Technologies Used
JADEPython
Grunt
Angular
Sass
Feedzai api
Python Flask
About
We use multiple sources of data to validate every customer, such as SMS, Facebook, Apple Pay, etc. Bacon then takes this information to assign each customer a risk score, and give merchants suggestions on how to handle potentially risky transactions. Machine learning is good at identifying obvious cases of fraud, but it’s not good at dealing with the grey zone. Bacon combines the best of ML and human interaction for the most effective way to reduce fraud.
Comments
Peter Smith - 3066d
loved the admin panel. the middle column idea was super cool.
not sure merchants are a good market as they will lack the people to look at transactions. maybe banks.
Bruce Parker - 3066d
Loved the UI for the "middle of the road transactions". That's actually the real tough part of fraud. Banks are probably a better market than merchants. Nice. Lots of work for implementers, though.
ryan smith - 3066d
2FA for credit card purchases? Yes please.
Matthew Ozvat - 3066d
I absolutely love the focus on 'risky' transactions.
Armando - 3066d
Good idea, impeccable execution! The way you guys attacked the problem from a platform perspective and how you always looked for feedback and to improve your project is a testament to your talent.
Your pitch and demo and the way you made it loop back to Feedzai was really well done. A lot of work was clearly involved in this - congrats!
Balaji Gopalan - 3066d