I’m building a mobile checkout feature where users can add their bank card by scanning it instead of typing everything manually. In testing it works fine, but in real usage it becomes inconsistent very quickly—glare, motion blur, different phone cameras, and slightly damaged cards all affect results. I’m trying to understand if this is just a limitation of standard OCR or if AI-based solutions handle it significantly better in production. I also found an example of a bank card scaner SDK that looks focused on structured recognition rather than just text extraction: https://ocrstudio.ai/bank-card-scanner/. Has anyone actually used something like this in a real app and can share how stable it is under real-world conditions?
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A guy I know was trying to improve his credit score after spending years avoiding credit cards completely. He finally decided to open a small account and started paying attention to every transaction because he didn’t want any mistakes affecting his score again. Everything was going smoothly until he noticed a charge he didn’t recognize and couldn’t immediately explain. He spent most of the evening checking statements and eventually started reading through https://credit-one-bank.pissedconsumer.com/customer-service.html to see how other customers handled disputes, billing questions, and account problems.