畅数通反诈画像模型评分

基于隐私计算、联邦学习等技术，为银行客户提供反诈风险识别和决策支持等应用场景下的用户画像分析和联合建模服务。通过隐私计算平台节点部署和调用，对接多数据源融合建模。同时提供用户标签自定义、数据动态更新、算法联合建模等服务。

Based on technologies including privacy computing and federated learning, this dataset provides user portrait analysis and joint modeling services for banking customers in application scenarios such as anti-fraud risk identification and decision support. It supports integrated modeling across multiple data sources through the deployment and invocation of privacy computing platform nodes. Additionally, it offers services including custom user tagging, dynamic data update, and algorithm-based joint modeling.

搜集汇总

背景与挑战

背景概述

该数据集是一个专注于反欺诈领域的模型评分服务，基于隐私计算和联邦学习技术，为银行客户提供用户画像分析和联合建模支持，以识别诈骗风险并辅助决策。数据集覆盖全国范围的通信数据，每日动态更新，存储容量达7 TB，包含10个底层数据维度，适用于反诈风险识别和决策支持等应用场景。