be biased to see the good here — but they totally pushed back on biz folks on our side when they tried to nudge on things that the technology was not designed to do. So I would imagine / hope that they would have done the same in the case of something like constructing a “consumer score”, the tech is for flagging outright fraud, not for relatively scoring how good a customer is...

maxerickson 7y ago
A binary score is still a score.
- maxerickson 7y ago
  Seriously. If companies are relying on the fraud estimates, it isn't going to be fun to be a false positive.
  - awinder 7y ago
    I mean people have been subjected to fraud scoring for decades, you get declined, you follow up, and you get in w/ a new data point for the next time.
    - stedaniels 7y ago
      Not when these new automated systems don't allow for a follow-up because it would be too expensive to code or hire a human to do it.
      - awinder 7y ago
        How many companies don't have a support@____ email address? Seriously, they'll figure it out, it's really not that large of a haul to get stuff corrected, and it's the difference between "we can't take credit card payments" and "a very low-percentage of real users have some extra friction / bounce somewhere else".
    - maxerickson 7y ago
      Right, it's not a score, it's just a thing you have to argue with them to change. Not a score though.
    - CPLX 7y ago
      They've been subject to fraud scoring across a large group of disparate companies for decades? I would say that's absolutely not true at all. And to the extent that it is true, via credit reporting agencies, it's extremely aggressively regulated to allow consumers to see and challenge how that data is used, as well as to completely opt out of that system.
      - awinder 7y ago
        Credit card companies use your past history across merchants in risk scoring transactions, yes, and they also pull in data from external sources that are outside of their walls to further enrich that data. Anyways -- this is all massively orthogonal to what I originally wrote, which was around Sift being used as a consumer scoring system. I shouldn't have "taken the bait" so that's my bad.
- ineedasername 7y ago
  There's absolutely a difference between a binary "fraud/not fraud" flag and a continuous variable for quality of customer. They measure different things and have very different use cases.
  - CPLX 7y ago
    Is there a perceptible difference to a consumer who has been flagged as "fraud" when they are not, in fact, someone who has committed fraud? If not, then there's no difference.
    - ineedasername 7y ago
      They are literally two very different types of data. This isn't an ambiguous issue: One is a continuous variable, the other categorical. Whether or not one or the other could erroneously flag someone doesn't change that, and doesn't mean they're the same. Because the nature of those differences means the use cases are different. A continuous score has much wider versatility than a black & white binary value, and allows for more nuanced use. Even if it's just in the realm of fraud detection, a continuous score allows for more safeguards, e.g., if it's low but not too low then it triggers further review rather than outright rejection.
      - maxerickson 7y ago
        Categorization into groups that you will or will not do business with is scoring. Pedantically explaining what sort of scoring it is doesn't change that.
        ineedasername 7y ago
        Except that sort of will/won't is the only possible result of binary variables, while continuous allow more possibilities, like assigning a continuous variable interest rate on the basis of a continuous input. I wasn't explaining some basic aspect of statistical variables for it's own sake, in this context it is not some pedantic hair splitting, it's a relevant aspect of the types of things that can be done with this data.

maxerickson 7y ago

A binary score is still a score.

maxerickson 7y ago
Seriously. If companies are relying on the fraud estimates, it isn't going to be fun to be a false positive.
- awinder 7y ago
  I mean people have been subjected to fraud scoring for decades, you get declined, you follow up, and you get in w/ a new data point for the next time.
  - stedaniels 7y ago
    Not when these new automated systems don't allow for a follow-up because it would be too expensive to code or hire a human to do it.
    - awinder 7y ago
      How many companies don't have a support@____ email address? Seriously, they'll figure it out, it's really not that large of a haul to get stuff corrected, and it's the difference between "we can't take credit card payments" and "a very low-percentage of real users have some extra friction / bounce somewhere else".
  - maxerickson 7y ago
    Right, it's not a score, it's just a thing you have to argue with them to change. Not a score though.
  - CPLX 7y ago
    They've been subject to fraud scoring across a large group of disparate companies for decades? I would say that's absolutely not true at all. And to the extent that it is true, via credit reporting agencies, it's extremely aggressively regulated to allow consumers to see and challenge how that data is used, as well as to completely opt out of that system.
    - awinder 7y ago
      Credit card companies use your past history across merchants in risk scoring transactions, yes, and they also pull in data from external sources that are outside of their walls to further enrich that data. Anyways -- this is all massively orthogonal to what I originally wrote, which was around Sift being used as a consumer scoring system. I shouldn't have "taken the bait" so that's my bad.
ineedasername 7y ago
There's absolutely a difference between a binary "fraud/not fraud" flag and a continuous variable for quality of customer. They measure different things and have very different use cases.
- CPLX 7y ago
  Is there a perceptible difference to a consumer who has been flagged as "fraud" when they are not, in fact, someone who has committed fraud? If not, then there's no difference.
  - ineedasername 7y ago
    They are literally two very different types of data. This isn't an ambiguous issue: One is a continuous variable, the other categorical. Whether or not one or the other could erroneously flag someone doesn't change that, and doesn't mean they're the same. Because the nature of those differences means the use cases are different. A continuous score has much wider versatility than a black & white binary value, and allows for more nuanced use. Even if it's just in the realm of fraud detection, a continuous score allows for more safeguards, e.g., if it's low but not too low then it triggers further review rather than outright rejection.
    - maxerickson 7y ago
      Categorization into groups that you will or will not do business with is scoring. Pedantically explaining what sort of scoring it is doesn't change that.
      - ineedasername 7y ago
        Except that sort of will/won't is the only possible result of binary variables, while continuous allow more possibilities, like assigning a continuous variable interest rate on the basis of a continuous input. I wasn't explaining some basic aspect of statistical variables for it's own sake, in this context it is not some pedantic hair splitting, it's a relevant aspect of the types of things that can be done with this data.