智策-腾讯云联邦共建评分产品

融合银联跨行清算与腾讯网络黑产安全数据，应用联邦学习平台联合建模，多维度构建贷前风险评分。采用联邦学习技术，在保障数据安全、保证合法合规的前提下，在多参与方或多计算结点之间开展机器学习，具有成本低、效率高、迭代快等优点，解决数据孤岛和数据隐私问题，释放大数据能力。

This dataset integrates UnionPay cross-bank settlement data and Tencent's cyber black industry security data, and adopts federated learning platforms to conduct joint modeling for building multi-dimensional pre-loan risk scoring models. Leveraging federated learning technology, machine learning is carried out among multiple participants or computing nodes under the premise of ensuring data security and legal compliance. This approach boasts advantages including low cost, high efficiency and rapid iteration, addressing the issues of data silos and data privacy while unleashing the potential of big data.

搜集汇总

背景与挑战

背景概述

该数据集通过联邦学习技术整合银联清算与腾讯安全数据，构建多维度贷前风险评估模型，在确保数据隐私的前提下实现高效合规的联合建模。