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bank-t165-retail-finance-wealth-churn-warning-assistant

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用于银行零售理财客户流失预警,当需要监测AUM下滑、赎回集中与到期流失风险并输出处置建议时触发。

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零售客户理财流失预警助手

这个 skill 是做什么的

对理财客户的AUM、赎回与到期结构进行预警监测,识别异常赎回、资产下滑与产品到期集中导致的潜在流失风险,输出风险分层、驱动因素与挽留建议。

适用范围

  • 理财客户流失预警、客户经营与挽留
  • 客户经理、零售运营、财富管理团队
  • 需要可复用的监测与预警输出

何时使用

  • 需要监测理财AUM与赎回行为
  • 需要形成客户挽留与触达行动建议

何时不要使用

  • 仅凭单一赎回就给出违规定性
  • 未提供历史基线或产品到期信息

默认工作流

  1. 确认客户AUM基线与产品到期结构
  2. 识别赎回集中与AUM下滑幅度
  3. 输出风险分层与驱动因素
  4. 形成挽留与替代产品建议

输入要求

  • AUM时间序列与分产品余额
  • 赎回记录与到期日分布
  • 客户风险偏好、产品偏好与触达记录
  • 监测阈值与口径

输出要求

  • 风险等级与优先级
  • 主要驱动因素与证据
  • 挽留与替代产品建议
  • 待核验事项与数据缺口

风险与边界

  • 预警不等同违规或客户流失事实
  • 需标明时间窗口与阈值口径
  • 不得作收益承诺

信息不足时的处理

  • 标注缺失字段
  • 输出最小可行预警结论与补充建议

配套脚本

  • scripts/wealth_churn_warning.py:计算AUM下滑、赎回比例与到期集中度,输出风险等级。

脚本使用

python scripts/wealth_churn_warning.py --input wealth.json --rules rules.json --output out.json

wealth.json 示例结构

{
  "customer_id": "W2001",
  "aum": [
    {"date": "2026-01-01", "value": 800000},
    {"date": "2026-02-01", "value": 720000},
    {"date": "2026-03-01", "value": 600000}
  ],
  "redemptions_30d": 150000,
  "maturity_60d": 200000
}

rules.json 示例结构

{
  "thresholds": {
    "aum_drop_pct": 0.2,
    "redemption_ratio": 0.3,
    "maturity_ratio": 0.4
  }
}

交付标准

  • 能说明“为什么预警”与“下一步怎么做”
  • 输出可直接用于客户挽留与触达