NTUC Income 使用 DataRobot 进行定价分析
公司规模
Large Corporate
地区
- Asia
国家
- Singapore
产品
- DataRobot
技术栈
- Automated Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 分析与建模 - 预测分析
适用功能
- 商业运营
用例
- 需求计划与预测
- 补货预测
服务
- 数据科学服务
关于客户
NTUC Income 是新加坡领先的综合保险公司，为 200 多万客户提供 370 万份保单。它是全国工会联合会的一部分，全国工会联合会是新加坡唯一的全国工会中心，由 58 个工会和 10 个社会企业组成。这些社会企业由政府建立，旨在帮助稳定商品和服务价格、增强工人的购买力并促进更好的劳资关系。NTUC Income 是新加坡唯一的保险合作社，为全国 200 多万客户提供人寿、健康和一般保险产品。它既是新加坡领先的综合保险公司，也是最大的汽车保险公司。
挑战
新加坡顶级综合保险公司 NTUC Income 正面临着整个保险行业索赔成本不断上升的问题。随着经营成本的增加，该公司需要了解导致索赔成本上升的因素、受影响的人以及应采取的措施。此外，随着保险日益成为一种商品，准确的定价变得比以往任何时候都更加重要。然而，保险定价分析可能很复杂、重复且耗时。使用广义线性模型 (GLM) 进行定价分析的传统方法由于多种限制并不理想。这些限制包括假设评级因素与索赔成本之间存在直线关系、耗时的流程以及无法分析索赔描述中的文本。该公司需要一个能够解决其定价分析挑战并与团队一起扩展的解决方案。
解决方案
NTUC Income 求助于自动化机器学习平台 DataRobot 来开展大规模定价分析项目。该平台用于识别风险、索赔频率以及索赔严重程度和性质的变化。DataRobot 的功能影响和词云功能用于识别索赔频率的模式，并直观地展示索赔描述随时间的变化。从数据中获得的见解使 NTUC 的保险精算师能够制定更准确的技术定价。他们可以更好地估计风险溢价，识别错误定价的风险，并考虑未来的通货膨胀。最后一步是从技术定价过渡到商业定价。使用 DataRobot，保险精算师可以分析竞争对手的报价样本，并概括出竞争对手对不同类型的保单的定价。这使他们能够平衡利润率和数量，并找到客户愿意支付的实际保费率。
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