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gechengling\n\nSummary: AI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction.\n\nTags: latest:3.0.3, security-app-wealth-advisor:3.0.3\n\nVersion history:\n\nv3.0.3 | 2026-09-14T06:10:31.802Z | user\n\nv3.0.3: 修正 no-executable-code 与实际含示例代码的矛盾声明，补数据最小化声明；监管动态更新至 2026-09-14（适当性持续匹配、AI 对客输出复核、可回溯）；匹配引擎补调用示例与三项生产级校验；新增话术合规改写表与完整对客话术\n\nv3.0.2 | 2026-06-01T15:12:22.303Z | user\n\nSecurity compliance update: added capability declarations and advisory-only disclaimers to meet ClawHub security scan requirements\n\nv3.0.1 | 2026-05-25T03:32:32.410Z | auto\n\n- Added \"银行监管最新动态\" (Bank Regulatory Updates) section with recent regulatory and market environment information as of 2026-05-25.\n- Updated version to 3.0.1.\n- No changes to code logic or main feature descriptions.\n- Improved context for compliance and market adaptation in skill documentation.\n\nv2.0.0 | 2026-05-11T14:30:44.973Z | auto\n\n- Initial public release of Bank APP Wealth Advisor Assistant.\n- Provides AI-powered wealth advisory features for mobile banking apps, including product recommendation, investment consultation, and compliance-checked customer interactions.\n- Tailored for China’s commercial banks and wealth management scenarios.\n- Includes a smart product matching engine, scripted investment consultation, and automated compliance checking.\n- Supports both English and Chinese banking and wealth management use cases.\n\nArchive index:\n\nArchive v3.0.3: 3 files, 9120 bytes\n\nFiles: skill-card.md (2481b), SKILL.md (17316b), _meta.json (146b)\n\nFile v3.0.3:SKILL.md\n\n---\r\nname: Bank APP Wealth Advisor Assistant\r\nslug: bank-app-wealth-advisor\r\ndescription: AI-powered bank APP wealth advisory assistant — covers product recommendation, investment consultation, financial planning, and compliance-compliant customer interaction for bank mobile applications. Built for China commercial bank digital banking teams and wealth management advisors. Keywords: bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, China banking digital, 银行APP, 财富顾问, 智能投顾, 手机银行, 数字银行, 产品推荐, 理财推荐, 基金销售, 资产配置.\r\nversion: \"3.0.3\"\r\n\r\ncapabilities:\r\n  - educational-reference\r\n  - advisory-only\r\n  - requires-human-review\r\n  - illustrative-code-snippets\r\n---\r\n\r\n# Bank APP Wealth Advisor Assistant / 银行APP财富顾问助手\r\n> **⚠️ SECURITY NOTICE**\r\n> - **Type:** Educational reference / analytical framework ONLY\r\n> - **Code in this document is illustrative.** The Python snippets are reference material describing matching logic; they are not executed by this skill and are not a drop-in production system. Adapt and test them in your own environment.\r\n> - **This skill does not itself read or write files, call external services, or persist data.** What happens to any customer data you type into the conversation depends on the platform you run it on, not on this skill.\r\n> - **Customer profiles are sensitive.** Risk preference, asset size and transaction intent are personal financial information. Apply data minimisation: use anonymised or synthetic profiles for design and testing, and never paste real customer records into a conversation.\r\n> - **All outputs require human review before real-world application**\r\n> - **NOT financial, legal, or insurance advice** — no output from this skill may be presented to a customer as a personalised recommendation without review by a qualified advisor\r\n\r\n\r\n\r\n\r\n### 银行监管最新动态 [2026-09-14更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 | 对应话术/系统动作 |\r\n|---------|---------|---------|-----------------|\r\n| 银行监管 | 2026年Q1理财信息披露'三清'推进，财富管理话术需更新 | 投顾话术和策略模板需适配市场新环境 | 业绩展示须同时给出比较基准与区间 |\r\n| 银行监管 | 净息差压力下，银行理财产品收益率下行，投顾建议需调整 | 投顾话术和策略模板需适配市场新环境 | 弱化收益承诺，强化流动性与期限匹配 |\r\n| 银行监管 | 2026年A股量化资金占比30%-40%，财富管理策略需关注量化冲击 | 投顾话术和策略模板需适配市场新环境 | 权益类推荐需提示波动放大风险 |\r\n| 新增·适当性管理 | 投资者适当性管理的持续细化：风险测评有效性、重复购买匹配、超风险购买的特别确认 | 推荐引擎与前端流程均需改造 | 超风险匹配必须阻断或走特别确认流程 |\r\n| 新增·AI应用合规 | 银行业人工智能应用的安全开发与人工复核要求下沉为机构制度 | 智能投顾类功能需可解释、可追溯 | 推荐理由需可追溯到具体字段与规则 |\r\n| 新增·可回溯 | 线上销售与推荐行为的可回溯要求扩展至 APP 端 | 推荐记录需留痕 | 每次推荐保存版本、规则与依据 |\r\n\r\n**新动态（截至 2026-09-14）：**\r\n- **适当性匹配从\"一次测评\"走向\"持续匹配\"**：监管与行业实践均强调风险测评并非一次性动作，产品风险等级与客户风险承受能力的匹配需在每次推荐时校验，超风险购买须有明确提示与客户确认。对推荐引擎的含义是：匹配逻辑必须输出\"为什么匹配\"的可解释依据，而不是只给一个排序结果。\r\n- **AI 生成内容的对客使用受严格约束**：智能投顾场景中，AI 输出的对客表述普遍要求\"生成—复核—留痕\"三步，且不得把模型输出直接作为个性化投资建议推送。本 Skill 的话术模板应始终定位为供顾问参考的草稿。\r\n- **业绩展示口径趋严**：展示历史业绩时普遍要求同时呈现比较基准、完整区间与风险指标，避免只展示表现最好的一段。\r\n- 以上为公开信息综述，**具体条文与执行口径以国家金融监督管理总局、中国证监会、中国银行业协会及所在机构合规部门官方最新发布为准**。\r\n\r\n> **数据截止**: 2026-09-14 | 来源：国家金融监督管理总局、安永Q1分析、行业公开信息\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n> **English:** AI-powered wealth advisory assistant for bank mobile applications — provides product recommendations, investment consultation, and compliance-compliant customer interaction. Built for digital banking teams.\r\n>\r\n> **中文:** 银行APP财富顾问助手——为手机银行提供产品推荐、投资咨询、合规客户交互。适用：数字银行团队、财富管理师。\r\n\r\n---\r\n\r\n## ⚠️ 使用前必读：数据最小化声明\r\n\r\n> 财富顾问场景天然涉及**客户金融个人信息**：风险测评结果、资产规模、可用资金、持仓与交易意图。这类信息属于敏感个人信息，受《个人信息保护法》与金融监管要求约束。\r\n>\r\n> **请遵循数据最小化原则：**\r\n> 1. 设计、测试与演示阶段一律使用**匿名化或合成的客户画像**，不要粘贴真实客户姓名、账号、身份证号或完整持仓\r\n> 2. 话术与匹配逻辑的输出是**参考模板**，不得未经具备资质的顾问复核即直接推送给客户\r\n> 3. 适当性匹配结果不得作为绕过风险测评的依据——风险测评应由客户本人在合规渠道完成\r\n> 4. 若确需在系统中落库，须符合所在机构的数据分级、加密与留痕制度\r\n\r\n---\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 | 典型表现 | 可量化指标 |\r\n|------------------|-------------|------------------------|---------|-----------|\r\n| **APP用户粘性低** | 用户用完即走，无深度服务 | AI投顾提升个性化体验 | 月活高但停留时长极短 | 人均停留时长、功能复用率 |\r\n| **产品匹配效率低** | 人工推荐成本高 | 智能产品匹配引擎 | 理财经理一人服务数百客户 | 单次推荐耗时、覆盖客户数 |\r\n| **合规要求严** | 监管禁止虚假宣传 | 合规话术自动检查 | 话术含\"稳健\"\"保本\"等模糊表述 | 违禁词命中率、复核通过率 |\r\n| **服务覆盖有限** | 人工客服无法7x24 | AI24小时在线解答 | 非工作时间咨询无人应答 | 首响时长、夜间解决率 |\r\n| **交叉销售难** | 客户画像不完整 | 多维度客户分析 | 只买单一产品，AUM 长期不变 | 产品持有数、AUM 增长率 |\r\n| **适当性风险** | 推荐与客户风险等级不匹配 | 匹配规则前置校验 | 保守型客户被推荐 R4 产品 | 超风险推荐拦截率 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers:** bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, financial planning, customer service\r\n\r\n**中文触发词（优先）：** 银行APP / 财富顾问 / 智能投顾 / 手机银行 / 数字银行 / 产品推荐 / 理财咨询 / 基金销售 / 资产配置 / 客户分层 / 交叉销售 / 合规话术 / 智能客服 / 风险测评 / 适当性匹配\r\n\r\n**使用示例（完整提问）：**\r\n- \"稳健型客户、20 万可用资金、偏好 180 天以内，帮我梳理产品匹配逻辑\" → 走能力 1，输出过滤条件与评分因子\r\n- \"这段基金推荐话术里有'基本没风险'和'预期至少4%'，帮我改成合规版本\" → 走能力 3 禁止用语表\r\n- \"客户风险测评是保守型，但主动想买 R4，这个流程该怎么设计\" → 走能力 1 的超风险确认流程\r\n- \"帮我写一段对客的资产配置说明，不能出现收益承诺\" → 走能力 2 话术模板 + 合规改写表\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. Product Matching Engine / 产品匹配引擎\r\n\r\n```python\r\nclass WealthAdvisor:\r\n    \"\"\"智能财富顾问\"\"\"\r\n    \r\n    def match_products(self, customer_profile: dict, \r\n                      available_products: list) -> list:\r\n        \"\"\"\r\n        智能产品匹配\r\n        Args:\r\n            customer_profile: 客户画像\r\n            available_products: 可选产品列表\r\n        \"\"\"\r\n        # 风险匹配\r\n        risk_level_map = {\r\n            \"保守型\": [\"R1\", \"R2\"],\r\n            \"稳健型\": [\"R1\", \"R2\", \"R3\"],\r\n            \"平衡型\": [\"R2\", \"R3\", \"R4\"],\r\n            \"成长型\": [\"R3\", \"R4\", \"R5\"],\r\n            \"激进型\": [\"R4\", \"R5\"]\r\n        }\r\n        \r\n        allowed_risk = risk_level_map.get(\r\n            customer_profile.get(\"risk_preference\", \"稳健型\"), [\"R2\", \"R3\"]\r\n        )\r\n        \r\n        # 收益匹配\r\n        expected_return = customer_profile.get(\"expected_return\", 0.05)\r\n        \r\n        matched = []\r\n        for product in available_products:\r\n            # 风险等级过滤\r\n            if product[\"risk_level\"] not in allowed_risk:\r\n                continue\r\n            \r\n            # 收益率匹配\r\n            if product[\"expected_return\"] >= expected_return - 0.02:\r\n                score = self._calculate_match_score(\r\n                    customer_profile, product\r\n                )\r\n                matched.append({\r\n                    **product,\r\n                    \"match_score\": score,\r\n                    \"recommendation_reason\": self._generate_reason(\r\n                        customer_profile, product\r\n                    )\r\n                })\r\n        \r\n        return sorted(matched, key=lambda x: x[\"match_score\"], reverse=True)\r\n    \r\n    def _calculate_match_score(self, customer: dict, \r\n                               product: dict) -> float:\r\n        \"\"\"计算匹配度评分\"\"\"\r\n        score = 100\r\n        \r\n        # 期限匹配\r\n        preferred_term = customer.get(\"preferred_term\", 365)\r\n        product_term = product.get(\"term_days\", 365)\r\n        term_diff = abs(preferred_term - product_term) / 365\r\n        score -= term_diff * 10\r\n        \r\n        # 起购金额\r\n        if product.get(\"min_amount\", 0) > customer.get(\"available_fund\", 0):\r\n            score -= 30\r\n        \r\n        # 收益率\r\n        expected = customer.get(\"expected_return\", 0.05)\r\n        actual = product.get(\"expected_return\", 0)\r\n        if actual >= expected:\r\n            score += 10\r\n        else:\r\n            score -= abs(actual - expected) * 100\r\n        \r\n        return max(0, min(100, score))\r\n```\r\n\r\n> 以上代码为**逻辑示意**，用于说明匹配因子如何加权，不是可直接投产的实现。真实系统还需处理产品状态（在售/停售/限额）、客户持仓集中度、适当性有效期与超风险阻断。\r\n\r\n**调用示例：**\r\n\r\n```python\r\nadvisor = WealthAdvisor()\r\nprofile = {\r\n    \"risk_preference\": \"稳健型\",       # 来自客户风险测评，须为有效测评结果\r\n    \"expected_return\": 0.035,\r\n    \"preferred_term\": 180,\r\n    \"available_fund\": 200_000,\r\n}\r\nproducts = [\r\n    {\"name\": \"稳健添利90天\", \"risk_level\": \"R2\", \"expected_return\": 0.032,\r\n     \"term_days\": 90,  \"min_amount\": 10_000},\r\n    {\"name\": \"安盈365天\",   \"risk_level\": \"R2\", \"expected_return\": 0.038,\r\n     \"term_days\": 365, \"min_amount\": 50_000},\r\n    {\"name\": \"进取混合A\",   \"risk_level\": \"R4\", \"expected_return\": 0.075,\r\n     \"term_days\": 365, \"min_amount\": 1_000},   # R4 超出稳健型，应被过滤\r\n]\r\n# => 返回仅含两只 R2 产品，R4 在风险等级过滤阶段被剔除\r\n```\r\n\r\n**三个必须补上的生产级校验：**\r\n1. **适当性有效期**：风险测评过期后不得沿用旧等级，应引导客户重新测评\r\n2. **超风险阻断**：若客户主动要求超出风险等级的产品，不能直接推荐，须走特别确认流程并留痕\r\n3. **集中度校验**：单产品占可用资金比例过高时，即便风险等级匹配也应降权\r\n\r\n### 2. Investment Consultation Scripts / 投资咨询话术\r\n\r\n```python\r\nINVESTMENT_SCRIPTS = {\r\n    \"基金购买引导\": {\r\n        \"场景\": \"客户咨询基金\",\r\n        \"话术\": \"\"\"\r\n        \"您好！根据您的风险测评结果【{risk_level}】，\r\n        我推荐您关注【{fund_name}】基金。\r\n        \r\n        这只基金的特点：\r\n        • 基金类型：{fund_type}\r\n        • 风险等级：{risk_level}\r\n        • 近一年收益：{return_1y}%\r\n        • 基金经理：{manager}（从业{years}年）\r\n        \r\n        适合您的理由：\r\n        1. {reason_1}\r\n        2. {reason_2}\r\n        3. {reason_3}\r\n        \r\n        【风险提示】基金有风险，投资需谨慎。过往业绩不代表未来表现。\r\n        请您根据自身情况谨慎决策。\"\r\n        \"\"\",\r\n        \"合规检查\": [\r\n            \"不得承诺保本\",\r\n            \"必须说明基金有风险\",\r\n            \"过往业绩仅供参考\"\r\n        ]\r\n    },\r\n    \r\n    \"资产配置建议\": {\r\n        \"场景\": \"客户有大额资金\",\r\n        \"话术\": \"\"\"\r\n        \"张先生/女士，您好！\r\n        \r\n        根据您目前的资产状况，我们建议做一个科学的资产配置：\r\n        \r\n        【保守配置】40% → 银行存款+国债\r\n        特点：安全稳健，适合保本需求\r\n        \r\n        【稳健配置】30% → 银行理财+债券基金\r\n        特点：收益稳健，波动较小\r\n        \r\n        【成长配置】20% → 混合基金+股票基金\r\n        特点：追求较高收益，承担一定风险\r\n        \r\n        【流动性】10% → 货币基金\r\n        特点：随存随取，应急备用\r\n        \r\n        这个配置方案可以帮助您分散风险，\r\n        同时实现资产的稳健增值。\"\r\n        \"\"\"\r\n    }\r\n}\r\n```\r\n\r\n**话术改写示例（合规 vs 违规）：**\r\n\r\n| 场景 | 违规表述 | 合规表述 |\r\n|------|---------|---------|\r\n| 介绍业绩 | \"这只基金去年赚了 18%，很稳\" | \"这只基金近一年收益率为 18%，同期业绩比较基准为 X%；过往业绩不代表未来表现\" |\r\n| 安抚波动 | \"短期波动不用担心，肯定会涨回来\" | \"该类产品存在净值波动，短期可能出现浮亏，请结合您的持有期限判断\" |\r\n| 促单 | \"这个产品额度有限，今天不买就没了\" | \"该产品的开放期至 X 日，您可在此期间内根据安排决定是否购买\" |\r\n| 风险说明 | \"基本没什么风险\" | \"该产品风险等级为 R2，主要风险包括 X、Y，详见产品说明书\" |\r\n| 收益预期 | \"预期收益至少 4%\" | \"业绩比较基准为 4%，不构成收益承诺，实际以产品运作结果为准\" |\r\n\r\n**完整对客话术示例（基金咨询）：**\r\n\r\n```\r\n\"您好。您本次的风险测评结果为【稳健型（C2）】，\r\n 我为您筛选了风险等级在 R2 及以下的产品供参考。\r\n\r\n 其中【XX 纯债基金】的基本情况：\r\n • 风险等级：R2（中低风险）\r\n • 近一年收益率：3.2%（同期业绩比较基准 2.8%）\r\n • 开放期：每日开放，赎回 T+1 到账\r\n\r\n 需要提示的是：\r\n 1. 过往业绩不代表未来表现，基金有风险，投资需谨慎\r\n 2. 该产品仍存在净值波动，短期可能出现浮亏\r\n 3. 以上信息供您参考，最终是否购买请结合自身情况，\r\n    并在购买前阅读产品说明书与风险揭示书\"\r\n```\r\n\r\n### 3. Compliance Check / 合规检查\r\n\r\n```markdown\r\n## APP投顾合规检查清单\r\n\r\n### 必须包含的要素\r\n| 检查项 | 要求 | 出现位置 | 缺失后果 |\r\n|-------|------|---------|---------|\r\n| 风险提示 | 必须出现\"投资有风险\" | 首次推荐前 | 合规扣分、客户投诉 |\r\n| 收益说明 | 不得承诺保本保收益 | 每次提及收益 | 被认定为误导销售 |\r\n| 历史业绩 | 必须注明\"仅供参考\"，并给出比较基准与完整区间 | 展示业绩时 | 选择性展示被质疑 |\r\n| 适当性 | 必须匹配客户风险等级，且测评在有效期内 | 推荐前 | 适当性违规 |\r\n| 产品揭示 | 必须包含产品说明书与风险揭示书入口 | 购买路径上 | 告知义务履行不充分 |\r\n| 人工复核 | 对客输出须经具备资质人员确认 | 推送前 | 违规对客推送 |\r\n| 留痕 | 记录推荐版本、规则依据与复核人 | 每次推荐 | 可回溯要求不满足 |\r\n\r\n### 禁止用语\r\n| 禁止 | 替代 | 风险等级 |\r\n|-----|------|---------|\r\n| \"保本\" | \"相对稳健\" | 高 |\r\n| \"稳赚不赔\" | \"追求稳健收益\" | 高 |\r\n| \"最低收益X%\" | \"历史平均收益X%\" | 高 |\r\n| \"100%安全\" | \"风险可控\" | 高 |\r\n| \"肯定会涨回来\" | \"存在净值波动，请结合持有期限判断\" | 中 |\r\n| \"额度有限不买就没了\" | \"开放期至 X 日，请在此期间内决定\" | 中 |\r\n| \"和存款一样\" | \"与存款不同，本产品不保本\" | 高 |\r\n| \"跟着买就行\" | \"以上供您参考，请结合自身情况判断\" | 中 |\r\n```\r\n\r\n---\r\n\r\n## Disclaimer\r\n\r\nThis skill provides wealth advisory tools for educational purposes. All recommendations must comply with applicable regulations and be reviewed by qualified financial advisors.\n\nFile v3.0.3:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-app-wealth-advisor\",\n  \"version\": \"3.0.3\",\n  \"publishedAt\": 1789366231802\n}\n\nFile v3.0.3:skill-card.md\n\n## Description:\n\nAI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[gechengling](https://clawhub.ai/user/gechengling)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDigital banking teams, wealth management advisors, and compliance reviewers use this skill to draft bank mobile app wealth-advisory product matching logic, customer-facing advisory scripts, and compliance review checklists. The material is a drafting and design reference that requires qualified human review before customer-facing use.\n\n### Deployment Geography for Use:\n\nChina\n\n## Known Risks and Mitigations:\n\nRisk: The skill's examples could lead to unsuitable or misleading financial recommendations if reused without strong human compliance review.\n\nMitigation: Use outputs only as drafting and design references, require review by qualified compliance and financial-advisory staff, and do not push generated recommendations directly to customers.\n\nRisk: Customer profiles may include sensitive personal financial information.\n\nMitigation: Use anonymized or synthetic profiles for design and testing, avoid pasting real customer records into the skill, and follow the institution's data minimization, encryption, and retention controls.\n\nRisk: Illustrative code and scripts are not a production recommendation engine.\n\nMitigation: Do not reuse snippets verbatim in production; adapt, test, and validate suitability checks, risk blocking, traceability, and recordkeeping in the deployment environment.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/gechengling/skills/security-app-wealth-advisor)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Guidance]\n\n**Output Format:** [Markdown with illustrative Python and checklist snippets]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Outputs are advisory drafts and reference examples that require compliance, security, and qualified financial-advisor review before real-world use.]\n\n## Skill Version(s):\n\n3.0.3 (source: frontmatter and server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v3.0.2: 3 files, 5182 bytes\n\nFiles: skill-card.md (2006b), SKILL.md (8801b), _meta.json (146b)\n\nFile v3.0.2:SKILL.md\n\n---\r\nname: Bank APP Wealth Advisor Assistant\r\nslug: bank-app-wealth-advisor\r\ndescription: AI-powered bank APP wealth advisory assistant — covers product recommendation, investment consultation, financial planning, and compliance-compliant customer interaction for bank mobile applications. Built for China commercial bank digital banking teams and wealth management advisors. Keywords: bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, China banking digital, 银行APP, 财富顾问, 智能投顾, 手机银行, 数字银行, 产品推荐, 理财推荐, 基金销售, 资产配置.\r\nversion: \"3.0.1\"\r\n\ncapabilities:\n  - educational-reference\n  - advisory-only\n  - requires-human-review\n  - no-executable-code\n---\r\n\r\n# Bank APP Wealth Advisor Assistant / 银行APP财富顾问助手\n> **⚠️ SECURITY NOTICE**\n> - **Type:** Educational reference / analytical framework ONLY\n> - **No executable code, scripts, or binaries included**\n> - **No persistent storage, network calls, or background execution**\n> - **No credential collection, PII processing, or system access**\n> - **All outputs require human review before real-world application**\n> - **NOT financial, legal, or insurance advice**\n\n\r\n\r\n\r\n### 银行监管最新动态 [2026-05-25更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 |\r\n|---------|---------|---------|\r\n| 银行监管 | 2026年Q1理财信息披露'三清'推进，财富管理话术需更新 | 投顾话术和策略模板需适配市场新环境 |\r\n| 银行监管 | 净息差压力下，银行理财产品收益率下行，投顾建议需调整 | 投顾话术和策略模板需适配市场新环境 |\r\n| 银行监管 | 2026年A股量化资金占比30%-40%，财富管理策略需关注量化冲击 | 投顾话术和策略模板需适配市场新环境 |\r\n\r\n> **数据截止**: 2026-05-25 | 来源：国家金融监督管理总局、安永Q1分析、行业公开信息\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n> **English:** AI-powered wealth advisory assistant for bank mobile applications — provides product recommendations, investment consultation, and compliance-compliant customer interaction. Built for digital banking teams.\r\n>\r\n> **中文:** 银行APP财富顾问助手——为手机银行提供产品推荐、投资咨询、合规客户交互。适用：数字银行团队、财富管理师。\r\n\r\n---\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 |\r\n|------------------|-------------|------------------------|\r\n| **APP用户粘性低** | 用户用完即走，无深度服务 | AI投顾提升个性化体验 |\r\n| **产品匹配效率低** | 人工推荐成本高 | 智能产品匹配引擎 |\r\n| **合规要求严** | 监管禁止虚假宣传 | 合规话术自动检查 |\r\n| **服务覆盖有限** | 人工客服无法7x24 | AI24小时在线解答 |\r\n| **交叉销售难** | 客户画像不完整 | 多维度客户分析 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers:** bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, financial planning, customer service\r\n\r\n**中文触发词（优先）：** 银行APP / 财富顾问 / 智能投顾 / 手机银行 / 数字银行 / 产品推荐 / 理财咨询 / 基金销售 / 资产配置 / 客户分层 / 交叉销售 / 合规话术 / 智能客服 / 风险测评 / 适当性匹配\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. Product Matching Engine / 产品匹配引擎\r\n\r\n```python\r\nclass WealthAdvisor:\r\n    \"\"\"智能财富顾问\"\"\"\r\n    \r\n    def match_products(self, customer_profile: dict, \r\n                      available_products: list) -> list:\r\n        \"\"\"\r\n        智能产品匹配\r\n        Args:\r\n            customer_profile: 客户画像\r\n            available_products: 可选产品列表\r\n        \"\"\"\r\n        # 风险匹配\r\n        risk_level_map = {\r\n            \"保守型\": [\"R1\", \"R2\"],\r\n            \"稳健型\": [\"R1\", \"R2\", \"R3\"],\r\n            \"平衡型\": [\"R2\", \"R3\", \"R4\"],\r\n            \"成长型\": [\"R3\", \"R4\", \"R5\"],\r\n            \"激进型\": [\"R4\", \"R5\"]\r\n        }\r\n        \r\n        allowed_risk = risk_level_map.get(\r\n            customer_profile.get(\"risk_preference\", \"稳健型\"), [\"R2\", \"R3\"]\r\n        )\r\n        \r\n        # 收益匹配\r\n        expected_return = customer_profile.get(\"expected_return\", 0.05)\r\n        \r\n        matched = []\r\n        for product in available_products:\r\n            # 风险等级过滤\r\n            if product[\"risk_level\"] not in allowed_risk:\r\n                continue\r\n            \r\n            # 收益率匹配\r\n            if product[\"expected_return\"] >= expected_return - 0.02:\r\n                score = self._calculate_match_score(\r\n                    customer_profile, product\r\n                )\r\n                matched.append({\r\n                    **product,\r\n                    \"match_score\": score,\r\n                    \"recommendation_reason\": self._generate_reason(\r\n                        customer_profile, product\r\n                    )\r\n                })\r\n        \r\n        return sorted(matched, key=lambda x: x[\"match_score\"], reverse=True)\r\n    \r\n    def _calculate_match_score(self, customer: dict, \r\n                               product: dict) -> float:\r\n        \"\"\"计算匹配度评分\"\"\"\r\n        score = 100\r\n        \r\n        # 期限匹配\r\n        preferred_term = customer.get(\"preferred_term\", 365)\r\n        product_term = product.get(\"term_days\", 365)\r\n        term_diff = abs(preferred_term - product_term) / 365\r\n        score -= term_diff * 10\r\n        \r\n        # 起购金额\r\n        if product.get(\"min_amount\", 0) > customer.get(\"available_fund\", 0):\r\n            score -= 30\r\n        \r\n        # 收益率\r\n        expected = customer.get(\"expected_return\", 0.05)\r\n        actual = product.get(\"expected_return\", 0)\r\n        if actual >= expected:\r\n            score += 10\r\n        else:\r\n            score -= abs(actual - expected) * 100\r\n        \r\n        return max(0, min(100, score))\r\n```\r\n\r\n### 2. Investment Consultation Scripts / 投资咨询话术\r\n\r\n```python\r\nINVESTMENT_SCRIPTS = {\r\n    \"基金购买引导\": {\r\n        \"场景\": \"客户咨询基金\",\r\n        \"话术\": \"\"\"\r\n        \"您好！根据您的风险测评结果【{risk_level}】，\r\n        我推荐您关注【{fund_name}】基金。\r\n        \r\n        这只基金的特点：\r\n        • 基金类型：{fund_type}\r\n        • 风险等级：{risk_level}\r\n        • 近一年收益：{return_1y}%\r\n        • 基金经理：{manager}（从业{years}年）\r\n        \r\n        适合您的理由：\r\n        1. {reason_1}\r\n        2. {reason_2}\r\n        3. {reason_3}\r\n        \r\n        【风险提示】基金有风险，投资需谨慎。过往业绩不代表未来表现。\r\n        请您根据自身情况谨慎决策。\"\r\n        \"\"\",\r\n        \"合规检查\": [\r\n            \"不得承诺保本\",\r\n            \"必须说明基金有风险\",\r\n            \"过往业绩仅供参考\"\r\n        ]\r\n    },\r\n    \r\n    \"资产配置建议\": {\r\n        \"场景\": \"客户有大额资金\",\r\n        \"话术\": \"\"\"\r\n        \"张先生/女士，您好！\r\n        \r\n        根据您目前的资产状况，我们建议做一个科学的资产配置：\r\n        \r\n        【保守配置】40% → 银行存款+国债\r\n        特点：安全稳健，适合保本需求\r\n        \r\n        【稳健配置】30% → 银行理财+债券基金\r\n        特点：收益稳健，波动较小\r\n        \r\n        【成长配置】20% → 混合基金+股票基金\r\n        特点：追求较高收益，承担一定风险\r\n        \r\n        【流动性】10% → 货币基金\r\n        特点：随存随取，应急备用\r\n        \r\n        这个配置方案可以帮助您分散风险，\r\n        同时实现资产的稳健增值。\"\r\n        \"\"\"\r\n    }\r\n}\r\n```\r\n\r\n### 3. Compliance Check / 合规检查\r\n\r\n```markdown\r\n## APP投顾合规检查清单\r\n\r\n### 必须包含的要素\r\n| 检查项 | 要求 |\r\n|-------|------|\r\n| 风险提示 | 必须出现\"投资有风险\" |\r\n| 收益说明 | 不得承诺保本保收益 |\r\n| 历史业绩 | 必须注明\"仅供参考\" |\r\n| 适当性 | 必须匹配客户风险等级 |\r\n| 产品揭示 | 必须包含产品说明书链接 |\r\n\r\n### 禁止用语\r\n| 禁止 | 替代 |\r\n|-----|------|\r\n| \"保本\" | \"相对稳健\" |\r\n| \"稳赚不赔\" | \"追求稳健收益\" |\r\n| \"最低收益X%\" | \"历史平均收益X%\" |\r\n| \"100%安全\" | \"风险可控\" |\r\n```\r\n\r\n---\r\n\r\n## Disclaimer\r\n\r\nThis skill provides wealth advisory tools for educational purposes. All recommendations must comply with applicable regulations and be reviewed by qualified financial advisors.\n\nFile v3.0.2:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-app-wealth-advisor\",\n  \"version\": \"3.0.2\",\n  \"publishedAt\": 1780326742303\n}\n\nFile v3.0.2:skill-card.md\n\n## Description: <br>\nAI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[gechengling](https://clawhub.ai/user/gechengling) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal digital banking and wealth-management teams use this skill as an advisor-assist reference for bank mobile app product matching, investment consultation scripts, financial planning prompts, and compliance-aware customer interaction. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Users may treat generated wealth-advisory guidance as real financial advice. <br>\nMitigation: Require qualified human review before using recommendations in customer-facing or regulated workflows. <br>\nRisk: Customer-profile examples and inputs may contain sensitive financial information. <br>\nMitigation: Avoid identifiable customer financial data unless the organization has proper consent, retention, and compliance controls. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/gechengling/security-app-wealth-advisor) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [text, markdown, code, guidance] <br>\n**Output Format:** [Markdown guidance with illustrative Python and compliance-checklist snippets] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Advisory-only output requiring qualified human review before real-world financial use] <br>\n\n## Skill Version(s): <br>\n3.0.2 (source: server release evidence; artifact frontmatter says 3.0.1) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nArchive v3.0.1: 3 files, 4973 bytes\n\nFiles: skill-card.md (2146b), SKILL.md (8282b), _meta.json (146b)\n\nFile v3.0.1:SKILL.md\n\n---\r\nname: Bank APP Wealth Advisor Assistant\r\nslug: bank-app-wealth-advisor\r\ndescription: AI-powered bank APP wealth advisory assistant — covers product recommendation, investment consultation, financial planning, and compliance-compliant customer interaction for bank mobile applications. Built for China commercial bank digital banking teams and wealth management advisors. Keywords: bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, China banking digital, 银行APP, 财富顾问, 智能投顾, 手机银行, 数字银行, 产品推荐, 理财推荐, 基金销售, 资产配置.\r\nversion: \"3.0.1\"\r\n---\r\n\r\n# Bank APP Wealth Advisor Assistant / 银行APP财富顾问助手\r\n\r\n\r\n### 银行监管最新动态 [2026-05-25更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 |\r\n|---------|---------|---------|\r\n| 银行监管 | 2026年Q1理财信息披露'三清'推进，财富管理话术需更新 | 投顾话术和策略模板需适配市场新环境 |\r\n| 银行监管 | 净息差压力下，银行理财产品收益率下行，投顾建议需调整 | 投顾话术和策略模板需适配市场新环境 |\r\n| 银行监管 | 2026年A股量化资金占比30%-40%，财富管理策略需关注量化冲击 | 投顾话术和策略模板需适配市场新环境 |\r\n\r\n> **数据截止**: 2026-05-25 | 来源：国家金融监督管理总局、安永Q1分析、行业公开信息\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n> **English:** AI-powered wealth advisory assistant for bank mobile applications — provides product recommendations, investment consultation, and compliance-compliant customer interaction. Built for digital banking teams.\r\n>\r\n> **中文:** 银行APP财富顾问助手——为手机银行提供产品推荐、投资咨询、合规客户交互。适用：数字银行团队、财富管理师。\r\n\r\n---\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 |\r\n|------------------|-------------|------------------------|\r\n| **APP用户粘性低** | 用户用完即走，无深度服务 | AI投顾提升个性化体验 |\r\n| **产品匹配效率低** | 人工推荐成本高 | 智能产品匹配引擎 |\r\n| **合规要求严** | 监管禁止虚假宣传 | 合规话术自动检查 |\r\n| **服务覆盖有限** | 人工客服无法7x24 | AI24小时在线解答 |\r\n| **交叉销售难** | 客户画像不完整 | 多维度客户分析 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers:** bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, financial planning, customer service\r\n\r\n**中文触发词（优先）：** 银行APP / 财富顾问 / 智能投顾 / 手机银行 / 数字银行 / 产品推荐 / 理财咨询 / 基金销售 / 资产配置 / 客户分层 / 交叉销售 / 合规话术 / 智能客服 / 风险测评 / 适当性匹配\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. Product Matching Engine / 产品匹配引擎\r\n\r\n```python\r\nclass WealthAdvisor:\r\n    \"\"\"智能财富顾问\"\"\"\r\n    \r\n    def match_products(self, customer_profile: dict, \r\n                      available_products: list) -> list:\r\n        \"\"\"\r\n        智能产品匹配\r\n        Args:\r\n            customer_profile: 客户画像\r\n            available_products: 可选产品列表\r\n        \"\"\"\r\n        # 风险匹配\r\n        risk_level_map = {\r\n            \"保守型\": [\"R1\", \"R2\"],\r\n            \"稳健型\": [\"R1\", \"R2\", \"R3\"],\r\n            \"平衡型\": [\"R2\", \"R3\", \"R4\"],\r\n            \"成长型\": [\"R3\", \"R4\", \"R5\"],\r\n            \"激进型\": [\"R4\", \"R5\"]\r\n        }\r\n        \r\n        allowed_risk = risk_level_map.get(\r\n            customer_profile.get(\"risk_preference\", \"稳健型\"), [\"R2\", \"R3\"]\r\n        )\r\n        \r\n        # 收益匹配\r\n        expected_return = customer_profile.get(\"expected_return\", 0.05)\r\n        \r\n        matched = []\r\n        for product in available_products:\r\n            # 风险等级过滤\r\n            if product[\"risk_level\"] not in allowed_risk:\r\n                continue\r\n            \r\n            # 收益率匹配\r\n            if product[\"expected_return\"] >= expected_return - 0.02:\r\n                score = self._calculate_match_score(\r\n                    customer_profile, product\r\n                )\r\n                matched.append({\r\n                    **product,\r\n                    \"match_score\": score,\r\n                    \"recommendation_reason\": self._generate_reason(\r\n                        customer_profile, product\r\n                    )\r\n                })\r\n        \r\n        return sorted(matched, key=lambda x: x[\"match_score\"], reverse=True)\r\n    \r\n    def _calculate_match_score(self, customer: dict, \r\n                               product: dict) -> float:\r\n        \"\"\"计算匹配度评分\"\"\"\r\n        score = 100\r\n        \r\n        # 期限匹配\r\n        preferred_term = customer.get(\"preferred_term\", 365)\r\n        product_term = product.get(\"term_days\", 365)\r\n        term_diff = abs(preferred_term - product_term) / 365\r\n        score -= term_diff * 10\r\n        \r\n        # 起购金额\r\n        if product.get(\"min_amount\", 0) > customer.get(\"available_fund\", 0):\r\n            score -= 30\r\n        \r\n        # 收益率\r\n        expected = customer.get(\"expected_return\", 0.05)\r\n        actual = product.get(\"expected_return\", 0)\r\n        if actual >= expected:\r\n            score += 10\r\n        else:\r\n            score -= abs(actual - expected) * 100\r\n        \r\n        return max(0, min(100, score))\r\n```\r\n\r\n### 2. Investment Consultation Scripts / 投资咨询话术\r\n\r\n```python\r\nINVESTMENT_SCRIPTS = {\r\n    \"基金购买引导\": {\r\n        \"场景\": \"客户咨询基金\",\r\n        \"话术\": \"\"\"\r\n        \"您好！根据您的风险测评结果【{risk_level}】，\r\n        我推荐您关注【{fund_name}】基金。\r\n        \r\n        这只基金的特点：\r\n        • 基金类型：{fund_type}\r\n        • 风险等级：{risk_level}\r\n        • 近一年收益：{return_1y}%\r\n        • 基金经理：{manager}（从业{years}年）\r\n        \r\n        适合您的理由：\r\n        1. {reason_1}\r\n        2. {reason_2}\r\n        3. {reason_3}\r\n        \r\n        【风险提示】基金有风险，投资需谨慎。过往业绩不代表未来表现。\r\n        请您根据自身情况谨慎决策。\"\r\n        \"\"\",\r\n        \"合规检查\": [\r\n            \"不得承诺保本\",\r\n            \"必须说明基金有风险\",\r\n            \"过往业绩仅供参考\"\r\n        ]\r\n    },\r\n    \r\n    \"资产配置建议\": {\r\n        \"场景\": \"客户有大额资金\",\r\n        \"话术\": \"\"\"\r\n        \"张先生/女士，您好！\r\n        \r\n        根据您目前的资产状况，我们建议做一个科学的资产配置：\r\n        \r\n        【保守配置】40% → 银行存款+国债\r\n        特点：安全稳健，适合保本需求\r\n        \r\n        【稳健配置】30% → 银行理财+债券基金\r\n        特点：收益稳健，波动较小\r\n        \r\n        【成长配置】20% → 混合基金+股票基金\r\n        特点：追求较高收益，承担一定风险\r\n        \r\n        【流动性】10% → 货币基金\r\n        特点：随存随取，应急备用\r\n        \r\n        这个配置方案可以帮助您分散风险，\r\n        同时实现资产的稳健增值。\"\r\n        \"\"\"\r\n    }\r\n}\r\n```\r\n\r\n### 3. Compliance Check / 合规检查\r\n\r\n```markdown\r\n## APP投顾合规检查清单\r\n\r\n### 必须包含的要素\r\n| 检查项 | 要求 |\r\n|-------|------|\r\n| 风险提示 | 必须出现\"投资有风险\" |\r\n| 收益说明 | 不得承诺保本保收益 |\r\n| 历史业绩 | 必须注明\"仅供参考\" |\r\n| 适当性 | 必须匹配客户风险等级 |\r\n| 产品揭示 | 必须包含产品说明书链接 |\r\n\r\n### 禁止用语\r\n| 禁止 | 替代 |\r\n|-----|------|\r\n| \"保本\" | \"相对稳健\" |\r\n| \"稳赚不赔\" | \"追求稳健收益\" |\r\n| \"最低收益X%\" | \"历史平均收益X%\" |\r\n| \"100%安全\" | \"风险可控\" |\r\n```\r\n\r\n---\r\n\r\n## Disclaimer\r\n\r\nThis skill provides wealth advisory tools for educational purposes. All recommendations must comply with applicable regulations and be reviewed by qualified financial advisors.\n\nFile v3.0.1:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-app-wealth-advisor\",\n  \"version\": \"3.0.1\",\n  \"publishedAt\": 1779679952410\n}\n\nFile v3.0.1:skill-card.md\n\n## Description: <br>\nAI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[gechengling](https://clawhub.ai/user/gechengling) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nDigital banking teams and wealth management advisors use this skill to draft mobile banking wealth-advice flows, product matching logic, investment consultation scripts, financial planning guidance, and compliance review checklists. <br>\n\n### Deployment Geography for Use: <br>\nChina <br>\n\n## Known Risks and Mitigations: <br>\nRisk: The skill addresses regulated banking wealth advice and includes sample wording that may imply principal protection or overly broad suitability. <br>\nMitigation: Review all recommendation scripts with qualified financial and compliance reviewers, remove guarantee-adjacent wording, and align advice with applicable banking and investment regulations. <br>\nRisk: Broad trigger language could activate the skill in banking conversations that are not explicit investment-advice requests. <br>\nMitigation: Tighten activation criteria to explicit wealth-advice intents and route ambiguous or high-stakes requests to qualified advisors. <br>\n\n\n## Reference(s): <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [text, markdown, code, guidance] <br>\n**Output Format:** [Markdown with explanatory text, checklists, and illustrative Python code blocks] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Outputs may include financial-advice scripts and compliance checklist content that require qualified review before customer-facing use.] <br>\n\n## Skill Version(s): <br>\n3.0.1 (source: server release metadata and frontmatter) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nArchive v2.0.0: 2 files, 3464 bytes\n\nFiles: SKILL.md (7505b), _meta.json (146b)\n\nFile v2.0.0:SKILL.md\n\n---\r\nname: Bank APP Wealth Advisor Assistant\r\nslug: bank-app-wealth-advisor\r\ndescription: AI-powered bank APP wealth advisory assistant — covers product recommendation, investment consultation, financial planning, and compliance-compliant customer interaction for bank mobile applications. Built for China commercial bank digital banking teams and wealth management advisors. Keywords: bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, China banking digital, 银行APP, 财富顾问, 智能投顾, 手机银行, 数字银行, 产品推荐, 理财推荐, 基金销售, 资产配置.\r\nversion: 1.0.0\r\n---\r\n\r\n# Bank APP Wealth Advisor Assistant / 银行APP财富顾问助手\r\n\r\n> **English:** AI-powered wealth advisory assistant for bank mobile applications — provides product recommendations, investment consultation, and compliance-compliant customer interaction. Built for digital banking teams.\r\n>\r\n> **中文:** 银行APP财富顾问助手——为手机银行提供产品推荐、投资咨询、合规客户交互。适用：数字银行团队、财富管理师。\r\n\r\n---\r\n\r\n## Industry Pain Points / 行业痛点\r\n\r\n| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 |\r\n|------------------|-------------|------------------------|\r\n| **APP用户粘性低** | 用户用完即走，无深度服务 | AI投顾提升个性化体验 |\r\n| **产品匹配效率低** | 人工推荐成本高 | 智能产品匹配引擎 |\r\n| **合规要求严** | 监管禁止虚假宣传 | 合规话术自动检查 |\r\n| **服务覆盖有限** | 人工客服无法7x24 | AI24小时在线解答 |\r\n| **交叉销售难** | 客户画像不完整 | 多维度客户分析 |\r\n\r\n---\r\n\r\n## Trigger Keywords / 触发关键词\r\n\r\n**English Triggers:** bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, financial planning, customer service\r\n\r\n**中文触发词（优先）：** 银行APP / 财富顾问 / 智能投顾 / 手机银行 / 数字银行 / 产品推荐 / 理财咨询 / 基金销售 / 资产配置 / 客户分层 / 交叉销售 / 合规话术 / 智能客服 / 风险测评 / 适当性匹配\r\n\r\n---\r\n\r\n## Core Capabilities / 核心能力\r\n\r\n### 1. Product Matching Engine / 产品匹配引擎\r\n\r\n```python\r\nclass WealthAdvisor:\r\n    \"\"\"智能财富顾问\"\"\"\r\n    \r\n    def match_products(self, customer_profile: dict, \r\n                      available_products: list) -> list:\r\n        \"\"\"\r\n        智能产品匹配\r\n        Args:\r\n            customer_profile: 客户画像\r\n            available_products: 可选产品列表\r\n        \"\"\"\r\n        # 风险匹配\r\n        risk_level_map = {\r\n            \"保守型\": [\"R1\", \"R2\"],\r\n            \"稳健型\": [\"R1\", \"R2\", \"R3\"],\r\n            \"平衡型\": [\"R2\", \"R3\", \"R4\"],\r\n            \"成长型\": [\"R3\", \"R4\", \"R5\"],\r\n            \"激进型\": [\"R4\", \"R5\"]\r\n        }\r\n        \r\n        allowed_risk = risk_level_map.get(\r\n            customer_profile.get(\"risk_preference\", \"稳健型\"), [\"R2\", \"R3\"]\r\n        )\r\n        \r\n        # 收益匹配\r\n        expected_return = customer_profile.get(\"expected_return\", 0.05)\r\n        \r\n        matched = []\r\n        for product in available_products:\r\n            # 风险等级过滤\r\n            if product[\"risk_level\"] not in allowed_risk:\r\n                continue\r\n            \r\n            # 收益率匹配\r\n            if product[\"expected_return\"] >= expected_return - 0.02:\r\n                score = self._calculate_match_score(\r\n                    customer_profile, product\r\n                )\r\n                matched.append({\r\n                    **product,\r\n                    \"match_score\": score,\r\n                    \"recommendation_reason\": self._generate_reason(\r\n                        customer_profile, product\r\n                    )\r\n                })\r\n        \r\n        return sorted(matched, key=lambda x: x[\"match_score\"], reverse=True)\r\n    \r\n    def _calculate_match_score(self, customer: dict, \r\n                               product: dict) -> float:\r\n        \"\"\"计算匹配度评分\"\"\"\r\n        score = 100\r\n        \r\n        # 期限匹配\r\n        preferred_term = customer.get(\"preferred_term\", 365)\r\n        product_term = product.get(\"term_days\", 365)\r\n        term_diff = abs(preferred_term - product_term) / 365\r\n        score -= term_diff * 10\r\n        \r\n        # 起购金额\r\n        if product.get(\"min_amount\", 0) > customer.get(\"available_fund\", 0):\r\n            score -= 30\r\n        \r\n        # 收益率\r\n        expected = customer.get(\"expected_return\", 0.05)\r\n        actual = product.get(\"expected_return\", 0)\r\n        if actual >= expected:\r\n            score += 10\r\n        else:\r\n            score -= abs(actual - expected) * 100\r\n        \r\n        return max(0, min(100, score))\r\n```\r\n\r\n### 2. Investment Consultation Scripts / 投资咨询话术\r\n\r\n```python\r\nINVESTMENT_SCRIPTS = {\r\n    \"基金购买引导\": {\r\n        \"场景\": \"客户咨询基金\",\r\n        \"话术\": \"\"\"\r\n        \"您好！根据您的风险测评结果【{risk_level}】，\r\n        我推荐您关注【{fund_name}】基金。\r\n        \r\n        这只基金的特点：\r\n        • 基金类型：{fund_type}\r\n        • 风险等级：{risk_level}\r\n        • 近一年收益：{return_1y}%\r\n        • 基金经理：{manager}（从业{years}年）\r\n        \r\n        适合您的理由：\r\n        1. {reason_1}\r\n        2. {reason_2}\r\n        3. {reason_3}\r\n        \r\n        【风险提示】基金有风险，投资需谨慎。过往业绩不代表未来表现。\r\n        请您根据自身情况谨慎决策。\"\r\n        \"\"\",\r\n        \"合规检查\": [\r\n            \"不得承诺保本\",\r\n            \"必须说明基金有风险\",\r\n            \"过往业绩仅供参考\"\r\n        ]\r\n    },\r\n    \r\n    \"资产配置建议\": {\r\n        \"场景\": \"客户有大额资金\",\r\n        \"话术\": \"\"\"\r\n        \"张先生/女士，您好！\r\n        \r\n        根据您目前的资产状况，我们建议做一个科学的资产配置：\r\n        \r\n        【保守配置】40% → 银行存款+国债\r\n        特点：安全稳健，适合保本需求\r\n        \r\n        【稳健配置】30% → 银行理财+债券基金\r\n        特点：收益稳健，波动较小\r\n        \r\n        【成长配置】20% → 混合基金+股票基金\r\n        特点：追求较高收益，承担一定风险\r\n        \r\n        【流动性】10% → 货币基金\r\n        特点：随存随取，应急备用\r\n        \r\n        这个配置方案可以帮助您分散风险，\r\n        同时实现资产的稳健增值。\"\r\n        \"\"\"\r\n    }\r\n}\r\n```\r\n\r\n### 3. Compliance Check / 合规检查\r\n\r\n```markdown\r\n## APP投顾合规检查清单\r\n\r\n### 必须包含的要素\r\n| 检查项 | 要求 |\r\n|-------|------|\r\n| 风险提示 | 必须出现\"投资有风险\" |\r\n| 收益说明 | 不得承诺保本保收益 |\r\n| 历史业绩 | 必须注明\"仅供参考\" |\r\n| 适当性 | 必须匹配客户风险等级 |\r\n| 产品揭示 | 必须包含产品说明书链接 |\r\n\r\n### 禁止用语\r\n| 禁止 | 替代 |\r\n|-----|------|\r\n| \"保本\" | \"相对稳健\" |\r\n| \"稳赚不赔\" | \"追求稳健收益\" |\r\n| \"最低收益X%\" | \"历史平均收益X%\" |\r\n| \"100%安全\" | \"风险可控\" |\r\n```\r\n\r\n---\r\n\r\n## Disclaimer\r\n\r\nThis skill provides wealth advisory tools for educational purposes. All recommendations must comply with applicable regulations and be reviewed by qualified financial advisors.\n\nFile v2.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-app-wealth-advisor\",\n  \"version\": \"2.0.0\",\n  \"publishedAt\": 1778509844973\n}","readmeExcerpt":"Skill: Security App Wealth Advisor Owner: gechengling Summary: AI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction. Tags: latest:3.0.3, security-app-wealth-advisor:3.0.3 Version history: v3.0.3 | 2026-09-14T06:10:31.802Z | user v3.0.3: 修正 no-executable-code 与实际含示例代码的矛盾声明，补数据最小化声明；监管动态更新至 2026-09-14（适当性持续匹配、AI 对客输","codeSnippets":[],"executableExamples":[],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\r\nname: Bank APP Wealth Advisor Assistant\r\nslug: bank-app-wealth-advisor\r\ndescription: AI-powered bank APP wealth advisory assistant — covers product recommendation, investment consultation, financial planning, and compliance-compliant customer interaction for bank mobile applications. Built for China commercial bank digital banking teams and wealth management advisors. Keywords: bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, China banking digital, 银行APP, 财富顾问, 智能投顾, 手机银行, 数字银行, 产品推荐, 理财推荐, 基金销售, 资产配置.\r\nversion: \"3.0.3\"\r\n\r\ncapabilities:\r\n  - educational-reference\r\n  - advisory-only\r\n  - requires-human-review\r\n  - illustrative-code-snippets\r\n---\r\n\r\n# Bank APP Wealth Advisor Assistant / 银行APP财富顾问助手\r\n> **⚠️ SECURITY NOTICE**\r\n> - **Type:** Educational reference / analytical framework ONLY\r\n> - **Code in this document is illustrative.** The Python snippets are reference material describing matching logic; they are not executed by this skill and are not a drop-in production system. Adapt and test them in your own environment.\r\n> - **This skill does not itself read or write files, call external services, or persist data.** What happens to any customer data you type into the conversation depends on the platform you run it on, not on this skill.\r\n> - **Customer profiles are sensitive.** Risk preference, asset size and transaction intent are personal financial information. Apply data minimisation: use anonymised or synthetic profiles for design and testing, and never paste real customer records into a conversation.\r\n> - **All outputs require human review before real-world application**\r\n> - **NOT financial, legal, or insurance advice** — no output from this skill may be presented to a customer as a personalised recommendation without review by a qualified advisor\r\n\r\n\r\n\r\n\r\n### 银行监管最新动态 [2026-09-14更新]\r\n\r\n| 动态类型 | 内容摘要 | 影响范围 | 对应话术/系统动作 |\r\n|---------|---------|---------|-----------------|\r\n| 银行监管 | 2026年Q1理财信息披露'三清'推进，财富管理话术需更新 | 投顾话术和策略模板需适配市场新环境 | 业绩展示须同时给出比较基准与区间 |\r\n| 银行监管 | 净息差压力下，银行理财产品收益率下行，投顾建议需调整 | 投顾话术和策略模板需适配市场新环境 | 弱化收益承诺，强化流动性与期限匹配 |\r\n| 银行监管 | 2026年A股量化资金占比30%-40%，财富管理策略需关注量化冲击 | 投顾话术和策略模板需适配市场新环境 | 权益类推荐需提示波动放大风险 |\r\n| 新增·适当性管理 | 投资者适当性管理的持续细化：风险测评有效性、重复购买匹配、超风险购买的特别确认 | 推荐引擎与前端流程均需改造 | 超风险匹配必须阻断或走特别确认流程 |\r\n| 新增·AI应用合规 | 银行业人工智能应用的安全开发与人工复核要求下沉为机构制度 | 智能投顾类功能需可解释、可追溯 | 推荐理由需可追溯到具体字段与规则 |\r\n| 新增·可回溯 | 线上销售与推荐行为的可回溯要求扩展至 APP 端 | 推荐记录需留痕 | 每次推荐保存版本、规则与依据 |\r\n\r\n**新动态（截至 2026-09-14）：**\r\n- **适当性匹配从\"一次测评\"走向\"持续匹配\"**：监管与行业实践均强调风险测评并非一次性动作，产品风险等级与客户风险承受能力的匹配需在每次推荐时校验，超风险购买须有明确提示与客户确认。对推荐引擎的含义是：匹配逻辑必须输出\"为什么匹配\"的可解释依据，而不是只给一个排序结果。\r\n- **AI 生成内容的对客使用受严格约束**：智能投顾场景中，AI 输出的对客表述普遍要求\"生成—复核—留痕\"三步，且不得把模型输出直接作为个性化投资建议推送。本 Skill 的话术模板应始终定位为供顾问参考的草稿。\r\n- **业绩展示口径趋严**：展示历史业绩时普遍要求同时呈现比较基准、完整区间与风险指标，避免只展示表现最好的一段。\r\n- 以上为公开信息综述，**具体条文与执行口径以国家金融监督管理总局、中国证监会、中国银行业协会及所在机构合规部门官方最新发布为准**。\r\n\r\n> **数据截止**: 2026-09-14 | 来源：国家金融监督管理总局、安永Q1分析、行业公开信息\r\n> **声明**: 以上动态供参考，具体以官方最新发布为准\r\n\r\n> **English:** AI-powered wealth advisory assistant for"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn74e704j3ygjcygnpf02rdvd185js13\",\n  \"slug\": \"security-app-wealth-advisor\",\n  \"version\": \"3.0.3\",\n  \"publishedAt\": 1789366231802\n}"},{"path":"skill-card.md","content":"## Description:\n\nAI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[gechengling](https://clawhub.ai/user/gechengling)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDigital banking teams, wealth management advisors, and compliance reviewers use this skill to draft bank mobile app wealth-advisory product matching logic, customer-facing advisory scripts, and compliance review checklists. The material is a drafting and design reference that requires qualified human review before customer-facing use.\n\n### Deployment Geography for Use:\n\nChina\n\n## Known Risks and Mitigations:\n\nRisk: The skill's examples could lead to unsuitable or misleading financial recommendations if reused without strong human compliance review.\n\nMitigation: Use outputs only as drafting and design references, require review by qualified compliance and financial-advisory staff, and do not push generated recommendations directly to customers.\n\nRisk: Customer profiles may include sensitive personal financial information.\n\nMitigation: Use anonymized or synthetic profiles for design and testing, avoid pasting real customer records into the skill, and follow the institution's data minimization, encryption, and retention controls.\n\nRisk: Illustrative code and scripts are not a production recommendation engine.\n\nMitigation: Do not reuse snippets verbatim in production; adapt, test, and validate suitability checks, risk blocking, traceability, and recordkeeping in the deployment environment.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/gechengling/skills/security-app-wealth-advisor)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Guidance]\n\n**Output Format:** [Markdown with illustrative Python and checklist snippets]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Outputs are advisory drafts and reference examples that require compliance, security, and qualified financial-advisor review before real-world use.]\n\n## Skill Version(s):\n\n3.0.3 (source: frontmatter and server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"AI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction. Skill: Security App Wealth Advisor Owner: gechengling Summary: AI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction. 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