feat: 初始提交 - 科创企业特有风险的识别与管理 (数智风控系统)

risk_engine/risk_scorer.py

@@ -0,0 +1,148 @@
+# -*- coding: utf-8 -*-
+"""
+六维风险评分器
+整合所有数据源和分析结果，生成结构化六维风险画像
+"""
+import logging
+from typing import Optional
+
+logger = logging.getLogger(__name__)
+
+
+# 风险等级映射
+RISK_LEVELS = {
+    (0, 30): {"level": "低", "color": "#4CAF50", "emoji": "🟢"},
+    (30, 50): {"level": "中低", "color": "#8BC34A", "emoji": "🟡"},
+    (50, 70): {"level": "中高", "color": "#FF9800", "emoji": "🟠"},
+    (70, 90): {"level": "高", "color": "#F44336", "emoji": "🔴"},
+    (90, 101): {"level": "极高", "color": "#B71C1C", "emoji": "⛔"},
+}
+
+
+def get_risk_level(score: int) -> dict:
+    """根据分数获取风险等级详情"""
+    for (low, high), info in RISK_LEVELS.items():
+        if low <= score < high:
+            return info
+    return {"level": "未知", "color": "#9E9E9E", "emoji": "❓"}
+
+
+def calculate_six_dimension_scores(company_data: dict) -> dict:
+    """
+    基于企业数据直接计算六维风险评分（不依赖 LLM）
+    用于快速预览和规则引擎降级场景
+    """
+    financials = company_data.get("financials", {})
+    compliance = company_data.get("compliance", {})
+    tech_route = company_data.get("tech_route", {})
+    personnel = company_data.get("core_tech_personnel", [])
+    supply_chain = company_data.get("supply_chain", {})
+
+    scores = {}
+
+    # 1. 技术路线颠覆风险
+    competing = len(tech_route.get("competing_techs", []))
+    moat = tech_route.get("tech_moat", "")
+    tech_score = min(25 + competing * 15, 85)
+    if "差距" in moat or "受制" in moat or "威胁" in moat:
+        tech_score = min(tech_score + 15, 95)
+    if "领先" in moat or "第一" in moat:
+        tech_score = max(tech_score - 10, 10)
+    scores["tech_disruption"] = tech_score
+
+    # 2. 核心人员流失风险
+    departed = [p for p in personnel if "离职" in p.get("status", "")]
+    high_imp = [p for p in personnel if p.get("importance") == "极高"]
+    if departed:
+        scores["talent_loss"] = 80
+    elif len(high_imp) <= 1 and len(personnel) <= 2:
+        scores["talent_loss"] = 55
+    else:
+        scores["talent_loss"] = 25
+
+    # 3. 算法/数据合规风险
+    algo_status = compliance.get("algo_filing_status", "")
+    data_risk = compliance.get("data_export_risk", "低")
+    algo_score = 20
+    if "未" in algo_status:
+        algo_score = 75
+    elif data_risk == "高":
+        algo_score = 65
+    elif data_risk == "中":
+        algo_score = 40
+    elif "已备案" in algo_status:
+        algo_score = 15
+    scores["algo_compliance"] = algo_score
+
+    # 4. 地缘政治/出口管制风险
+    entity_status = compliance.get("entity_list_status", "")
+    if "被列入" in entity_status:
+        scores["geopolitical"] = 92
+    elif supply_chain.get("supplier_concentration_risk") == "极高":
+        scores["geopolitical"] = 68
+    elif supply_chain.get("supplier_concentration_risk") == "高":
+        scores["geopolitical"] = 50
+    else:
+        scores["geopolitical"] = 18
+
+    # 5. 研发资本化操纵风险
+    cap_rate = financials.get("rd_capitalization_rate", 0)
+    if cap_rate >= 0.4:
+        scores["rd_capitalization"] = 90
+    elif cap_rate >= 0.3:
+        scores["rd_capitalization"] = 72
+    elif cap_rate >= 0.15:
+        scores["rd_capitalization"] = 48
+    elif cap_rate > 0:
+        scores["rd_capitalization"] = 25
+    else:
+        scores["rd_capitalization"] = 10
+
+    # 6. 客户/供应商集中风险
+    cust_ratio = financials.get("top5_customer_ratio", 0)
+    supp_ratio = financials.get("top5_supplier_ratio", 0)
+    max_conc = max(cust_ratio, supp_ratio)
+    if max_conc >= 0.8:
+        scores["concentration"] = 88
+    elif max_conc >= 0.6:
+        scores["concentration"] = 68
+    elif max_conc >= 0.4:
+        scores["concentration"] = 42
+    else:
+        scores["concentration"] = 18
+
+    # 加权综合
+    weights = {
+        "tech_disruption": 0.20,
+        "talent_loss": 0.15,
+        "algo_compliance": 0.15,
+        "geopolitical": 0.20,
+        "rd_capitalization": 0.15,
+        "concentration": 0.15,
+    }
+    comprehensive = int(sum(scores[k] * weights[k] for k in scores))
+
+    # 维度中文名映射
+    dim_names = {
+        "tech_disruption": "技术路线颠覆",
+        "talent_loss": "核心人员流失",
+        "algo_compliance": "算法/数据合规",
+        "geopolitical": "地缘政治/出口管制",
+        "rd_capitalization": "研发资本化操纵",
+        "concentration": "客户/供应商集中",
+    }
+
+    return {
+        "scores": scores,
+        "comprehensive_score": comprehensive,
+        "risk_level": get_risk_level(comprehensive),
+        "dimension_details": {
+            k: {
+                "name": dim_names[k],
+                "score": v,
+                "level": get_risk_level(v),
+                "weight": weights[k],
+            }
+            for k, v in scores.items()
+        },
+    }