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AI-powered wealth advisor for bank mobile apps offering personalized product matching, investment consultation, and compliance-compliant customer interaction.
---
name: Bank APP Wealth Advisor Assistant
slug: bank-app-wealth-advisor
description: 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.
version: "3.0.1"
capabilities:
- educational-reference
- advisory-only
- requires-human-review
- no-executable-code
---
# Bank APP Wealth Advisor Assistant / 银行APP财富顾问助手
> **⚠️ SECURITY NOTICE**
> - **Type:** Educational reference / analytical framework ONLY
> - **No executable code, scripts, or binaries included**
> - **No persistent storage, network calls, or background execution**
> - **No credential collection, PII processing, or system access**
> - **All outputs require human review before real-world application**
> - **NOT financial, legal, or insurance advice**
### 银行监管最新动态 [2026-05-25更新]
| 动态类型 | 内容摘要 | 影响范围 |
|---------|---------|---------|
| 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 |
| 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 |
| 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 |
> **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
> **声明**: 以上动态供参考，具体以官方最新发布为准
> **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.
>
> **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。
---
## Industry Pain Points / 行业痛点
| Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 |
|------------------|-------------|------------------------|
| **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 |
| **产品匹配效率低** | 人工推荐成本高 | 智能产品匹配引擎 |
| **合规要求严** | 监管禁止虚假宣传 | 合规话术自动检查 |
| **服务覆盖有限** | 人工客服无法7x24 | AI24小时在线解答 |
| **交叉销售难** | 客户画像不完整 | 多维度客户分析 |
---
## Trigger Keywords / 触发关键词
**English Triggers:** bank APP, wealth advisor, digital banking, mobile banking, AI advisor, product recommendation, financial planning, customer service
**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
---
## Core Capabilities / 核心能力
### 1. Product Matching Engine / 产品匹配引擎
```python
class WealthAdvisor:
"""智能财富顾问"""
def match_products(self, customer_profile: dict,
available_products: list) -> list:
"""
智能产品匹配
Args:
customer_profile: 客户画像
available_products: 可选产品列表
"""
# 风险匹配
risk_level_map = {
"保守型": ["R1", "R2"],
"稳健型": ["R1", "R2", "R3"],
"平衡型": ["R2", "R3", "R4"],
"成长型": ["R3", "R4", "R5"],
"激进型": ["R4", "R5"]
}
allowed_risk = risk_level_map.get(
customer_profile.get("risk_preference", "稳健型"), ["R2", "R3"]
)
# 收益匹配
expected_return = customer_profile.get("expected_return", 0.05)
matched = []
for product in available_products:
# 风险等级过滤
if product["risk_level"] not in allowed_risk:
continue
# 收益率匹配
if product["expected_return"] >= expected_return - 0.02:
score = self._calculate_match_score(
customer_profile, product
)
matched.append({
**product,
"match_score": score,
"recommendation_reason": self._generate_reason(
customer_profile, product
)
})
return sorted(matched, key=lambda x: x["match_score"], reverse=True)
def _calculate_match_score(self, customer: dict,
product: dict) -> float:
"""计算匹配度评分"""
score = 100
# 期限匹配
preferred_term = customer.get("preferred_term", 365)
product_term = product.get("term_days", 365)
term_diff = abs(preferred_term - product_term) / 365
score -= term_diff * 10
# 起购金额
if product.get("min_amount", 0) > customer.get("available_fund", 0):
score -= 30
# 收益率
expected = customer.get("expected_return", 0.05)
actual = product.get("expected_return", 0)
if actual >= expected:
score += 10
else:
score -= abs(actual - expected) * 100
return max(0, min(100, score))
```
### 2. Investment Consultation Scripts / 投资咨询话术
```python
INVESTMENT_SCRIPTS = {
"基金购买引导": {
"场景": "客户咨询基金",
"话术": """
"您好！根据您的风险测评结果【{risk_level}】，
我推荐您关注【{fund_name}】基金。
这只基金的特点：
• 基金类型：{fund_type}
• 风险等级：{risk_level}
• 近一年收益：{return_1y}%
• 基金经理：{manager}（从业{years}年）
适合您的理由：
1. {reason_1}
2. {reason_2}
3. {reason_3}
【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。
请您根据自身情况谨慎决策。"
""",
"合规检查": [
"不得承诺保本",
"必须说明基金有风险",
"过往业绩仅供参考"
]
},
"资产配置建议": {
"场景": "客户有大额资金",
"话术": """
"张先生/女士，您好！
根据您目前的资产状况，我们建议做一个科学的资产配置：
【保守配置】40% → 银行存款+国债
特点：安全稳健，适合保本需求
【稳健配置】30% → 银行理财+债券基金
特点：收益稳健，波动较小
【成长配置】20% → 混合基金+股票基金
特点：追求较高收益，承担一定风险
【流动性】10% → 货币基金
特点：随存随取，应急备用
这个配置方案可以帮助您分散风险，
同时实现资产的稳健增值。"
"""
}
}
```
### 3. Compliance Check / 合规检查
```markdown
## APP投顾合规检查清单
### 必须包含的要素
| 检查项 | 要求 |
|-------|------|
| 风险提示 | 必须出现"投资有风险" |
| 收益说明 | 不得承诺保本保收益 |
| 历史业绩 | 必须注明"仅供参考" |
| 适当性 | 必须匹配客户风险等级 |
| 产品揭示 | 必须包含产品说明书链接 |
### 禁止用语
| 禁止 | 替代 |
|-----|------|
| "保本" | "相对稳健" |
| "稳赚不赔" | "追求稳健收益" |
| "最低收益X%" | "历史平均收益X%" |
| "100%安全" | "风险可控" |
```
---
## Disclaimer
This skill provides wealth advisory tools for educational purposes. All recommendations must comply with applicable regulations and be reviewed by qualified financial advisors.
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