通过 DataRobot 的 AI 服务进行独立模型验证
公司规模
Large Corporate
地区
- America
国家
- United States
产品
- DataRobot’s Enterprise AI platform
- DataRobot’s AI Services
技术栈
- Machine Learning
- Predictive Models
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Digital Expertise
技术
- 分析与建模 - 预测分析
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 金融与保险
适用功能
- 商业运营
用例
- 预测性维护
- 欺诈识别
服务
- 数据科学服务
关于客户
客户是一家总部位于美国的领先金融科技公司。他们帮助各行各业的客户获得购买商品和服务所需的资金和付款计划。他们还帮助商家和服务供应商通过信贷计划增加销售额。该公司使用机器学习模型进行决策，这在受到严格监管的金融行业中至关重要。他们在 DataRobot 平台上构建了多个模型并部署到生产中，包括内部信用评分模型、欺诈评分模型和经销商评分模型。
挑战
这家总部位于美国的金融科技公司在将其业务流程与监管合规要求相一致方面面临挑战。他们使用机器学习模型进行决策，由于该行业受到严格监管，这增加了风险。该公司已经在使用 DataRobot 的企业 AI 平台来改进其模型构建，但他们需要加快其业务流程与模型风险管理法规的一致性。他们在 DataRobot 平台上构建了几个模型并部署到生产中，包括内部信用评分模型、欺诈评分模型和经销商评分模型。然而，在与银行合作后，他们需要进行独立的模型验证，这是他们合作的关键组成部分。
解决方案
该金融科技公司与 DataRobot 的 AI 服务部门合作，独立验证其模型。DataRobot 的 AI 服务团队独立于公司其他部门运营，独立完成了验证工作的五个主要阶段：项目规划、文档和方法审查、模型性能、测试和分析以及最终模型验证报告和工作底稿的准备。该团队提供了金融科技公司所需的独立验证，并附有模型验证报告，该报告详细描述了模型的工作原理，以及在验证过程中为有效挑战该模型的开发所做的工作。该公司计划每年与 DataRobot 的 AI 服务部门合作，以满足其模型验证需求。
运营影响
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