通过传播数据科学来改进欺诈检测
公司规模
Large Corporate
地区
- Europe
国家
- Luxembourg
产品
- Dataiku Data Science Studio (DSS)
技术栈
- Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Digital Expertise
技术
- 分析与建模 - 机器学习
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 欺诈识别
服务
- 数据科学服务
关于客户
BGL BNP Paribas 是卢森堡最大的银行之一，隶属于法国巴黎银行集团。该银行为个人、专业人士、私人银行客户和企业提供种类繁多的金融产品和银保解决方案。2017 年，国际杂志《欧洲货币》连续第二年将 BGL BNP Paribas 评为“卢森堡最佳银行”。该银行已在使用机器学习模型进行高级欺诈检测，但由于可见性和数据科学资源有限，该模型基本处于静态状态。
挑战
BGL BNP Paribas 是卢森堡最大的银行之一，它已建立了一个机器学习模型，用于高级欺诈检测。然而，由于可见性有限和数据科学资源有限，该模型基本保持静态。业务团队热衷于更新模型，但由于缺乏对数据项目和数据团队的访问权限，因此面临挑战。挑战在于在整个组织的所有部门中采用数据驱动的方法。银行需要一种解决方案，既能使整个公司的数据访问和使用民主化，又不会损害数据治理标准。
解决方案
BGL BNP Paribas 选择 Dataiku 数据科学工作室 (DSS) 来实现整个公司的数据访问和使用民主化。在短短八周内，BGL BNP Paribas 就能够使用 Dataiku 创建一个新的欺诈检测原型。该项目涉及欺诈部门的数据分析和业务用户以及 BGL BNP Paribas 数据实验室和 Dataiku 的数据科学家。Dataiku 的协作性质以及整个公司团队的参与使得知识得以最佳组合，从而产生了具有明确商业价值的准确模型。Dataiku 的生产功能使 BGL BNP Paribas 的生产环境能够顺利过渡，使新的欺诈预测项目能够在项目启动后很快显示结果。
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