Engineering manager for Stripe Radar here. Today’s update has been almost a year in the making and we’re excited to help Stripe businesses fight fraud more effectively. Here's more on what's new: https://stripe.com/blog/radar-2018 I (and the entire Radar team) are on hand to answer any questions you may have!
A problem we've run into with Radar is that it only kicks in when you attempt to create a charge, and not when you attach a card to a customer. This means that if your business model involves "try before you buy" or usage-based billing, you'd better be sure to make an initial charge, otherwise the customer might incur costs before Radar decides to block the charges. Even if you do require an initial charge, if you al…
In software sold on a free-trial model, you assume most trials don’t convert (overwhelmingly due to declining to pay but with a bit of fraud) and then the cost to provision the service (COGS) is, effectively, a marketing expense. COGS in SaaS are typically negligible to low; this is why the industry is OK with providing services on, basically, a digital handshake. If you want to allow users to try out high-COGS services (or highly-abused services) prior to verifying capacity/willingness to pay, you’d need some way to credit score potential customers outside the context of a particular payment.
To date, we’ve generally focused the bulk of our ML efforts on things which apply to the majority of our users, but as we get better at customizing these technologies to specific industries at scale and even on a per-account basis, we could certainly imagine applying them in contexts that are more relevant in your model. I’d love to hear more detail about your use case; feel free to email me (my HN username at stripe.com). If we get closer to shipping something that is probably interesting, we’d be happy to give you a heads up.