🛡️ 保险公司解决方案Insurance Solution

从被动赔付转型为主动健康管理者From Passive Payer to Active Health Manager

在赔付窗口关闭前锁定干预机会，用PSM因果证据量化干预降低赔付的真实效果，将预防结果转化为标准化可结算证据，支持费率优化和再保险谈判。Lock in intervention before the claims window closes. PSM causal evidence quantifies the real impact on claims, supporting rate optimization and reinsurance negotiations.

申请合作Get in Touch → 险企评估指南Insurer Assessment Guide

15%

高危人群平均事件率基线High-risk event rate baseline

25%

干预后可节省赔付估算Estimated claims savings post-intervention

PSM

因果归因，非简单相关Causal attribution, not correlation

<2周

核保系统接入周期Underwriting system integration

核心挑战Core Challenges

健康险赔付的三个结构性困境Three Structural Barriers in Health Insurance Claims

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高赔付人群识别滞后Late Detection of High-Claim Groups

传统核保依赖历史记录和问卷，无法在承保时准确识别潜在高赔付人群，赔付风险在承保时已被锁定。Traditional underwriting relies on history and questionnaires, unable to accurately identify high-claim populations at policy inception.

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干预效果无法量化Unquantifiable Intervention Outcomes

险企投入健康管理资源，但无法向管理层和再保险方证明干预真实降低了多少赔付——没有因果证据，健康管理永远是成本。Insurers invest in health management but cannot prove to management or reinsurers that interventions actually reduced claims.

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受益方与付费方错位Beneficiary-Payer Misalignment

企业为员工购买健康险，干预受益的是险企（赔付降低），但险企无法向企业证明是干预降低了赔付——三方之间缺少可流通的证据货币。Employers buy insurance, but insurers benefit from lower claims. No shared evidence currency exists between the three parties.

商业模式转型Business Model Transformation

从"赔付方"到"健康管理者"From "Payer" to "Health Manager"

❌ 传统险企模式Traditional Insurer Model

被动等待赔付事件发生Passively waiting for claims

健康管理是成本中心Health management is a cost center

无法量化干预ROICannot quantify intervention ROI

费率调整依赖精算历史Rate adjustments rely on actuarial history

与企业客户缺少健康数据连接No health data connection with clients

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✅ ReHealth Core 赋能后With ReHealth Core

提前识别高危，在窗口期干预Early identification and proactive intervention

健康管理产生可量化的赔付节省Quantifiable claims savings from health management

PSM因果证据证明干预ROIPSM causal evidence proves intervention ROI

动态风险数据支持精准定价Dynamic risk data enables precision pricing

与企业共享健康管理成果Share health outcomes with enterprise clients

解决方案Solution

四步打通险企主动健康管理闭环Four Steps to Active Health Management

承保前风险分层Pre-Underwriting Risk Stratification

基于16个临床特征维度，对待承保人群进行心脑血管风险分层，支持差异化定价和风险选择决策。16 clinical feature dimensions for cardiovascular risk stratification of prospective policyholders, enabling differentiated pricing and risk selection.

批量核保Batch Underwriting风险分层Risk Stratification差异化定价Differentiated Pricing

承保后高危人群干预Post-Underwriting High-Risk Intervention

对已承保的高风险人群推送个性化干预方案，在赔付窗口关闭前锁定干预机会，完整记录干预轨迹。Push personalized interventions to high-risk policyholders before the claims window closes. Full trajectory logging for PSM attribution.

高危识别High-Risk ID个性化干预Personalized轨迹记录Tracking

PSM因果归因——量化赔付降低效果PSM Attribution — Quantify Claims Reduction

通过倾向评分匹配消除选择偏倚，量化干预对赔付降低的真实因果效应（ATT）。向再保险方、监管机构和企业客户展示健康管理ROI的核心证据。PSM eliminates selection bias and quantifies the true causal effect (ATT) of interventions on claims. Core evidence for presenting health management ROI to reinsurers and regulators.

PSMATT选择偏倚消除Bias Elimination

可结算证据——支持费率优化和再保谈判Billable Evidence — Rate Optimization & Reinsurance

生成标准化可结算证据报告，向企业客户证明健康管理项目的实际赔付节省，支持差异化保费方案；向再保险方证明风险池质量，支持再保条款谈判。Standardized billable evidence reports prove actual claims savings to enterprise clients, support differentiated premiums, and demonstrate risk pool quality to reinsurers.

费率优化Rate Optimization再保谈判Reinsurance企业客户证明Client Proof

常见问题FAQ

保险合作常见问题Insurance Partnership FAQ

PSM因果证据如何帮助险企进行费率优化？How does PSM evidence support rate optimization?

PSM证据量化了干预降低赔付的真实因果效应，险企可以此为依据向企业客户提供差异化保费方案——对参与健康管理的投保人给予费率优惠，同时向再保险方证明风险池质量提升。PSM evidence quantifies the true causal effect of interventions on claims reduction. Insurers can offer differentiated premiums to participants in health management programs while proving improved risk pool quality to reinsurers.

ReHealth Core 如何与核保系统对接？How does ReHealth Core integrate with underwriting systems?

提供标准RESTful API，支持批量核保风险评估和单人实时查询两种模式。平均接入周期不超过2周，数据格式支持JSON，兼容主流核保系统。Standard RESTful API supporting batch underwriting risk assessment and individual real-time queries. Average integration under 2 weeks, JSON format compatible with major underwriting systems.

投保人数据如何保障安全合规？How is policyholder data kept secure and compliant?

采用医疗级联邦学习架构，投保人原始数据不出险企本地环境。满足《个人信息保护法》《保险法》相关数据处理合规要求。所有数据处理均在差分隐私保护下进行。Medical-grade federated learning: policyholder raw data stays within the insurer's local environment. Compliant with PIPL and Insurance Law data processing requirements, with differential privacy protection.

准备好了解更多？Ready to Learn More?

联系我们，了解ReHealth Core如何帮助您的险企实现主动健康管理转型。Contact us to learn how ReHealth Core can help your insurer transition to active health management.

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