亚马逊AWS日前宣布推出适用于 Amazon Fraud Detector机器学习(ML)模型的电话号码扩充功能。Amazon Fraud Detector(AFD)是一项完全托管式服务,可轻松识别潜在的欺诈性线上活动,以加强安全保护。
通过在幕后使用机器学习(ML),并依托 Amazon 20 多年的欺诈侦测专业知识,Amazon Fraud Detector 可在几毫秒内自动识别潜在的欺诈活动,而无需要机器学习(ML)专业知识。
作为模型训练过程的一部分,Amazon Fraud Detector 使用 IP 地址的地理位置或信用卡的发卡行等数据来丰富原始数据元素,例如支付工具的 IP 地址和银行标识(BIN)编号。使用此类扩充功能来增强用户数据可确保 AFD 模型具有一流的性能。
自即日起,Amazon Fraud Detector 现在可通过地理定位和原始运营商等附加信息来丰富电话号码数据。这一全新的数据扩充功能提高了使用电话号码的模型的性能,使这些模型能够以 4% 的误报率捕获多达 16% 的欺诈行为。
在AFD的所有可用区域,自动为AFD的线上欺诈洞察(OFI)和交易欺诈洞察(TFI)模型启用电话号码扩充。AFD客户可以通过重新训练使用电话号码作为事件变量之一的AFD模型来利用这一全新的数据扩充功能。
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