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如何阻止欺诈信用卡/借记卡?

[英]How to block fraud credit / debit cards?

I'm not sure if this is the right place to ask this question not, Please do let me know where I can try.我不确定这是不是问这个问题的正确地方,请让我知道我可以在哪里尝试。

I'm having a real concern for blocking / disallow the usage of fraud transactions in our platform.我非常担心在我们的平台上阻止/禁止使用欺诈交易。

Some of customer uses some of fraud or stolen card to make payment in our platform and they keep doing it on daily basis.一些客户使用一些欺诈或被盗卡在我们的平台上付款,他们每天都在这样做。 Its not one or two cards.它不是一张或两张牌。 Its like many (say more than 50 a day).它像很多(比如说每天超过 50 个)。

As We are not payment company So We don't a license to store the card details in DB and block the card if same card is appears again.由于我们不是支付公司,所以我们没有将卡详细信息存储在数据库中的许可,如果再次出现同一张卡,我们将阻止该卡。

Weird thing is these customer's are able to pass 3D secure page protected by bank website, which ask for real user's OTP for that transaction.奇怪的是这些客户能够通过受银行网站保护的 3D 安全页面,该页面要求真实用户的 OTP 进行交易。

Update: Though I'm blocking customer's account and there android device Ids If found suspicious user.更新:虽然我阻止了客户的帐户,但如果发现可疑用户,则存在 android 设备 ID。

Is there any way I can reduce or stop these frauds?有什么办法可以减少或阻止这些欺诈行为?

For your issue, try to collect the data (be sure to ask the customers' permissions):对于您的问题,请尝试收集数据(请务必询问客户的权限):

  • credit card BIN (you can use it to find out the issuer bank and card country) credit card BIN (您可以使用它来查找issuer bank和发卡国)
  • IP subset and customer timezone (you can use it to find out is the customer use anonymizer like proxy, VPN, TOR) IP subsetcustomer timezone (您可以使用它来确定客户是否使用代理、VPN、TOR 等匿名器)
  • device fingerprint (mobile or browser) device fingerprint (手机或浏览器)
  • information about the used 3DS protocol and bank's operation result code (there are static - not dynamic - 3DS codes in some banks, or you can incorrect processing operation result code).使用的3DS协议和bank的操作结果代码信息(有static-非动态-部分bank中的3DS代码,或者您可以错误处理操作结果代码)。

After you gather these data you can apply the following approaches to fraud prevention:收集这些数据后,您可以应用以下方法来预防欺诈:

  1. Rule-based anti-fraud :基于规则的反欺诈
    • Black/white lists (countries, IP addresses, card BINs) Black/white lists (国家、IP 地址、卡 BIN)
    • Statistics-based approach (for example, if more than 3 accounts use the same credit card then ) Statistics-based方法(例如,如果超过 3 个账户使用同一张信用卡,则 )
  2. ML-based anti-fraud :基于机器学习的反欺诈
    • Fraud prediction using Supervised Machine Learning methods使用Supervised Machine Learning方法进行Fraud prediction
    • Anomaly detection using Unsupervised Machine Learning methods.使用Unsupervised Machine Learning方法进行Anomaly detection

And of course, you can use Anti-fraud as a Service (3rd party services) to solve your issue.当然,您可以使用反欺诈即服务(第三方服务)来解决您的问题。

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