Valley Bank 将反洗钱误报率降低了 22%
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- DataRobot AI Cloud
- MLOps
- AutoML
技术栈
- Predictive Analytics
- Automated Modeling
- AI Lifecycle Optimization
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Cost Savings
技术
- 分析与建模 - 预测分析
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 欺诈识别
- 质量预测分析
服务
- 数据科学服务
- 云规划/设计/实施服务
关于客户
Valley National Bank 是 Valley National Bancorp 的主要子公司。这是一家资产规模约为 500 亿美元的地区性银行。该银行在新泽西州、纽约州、佛罗里达州、阿拉巴马州、加利福尼亚州和伊利诺伊州设有多家便利的分行和商业银行办事处。Valley 致力于提供最便捷的服务、最新的创新技术以及一支经验丰富、知识渊博的团队，致力于满足客户的需求。该银行还致力于帮助社区发展和繁荣，这是 Valley 企业公民理念的核心。
挑战
Valley Bank 是一家拥有约 500 亿美元资产的地区性银行，其反洗钱 (AML) 部门面临挑战。该银行在努力发现数百万笔交易中的洗钱活动时，遇到了大量误报。该银行的反洗钱团队正在寻求减少预测建模所涉及的手动工作。手动创建模型的过程非常耗时，需要数周才能完成。该银行正在寻找一种可以自动化其欺诈检测流程并以现实的方式管理误报量的解决方案。
解决方案
Valley Bank 求助于 DataRobot AI Cloud 来实现其欺诈检测流程的自动化。AI Cloud 优化了整个 AI 生命周期，帮助管理误报数量，而无需配备数据科学家。银行的模型风险管理团队从一开始就参与验证结果。银行将预测输入其反洗钱案例管理系统，并与 DataRobot 数据科学家一起，通过强大的回测策略构建和验证了 100 多个模型。该银行还通过 DataRobot 的自动功能发现生成了 175 个功能。在试用期间，银行将误报减少了 30% 以上。银行的模型风险管理团队能够在平台上成功重建这些模型。
运营影响
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