Viewing profile — stephenlambe
stephenlambe
HN member- Joined
- Tue, Aug 14, 2012, 4:07 AM UTC
- HN karma
- 7
- Public activity
- 10 items
- HN profile
- View on Hacker News ↗
About stephenlambe
No profile information was provided.
Recent public activity
-
comment
Comment #6381720
This was discovered automatically. That's one benefit of a machine learning-based system: you feed it a lot of data and tell it when fraud actually occurred and it adapts its rules…
-
comment
Comment #6381697
Not quite...an order is more likely fraudulent when it was placed at 2-4am local time. Local time for the fraudster (in Vietnam or wherever else), not local time for the site they'…
-
comment
Comment #6377952
E-commerce fraud takes many forms. Three main types of fraud impact merchants: payment fraud, new account fraud and account takeover. We described all three recently at Sift in a b…
-
comment
Comment #6376813
Sift intern here. We use the time zone of the customer rather than of the website for scoring riskiness. Sorry if that wasn't clear. As for customers including birth years in their…
-
comment
Comment #6209495
it's per capita. Total fraudulent transactions/total transactions in each country.
-
comment
Comment #6208499
Sift Science intern here. We used the latter for the purposes of this map.
-
comment
Comment #6130831
These results are averaged across many different types of e-commerce companies. So you're correct that a particular company shouldn't necessarily set up a rule to flag transactions…
-
comment
Comment #4514864
Exactly what part of that website "portrays class and ethnic conflict"?
-
comment
Comment #4393114
They're only processing $10M of transactions/month, so even if they were to start charging fees, that wouldn't translate into much revenue. Agree that this is a great exit for the …
-
comment
Comment #4384263
turns out Su actually got the Seattle office a (waterless) hot tub http://seattletimes.nwsource.com/html/technologybrierdudleys...