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atec_season_two's Introduction

蚂蚁金服风险支付

赛题介绍

赛题介绍

赛题需要根据用户的支付环境判断用户当前的支付是否存在风险。其中数据主要有支付时间、地点、金额、场景、方式、支付方的网络、设备、收入方的省份、城市、证件、手机、银行代码等等。

特征工程

直接特征:

事件是发生在节假日,深夜等,支付金额,是否代付,版本号

简单特征:

用户IP、网络类型、设备、省、操作平台的使用频率,用户支付方式、场景、金额的频率。

用户10天内、5天内、1天内的平均交易次数,交易金额,用户历史交易次数、金额,这笔交易发生的时间段(工作时间、饭点、凌晨)

收款方的省份、操作类型、手机号码、信用卡是否为空

复杂特征:

用户在这个IP下使用这个网络类型的概率

用户在这个身份、城市下使用这个设备类型的概率

用户在这个支付方式、场景下下支付这个金额的概率

模型

使用LR和GBDT模型,GBDT模型好多了

赛题难点

比赛需要运行在蚂蚁金服上的数巢平台,所有的特征需要用sql生成

数巢平台的模型有限,组件化的工具不太好用

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