185 lines
5.9 KiB
Python
185 lines
5.9 KiB
Python
# -*- coding: utf-8 -*-
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"""
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动态保险定价模型
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基于精算原理，结合六维风险评分实现"千企千面"费率计算
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"""
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import logging
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import sys
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import os
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# 将项目根目录添加到 Python 路径
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from config import INSURANCE_PRODUCTS
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logger = logging.getLogger(__name__)
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# 行业风险系数
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INDUSTRY_RISK_FACTORS = {
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"芯片": 1.35, # 地缘风险+技术迭代双高
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"AI": 1.30, # 合规风险+技术竞争
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"软件": 1.05, # 相对成熟
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"医疗器械": 0.95, # 技术壁垒高但风险较稳
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"新能源": 1.15, # 技术路线之争+贸易摩擦
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"消费电子": 1.10, # 供应链风险
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}
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# 企业规模折扣（大企业风险分散能力更强）
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SCALE_DISCOUNT = {
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"超大型": 0.85, # 营收 > 500亿
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"大型": 0.90, # 100-500亿
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"中型": 1.00, # 10-100亿
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"小型": 1.15, # 1-10亿
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"微型": 1.30, # < 1亿
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}
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def get_enterprise_scale(revenue: float) -> str:
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"""根据营收判断企业规模"""
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if revenue >= 50_000_000_000:
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return "超大型"
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elif revenue >= 10_000_000_000:
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return "大型"
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elif revenue >= 1_000_000_000:
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return "中型"
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elif revenue >= 100_000_000:
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return "小型"
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return "微型"
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def calculate_premium(
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product_key: str,
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comprehensive_risk_score: int,
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six_dimension_scores: dict,
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sector: str = "",
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revenue: float = 0,
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) -> dict:
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"""
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动态费率计算器
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定价公式：
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实际保费 = 基础保费 × 风险系数 × 行业调整 × 规模折扣
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风险系数由综合评分决定（分段线性）：
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- [0, 30) → 0.7 ~ 0.9（优质折扣）
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- [30, 50) → 0.9 ~ 1.2（标准浮动）
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- [50, 70) → 1.2 ~ 1.8（风险上浮）
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- [70, 90) → 1.8 ~ 2.5（惩罚性费率）
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- [90,100] → 拒保或附加极高免赔额
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"""
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product = INSURANCE_PRODUCTS.get(product_key)
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if not product:
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return {"error": f"未知保险产品: {product_key}"}
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base_premium = product["base_premium"]
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base_coverage = product["base_coverage"]
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# 1. 计算风险系数
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risk_multiplier = _calculate_risk_multiplier(comprehensive_risk_score)
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# 2. 行业调整系数
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industry_factor = INDUSTRY_RISK_FACTORS.get(sector, 1.0)
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# 3. 规模折扣
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scale = get_enterprise_scale(revenue)
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scale_factor = SCALE_DISCOUNT[scale]
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# 4. 特定险种的维度调整
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dimension_adjustment = _get_dimension_adjustment(product_key, six_dimension_scores)
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# 5. 最终保费
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final_premium = base_premium * risk_multiplier * industry_factor * scale_factor * dimension_adjustment
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# 6. 核保条件
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deductible_rate = _calculate_deductible(comprehensive_risk_score)
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adjusted_coverage = base_coverage * (1.0 if comprehensive_risk_score < 70 else 0.7)
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return {
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"product_name": product["name"],
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"product_key": product_key,
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"base_premium": base_premium,
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"base_coverage": base_coverage,
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"risk_multiplier": round(risk_multiplier, 3),
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"industry_factor": round(industry_factor, 3),
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"scale_factor": round(scale_factor, 3),
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"scale_label": scale,
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"dimension_adjustment": round(dimension_adjustment, 3),
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"final_premium": round(final_premium, 2),
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"adjusted_coverage": round(adjusted_coverage, 2),
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"deductible_rate": round(deductible_rate, 3),
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"deductible_amount": round(adjusted_coverage * deductible_rate, 2),
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"comprehensive_risk_score": comprehensive_risk_score,
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"is_insurable": comprehensive_risk_score < 90,
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"pricing_breakdown": (
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f"¥{base_premium:,.0f} × {risk_multiplier:.2f}(风险) "
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f"× {industry_factor:.2f}(行业) × {scale_factor:.2f}(规模) "
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f"× {dimension_adjustment:.2f}(维度) = ¥{final_premium:,.0f}"
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),
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}
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def _calculate_risk_multiplier(score: int) -> float:
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"""分段线性风险系数计算"""
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if score < 30:
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return 0.7 + (score / 30) * 0.2 # 0.7 ~ 0.9
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elif score < 50:
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return 0.9 + ((score - 30) / 20) * 0.3 # 0.9 ~ 1.2
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elif score < 70:
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return 1.2 + ((score - 50) / 20) * 0.6 # 1.2 ~ 1.8
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elif score < 90:
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return 1.8 + ((score - 70) / 20) * 0.7 # 1.8 ~ 2.5
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else:
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return 3.0 # 拒保级别
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def _get_dimension_adjustment(product_key: str, scores: dict) -> float:
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"""针对特定险种，根据相关维度得分进行微调"""
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if product_key == "ip_lawsuit":
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# 知识产权被诉险：重点看技术路线和专利
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tech_score = scores.get("tech_disruption", 50)
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return 0.8 + (tech_score / 100) * 0.4 # 0.8 ~ 1.2
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elif product_key == "exec_departure":
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# 高管离职险：重点看人员流失风险
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talent_score = scores.get("talent_loss", 50)
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return 0.7 + (talent_score / 100) * 0.6 # 0.7 ~ 1.3
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elif product_key == "data_compliance":
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# 数据合规险：重点看合规风险
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compliance_score = scores.get("algo_compliance", 50)
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return 0.8 + (compliance_score / 100) * 0.4 # 0.8 ~ 1.2
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return 1.0
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def _calculate_deductible(score: int) -> float:
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"""计算免赔率"""
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if score < 30:
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return 0.05 # 5%
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elif score < 50:
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return 0.10 # 10%
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elif score < 70:
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return 0.15 # 15%
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elif score < 90:
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return 0.25 # 25%
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else:
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return 0.50 # 50%（惩罚性高免赔）
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def calculate_all_products(
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comprehensive_risk_score: int,
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six_dimension_scores: dict,
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sector: str = "",
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revenue: float = 0,
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) -> list:
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"""计算所有险种的保费"""
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results = []
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for product_key in INSURANCE_PRODUCTS:
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result = calculate_premium(
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product_key, comprehensive_risk_score,
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six_dimension_scores, sector, revenue,
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)
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results.append(result)
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return results
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