使用 DataRobot AI 应用程序优化贷款预测
地区
- America
国家
- United States
产品
- DataRobot Enterprise AI platform
- DataRobot Optimizer App
技术栈
- Machine Learning
- Data Science
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Revenue Growth
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
- 销售与市场营销
用例
- 欺诈识别
- 补货预测
服务
- 数据科学服务
- 软件设计与工程服务
关于客户
客户是一家位于美国的创新型金融科技公司。他们提供传统消费贷款产品的替代品。该公司主要向个人借款人提供 5,000 美元以下的小额消费贷款，以及为商户提供融资选择。这些贷款的催收是公司每月收入的很大一部分，催收团队因此成为公司业务的重中之重。他们有一个由数据科学家和分析师组成的小团队，他们对 DataRobot 平台印象深刻，并发现使用该平台可以大大提高生产力和数据科学。
挑战
这家金融科技公司通过比传统贷款计划更具适应性的替代方案，在销售点为商家和消费者提供消费融资。他们建立了模型来支持公司各个部门的项目，包括承保、会计和催收。然而，他们在催收部门面临着挑战。由于任何时候都有数以万计的拖欠贷款，催收团队需要拨打大量电话。他们拨打的成功电话越多（以行业指标“正确方联系 (RPC)”衡量），他们就越有可能成功收回这些拖欠贷款，从而为公司带来收入。然而，由于要拨打的目标电话数量如此之多，而且在联系到正确人员或团体方面，接通率通常很低，任何类型的优化或效率都可以产生很大的影响。
解决方案
该团队看到了利用 DataRobot 模型的机会，并与 DataRobot 的新 AI 应用程序团队合作，构建了 DataRobot Optimizer 应用程序的测试版。该应用程序由 DataRobot 的模型提供支持，能够预测一天中拨打电话和连接大量拖欠账户的最佳时间，并在 20 分钟内做出这些预测。然后，这些预测被推送到 Collections 团队使用的自动拨号系统，通过优化列表告诉他们在什么时候拨打谁的电话，从而提高工作效率。DataRobot 团队实施了一种新的专门优化算法，吞吐量提高了 220 倍，满足了在 15-18 分钟内完成工作的挑战。这种新算法已集成到 Optimizer 应用程序中，适用于任何具有潜在客户评分、客户流失或追加销售用例的客户。
运营影响
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