Last active
December 22, 2015 08:18
-
-
Save andrewdunbar/6443528 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
If you think you're up to the challenge, we've created two case studies | |
to test your aptitude at detecting fraudulent activity in online orders. | |
Below are two shops with 5 orders each. Your challenge is to identify | |
fraudulent activity in the shops. | |
Feel free to use anything you can think of to gain insight into these | |
situations, including any free lookup tools you can find. | |
To help you out, we've signed up with our friends at Maxmind for a | |
minFraud account you can use in this exercise, which you can freely | |
use as you wade through these orders. The only caveat is you'll have | |
to use the API to make your determinations. | |
Please email us at payments-operations@shopify.com to obtain a Maxmind | |
licence key if you haven't already been provided one. | |
Documentation on the API can be found at: | |
http://dev.maxmind.com/minfraud/ | |
Use the data from Maxmind in addition to any other sources you like to determine the likelihood of fraud and provide a | |
descriptive reason as to why you think that. Also provide your impression of the merchant from an underwriting perspective. | |
First shop: | |
https://gist.github.com/andrewdunbar/6442457 | |
Second shop: | |
https://gist.github.com/andrewdunbar/6442067 | |
Please provide us with the source code of any tools you've written to | |
solve these problems, and name any sources which have provided useful | |
information. | |
please send your answers to payments-operations@shopify.com |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment