julia-zheng

Exactly - the effort required for this much beyond what most fraudsters would be willing to do on most platforms.

Interesting - would love to get more context if it's possible to share

Interesting - we're currently only detect credit card fraud for the segment of customers transacting with more typical credit cards (the largest chunk of the market) but this is good to know.

So actually acquiring stolen cc numbers is very easy - there's a bunch of marketplaces that sell thousands of them. Figuring out a scalable way to extract value out of them, however, is hard. More than visible or invisible barriers, what makes a fraudster want to spend time getting around the defenses of a specific business is the value of the offering (e.g., banks vs an app that sells a service)

Hahahaha they're all cancelled or expired cards :)

Amazing - thanks for all the feedback. This is definitely on the roadmap - stay tuned!!

Currently it's only available on iOS and Android apps, with mobile web coming soon. We're still working out exactly what the experience will look like on desktop (it's a less natural flow for sure), but once we work out the kinks we'll be building that out as well.

Hope it helps - good luck!!!

For the most part the model should generalize pretty well to new formats, but we do constantly monitor and update to catch up with any holes.

Thanks!

Cool!! Until we have enough transaction volume, we are replicating methods fraudsters use to create fake cards to train our models.

Thanks!

Great question! The company that owns the app is ultimately responsible for the encryption there, but there are a few ways we can help out with that as well (sorry, I know this is a terrible answer - but it's best practice not to reveal too much about how the encryption works)

Definitely take the below with a grain of salt - this worked for me thus far but there are probably paths other people have taken that worked equally well or better :) My recommendation would be: 1) A smaller/less established team where you'll be responsible for building out key chunks of the team 2) A team where you can build expertise in a domain you find interesting, and where you think there might be more problems than solutions

The benefit of working on a smaller/less established team is getting the autonomy to build something that's immediately impactful to the company and its customers, while not having to worry too about how to stay alive (fundraising, revenue, resources) - I think that's pretty good training for building a startup.

Picking a team where you'll get expertise in a newer/growing field can be helpful too - think something where you'll only need a few years to become an expert and start adding value. Also be sure to pick something you like, since if you do start a company in that field, you'll likely be spending a big chunk of your life on it.

Thank you!

The photos of cards aren't stored anywhere - everything is analyzed on device to ensure privacy and compliance.

Re privacy policy - thanks, gotta put that up!

Thanks! Just sent you an email :)

Great question! The small proportion of cards that can't be scanned can be pushed through a higher friction fraud prevention flow. Since card scanning is low friction, this allows you to catch a ton of fraud at minimal impact to good users, and subject only a very small number to the higher friction flow.

Thanks for sharing that - super helpful to know.

Definitely agree it's possible to make good fake cards, but it makes it difficult enough that fraudsters will usually migrate to a different platform. Since banks are probably the most attractive business to fraudsters, we'd suspect banks would have to make life much more difficult for fraudsters than the average business in order to chase them away.

Whoa you know a lot about Card.io!

Apple does have great card scanner. Our thoughts on this (would love to hear yours) are they have little incentive to open up the card scanning tech standalone for developers, but even assuming they did, the standalone Apple scanner wouldn't include any fraud prevention features.

Longer term, we plan to leverage data from our customer base to make our fraud prevention features very robust - and we suspect this would be difficult for a competitor to replicate.

A stripe integration out of the gate would be REALLY nice :)

Thanks so much for the feedback! Just put it on my to-dos

There's a number of ways that a fake card will look different from a real card - we aggregate these signals and form a decision on real vs fake (sorry, we know that's a terrible answer - we would disclose more, but it's best practice to keep specifics of fraud detection a secret to maintain efficacy). Surprisingly, the gap between real and fake is wide enough that we can with good precision separate those cases. Of course, someone could build a replica indistinguishable from a real card, but at that point you've raise the barrier of committing fraud much higher than simply having a stolen credit card number, so chances are the fraudsters would migrate to some other platform