Fraud is an incredibly difficult problem for payment processors, for both technical and business reasons.
Fraud is an incredibly difficult problem for payment processors, for both technical and business reasons. It's well worth studying if you're into this sort of thing. Fraud is a sensitivity/specificity problem. For sensitivity, Stripe wants to detect as many actual fraud cases as possible, because undetected fraud is expensive. For specificity, they want as few false positives as possible, because false positives mean angry customers who feel mistreated. Generally, there's a sensitivity/specificity tradeoff, and priorities need to be set (which is worse - letting criminals get away, or frustrating honest customers?). But at such a scale, and with so many creative minds working on new mechanisms for fraud, it's impossible to achieve perfect numbers on either side.
Posted by beat on Jun 18, 2015, 4:33 PM
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Raise real-world problems, find people facing the same issue, and discuss solutions.6,000 issues0 comments
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While I hate that it's like this, you're leaving money on the table.
The biggest problem with micropayments is how credit card payment processors work.
I think with the advent of cheap Chinese electric cars (new BYD for 7-9k€ in China) VW will die a slow death, slowed down by tariffs, tax...
The German bank I have an account with solves this by making the statements available online and considering them delivered if the statem...
Feature Request: India-Specific Pricing Plans (INR) for Claude & Claude Code
Think about cabinet from 1972 for one electricity meter.
You're right, but until the laws change we should be telling everyone how and make these tools better.
I worked in this industry as a software developer.
Fraud is an incredibly difficult problem for payment processors, for both technical and business reasons.
Fraud is an incredibly difficult problem for payment processors, for both technical and business reasons. It's well worth studying if you're into this sort of thing. Fraud is a sensitivity/specificity problem. For sensitivity, Stripe wants to detect as many actual fraud cases as possible, because undetected fraud is expensive. For specificity, they want as few false positives as possible, because false positives mean angry customers who feel mistreated. Generally, there's a sensitivity/specificity tradeoff, and priorities need to be set (which is worse - letting criminals get away, or frustrating honest customers?). But at such a scale, and with so many creative minds working on new mechanisms for fraud, it's impossible to achieve perfect numbers on either side.
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