落地第十五条豁免额度校验；登记三处业务裁定
一、第十五条豁免规则（docs/25 第七节 #2，业务裁定：实现） 政策原文：C3→R4 签署风险揭示书后**可买**，但单只 R4 持仓不超过总资产 20%； C4→R5 同理，上限 10%。越级购买本身不是违规，超出额度才是 —— 原先扫描侧只看 "留痕是否齐全"，于是"签了字但买超额度"这种明确违规没有预警；研判侧也把豁免的 前提条件（留痕齐全）当成了结论，直接判"疑似误报"。 - 扫描侧：新增 EXEMPTION_LIMITS 与 RiskRuleEngine._exemption_state，核算 "单只持仓 / 总资产"并写进证据快照；触发条件改为 gap > 0 and (missing_trace or 超出额度)。 - 研判侧：_assess_rw007 先判额度再判留痕。超限 → 证据支持风险；留痕齐全且在额度 内 → 疑似误报；留痕齐全但快照缺总资产/持仓 → 继续复核。 数据前提（tools/probe_exemption_data.py，证据见 docs/evidence/exemption-data-probe.json）： 库内 fin_customer_profile 仅 1 行且 total_asset = 0.00、fin_holding 0 行、无任何申购 交易 —— 这条规则当前不会被触发，与 behavior_score 同源（画像与持仓由本项目之外的 流程写入）。因此刻意不把"算不出来"当成"超限"：拿 0 去算会让每一笔 C3→R4 都变成违规， 豁免规则反倒成了误报源。上游把数据写入后无需再改代码即可生效。 二、三处业务裁定（此前挂在"待裁定"） - 模型网关 chat + tools 入口：本轮不补，按基座能力缺口记录。它要贯穿 ModelGateway → … → BaseAgent 整条链路，属公共契约变更，演示联调期影响面大于收益。 - exclude（关闭误报）是否必须先"调查中"：保持现状，不加门禁。 - 政策冲突：以第十四条 C ≥ R 为准；客服侧 check_suitability 复核后确认本来就按 C ≥ R 实现，无需改动。 三、其他 - 新增 tests/unit/service/test_risk_judgement_rw007.py（6 例）与扫描侧 4 例。 - 风控文档 03/05 同步 RW-007 的豁免额度条件与研判口径。
This commit is contained in:
@@ -203,8 +203,38 @@ def _assess_rw007(detail: dict[str, Any]) -> dict[str, Any]:
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["核对预警生成时和当前测评记录是否发生变更。"],
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)
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# 第十五条豁免规则：C3→R4、C4→R5 是**允许**的越级购买，前提是签署风险揭示书
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# 且单只持仓不超过总资产的 20% / 10%。所以"留痕齐全"只是豁免成立的一半条件，
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# 另一半是额度 —— 只判留痕会把"签了字但买超了额度"的违规判成误报。
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snapshot = _mapping(detail.get("evidence_snapshot"))
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limit = _decimal(snapshot.get("exemption_limit"))
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ratio = _decimal(snapshot.get("exemption_ratio"))
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if limit is not None and ratio is not None and ratio > limit:
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return _assessment(
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VERDICT_RISK_SUPPORTED,
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"高",
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[
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f"客户等级与产品等级相差 {level_gap} 级，属第十五条可豁免情形。",
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f"但单只持仓占比 {ratio:.2%} 已超过豁免上限 {limit:.0%}。",
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],
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["核实风险揭示书签署情况，并查明持仓占比突破豁免额度的原因。"],
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)
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missing_traces = _missing_traces(product, work_order)
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if not missing_traces:
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if limit is not None and snapshot.get("exemption_data_missing"):
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# 额度要靠总资产与持仓快照才能核算。本项目的画像与持仓由上游流程写入，
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# 数据没落地时既不能默认"没超"判误报，也不能默认"超了"判风险。
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return _assessment(
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VERDICT_CONTINUE_REVIEW,
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"中",
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[
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f"客户等级与产品等级相差 {level_gap} 级，属第十五条可豁免情形，"
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"且产品要求的交易留痕已具备。",
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"但缺少总资产或单只持仓快照，无法核算豁免额度是否被突破。",
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],
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["补查客户总资产与单只产品持仓市值后，再判定豁免是否成立。"],
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)
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return _assessment(
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VERDICT_SUSPECTED_FALSE_POSITIVE,
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"高",
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@@ -23,6 +23,7 @@ from app.model.audit import InteractionAudit
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from app.model.fund import (
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FundCapitalFlow,
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FundCustomerProfile,
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FundHolding,
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FundProduct,
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FundRiskAlert,
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FundTransaction,
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@@ -35,6 +36,38 @@ HIGH_RISK = "高"
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MEDIUM_RISK = "中"
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LOW_RISK = "低"
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RISK_ORDER = {LOW_RISK: 0, MEDIUM_RISK: 1, HIGH_RISK: 2}
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# 《个人投资者适当性管理指南》第十五条豁免规则：这两组越级购买是**允许**的，
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# 但单只产品持仓有额度上限。键是（客户等级, 产品等级），值是"单只持仓 / 总资产"上限。
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EXEMPTION_LIMITS: dict[tuple[str, str], Decimal] = {
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("C3", "R4"): Decimal("0.20"),
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("C4", "R5"): Decimal("0.10"),
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}
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def _exemption_exceeded(exemption: dict[str, Any]) -> bool:
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"""豁免额度是否被突破。占比算不出来时**不算突破**（取向见 `_exemption_state`）。"""
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ratio = exemption.get("exemption_ratio")
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limit = exemption.get("exemption_limit")
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if ratio is None or limit is None:
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return False
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return Decimal(ratio) > Decimal(limit)
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def _suitability_summary(
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customer_level: str,
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product_level: str,
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missing_trace: bool,
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exemption: dict[str, Any],
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) -> str:
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parts = [f"{customer_level} 客户购买 {product_level} 产品"]
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if _exemption_exceeded(exemption):
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parts.append(
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f"单只持仓占比 {Decimal(exemption['exemption_ratio']):.2%} "
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f"超过第十五条豁免上限 {Decimal(exemption['exemption_limit']):.0%}"
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)
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if missing_trace:
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parts.append("交易留痕不完整")
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return "，".join(parts) + "。"
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_scan_lock = asyncio.Lock()
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logger = logging.getLogger(__name__)
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@@ -161,6 +194,7 @@ class RiskRuleEngine:
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)
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continue
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gap = product_level - customer_level
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exemption = await self._exemption_state(transaction, customer, product)
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missing_trace = (
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(
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product.risk_disclosure_required
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@@ -181,16 +215,20 @@ class RiskRuleEngine:
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and (work_order is None or not work_order.recording_reference)
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)
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)
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if gap > 0 and missing_trace:
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exceeded = _exemption_exceeded(exemption)
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missing_trace = bool(missing_trace)
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if gap > 0 and (missing_trace or exceeded):
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level = HIGH_RISK if gap >= 2 else MEDIUM_RISK
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alerts.append(self._build_alert(
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transaction=transaction,
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alert_type="适当性错配",
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level=level,
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rules=["RW-007"],
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summary=(
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f"{customer.investor_type} 客户购买 "
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f"{product.risk_level} 产品，交易留痕不完整。"
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summary=_suitability_summary(
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customer.investor_type or "",
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product.risk_level,
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missing_trace,
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exemption,
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),
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priority=90 if level == HIGH_RISK else 70,
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event_status="刚刚发生",
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@@ -198,10 +236,61 @@ class RiskRuleEngine:
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"product_id": product.id,
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"level_gap": gap,
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"work_order_id": transaction.work_order_id,
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**exemption,
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},
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))
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return alerts
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async def _exemption_state(
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self,
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transaction: FundTransaction,
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customer: RiskUser,
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product: FundProduct,
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) -> dict[str, Any]:
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"""按第十五条核算豁免额度，返回要写进证据快照的字段。
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政策原文：C3 买 R4 需签《产品风险超越投资者风险承受能力揭示书》且**单只 R4 持仓
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不超过总资产 20%**；C4 买 R5 同理，上限 10%。所以越级购买本身不是违规，
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**超出额度**才是 —— 原先扫描侧只看"留痕是否齐全"，完全没有额度这一维。
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数据缺失时的取向：**不把"算不出来"当成"超限"**。实测本项目库里
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`fin_customer_profile.total_asset` 全为 0、`fin_holding` 为空 —— 画像与持仓由本
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项目之外的流程写入（与 `behavior_score` 同源），拿 0 去算会让每一笔 C3→R4 都变成
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"超限"，等于把豁免规则变成新的误报源。因此这里只如实写出缺失，
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由研判侧提示人工确认。
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"""
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limit = EXEMPTION_LIMITS.get((customer.investor_type or "", product.risk_level))
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if limit is None:
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return {}
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total_asset = await self.session.scalar(
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select(FundCustomerProfile.total_asset).where(
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FundCustomerProfile.customer_id == transaction.customer_id
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)
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)
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holding_value = await self.session.scalar(
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select(FundHolding.current_value)
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.where(
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FundHolding.customer_id == transaction.customer_id,
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FundHolding.product_id == transaction.product_id,
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)
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.order_by(FundHolding.id.desc())
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.limit(1)
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)
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state: dict[str, Any] = {"exemption_limit": str(limit)}
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if (
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total_asset is None
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or holding_value is None
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or Decimal(total_asset) <= 0
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):
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state["exemption_ratio"] = None
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state["exemption_data_missing"] = True
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return state
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state["exemption_ratio"] = str(Decimal(holding_value) / Decimal(total_asset))
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state["exemption_data_missing"] = False
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state["holding_value"] = str(holding_value)
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state["total_asset"] = str(total_asset)
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return state
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async def _elderly_redemption(self) -> list[FundRiskAlert]:
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alerts: list[FundRiskAlert] = []
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transactions = await self._scalars(
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+57
-3
@@ -97,6 +97,18 @@ agent_intent_config 中 agent_type='risk'：0 条
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`ModelGenerationService` → `BaseAgent`），再让风控改用它。因为**只是新增方法、不改现有行为**，
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对已有 Agent 零影响，但涉及基座核心链路，**是否做需要项目方定**（本轮未实施）。
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**业务裁定（2026-09-11）：本轮不补，按基座能力缺口记录。**
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理由：风控已经跑通，收益只在风控一侧；而 `chat(messages, tools)` 要贯穿
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`ModelGateway` → `OpenAICompatibleGateway` → `ModelDispatchService` →
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`ModelGenerationService` → `BaseAgent` **整条链路**，属于公共契约变更 —— 在演示与联调期间
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改它，影响面大于收益。留待基座排期时一并做，届时风控改用它是替换
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`RiskAgentModelClient` 一个类的事。
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上面"仍然成立的两点"里，第 1 点（`bootstrap.py:262-265` 的 lambda 让注入点形同虚设）本轮
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同样**不改**：它只在注入替身时才看得出差别，不影响任何行为，等基座补 `chat` 入口时一起处理。
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第 2 点（HTTP 逻辑重复一份）随第 1 点一起消失。
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### 3. 能力过滤失效，当前能工作只是巧合 🔁 ✅
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`risk_agent_model_client.py:51-54` 传 `task_type="risk_agent_chat"`，不在 `TASK_CAPABILITY` 里 →
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@@ -186,6 +198,10 @@ Asia/Shanghai 展示。北京 08:00 前生成时，统计窗口是"前一日 08:
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规则**：把明显误报（如系统重复触发）也强制走一遍调查，未必是想要的效果。代码里两道门是有意
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设置的，看不出实现偏差。**需要业务方裁定**，不由技术侧单方面加门禁。
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**业务裁定（2026-09-11）：保持现状，不加门禁。** `exclude` 继续只要求"已确认接收 +
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未闭环"。理由与复核时的判断一致：强制"调查中"会让明显误报（如系统重复触发）也必须走
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一遍调查流程，代价大于收益；`exclude` 仍会写审计、仍要求已确认接收，不是无声关闭。
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**b. `min(20, score_before)` —— 误报。**
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`BEHAVIOR_SCORE_INITIAL = 20` 是**满分**（`:18`），扣分表 `{"低":3, "中":5, "高":20}`（`:19`）
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@@ -287,10 +303,48 @@ C1(1) 与 R2(2) 相比 `1 < 2`：**按矩阵可以买，按第十四条不能买
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**这不是代码问题，是制度文本冲突**，需要业务方定一条为准。客服侧的适当性裁决走的是
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`check_suitability`（按档案等级与匹配规则），两边口径也需要对齐。
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### 2. 第十五条豁免规则未落地 ⚠️
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**业务裁定（2026-09-11）：以第十四条 `C ≥ R` 为准。**
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C3→R4（单只 ≤ 总资产 20%）、C4→R5（≤10%）的**持仓占比校验完全没有实现**；
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`risk_judgement_service.py:157` 只要留痕齐全就判"疑似误报"。是暂不实现还是漏了，需确认。
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**客服侧口径复核（同日）：本来就一致，无需改动。** 复核 `SuitabilityService._decide`
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（`suitability_service.py:195`）后确认，它的判定是
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`if profile.customer_risk_level < request.product_risk_level: 拒绝` —— **同样是第十四条的
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`C ≥ R`**，并没有使用第十二条的匹配矩阵。原文"按档案等级与匹配规则"是评审时的推测，
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不成立。
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两侧看上去的差异只有两点，且都不构成口径冲突：
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1. **专业投资者**：客服侧豁免等级匹配，但强制 `required_disclosure` /
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`requires_confirmation` / `requires_recording`（`suitability_service.py:183-194`）；
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风控扫描不做等级豁免，而是直接检查"该有的揭示、二次确认、录音留痕有没有"。
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两者合起来是同一句话：豁免等级不等于豁免留痕。
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2. **触发条件**：客服是**事前拦截**（`C < R` 直接不许买），风控是**事后发现**
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（`risk_scan_service.py:184` 的 `gap > 0 and missing_trace`）。这是职责差异，不是口径
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差异 —— RW-007 的语义是"错配**且**留痕不全"，不是"所有错配"。留痕完整却仍然成交，
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那是客服没能拦住，属另一个问题。
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### 2. 第十五条豁免规则未落地 ✅（业务裁定：实现，2026-09-11 已完成）
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C3→R4（单只 ≤ 总资产 20%）、C4→R5（≤ 10%）的**持仓占比校验原先完全没有实现**；
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`risk_judgement_service.py` 只要留痕齐全就判"疑似误报" —— 把豁免的**前提条件**当成了
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结论。业务方裁定实现，两侧一起改：
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- **扫描侧**：新增 `EXEMPTION_LIMITS` 与 `RiskRuleEngine._exemption_state`，核算
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"单只持仓 / 总资产"并写进证据快照（`exemption_limit`、`exemption_ratio`、
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`exemption_data_missing`、`holding_value`、`total_asset`）；触发条件由
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`gap > 0 and missing_trace` 改为 `gap > 0 and (missing_trace or 超出额度)`。
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- **研判侧**：`_assess_rw007` 先判额度、再判留痕 —— 超限 → "证据支持风险"；
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留痕齐全且在额度内 → "疑似误报"；留痕齐全但快照缺总资产/持仓 → "继续复核"。
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**数据前提**（探查脚本 `tools/probe_exemption_data.py`，证据留档
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`docs/evidence/exemption-data-probe.json`）：实测库内 `fin_customer_profile` 只有 1 行、
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`total_asset = 0.00`，`fin_holding` 为 0 行，且没有任何 `申购` 交易 —— 这条规则**当前不会
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被触发**，与 `behavior_score` 同源：画像与持仓由本项目之外的流程写入。
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|
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因此刻意**不**把"算不出来"当成"超限"。拿 `total_asset = 0` 去算，每一笔 C3→R4 都会变成
|
||||
违规，豁免规则反而成了新的误报源。数据缺失时扫描侧不产生预警，研判侧返回"继续复核"并
|
||||
要求补查总资产与持仓快照 —— 由人工定案，而不是用缺失数据假装有结论。
|
||||
|
||||
上游把总资产与持仓写入之后，这条链路**无需再改代码**即可生效。
|
||||
|
||||
### 3. `docs/24` 需要同步更新
|
||||
|
||||
|
||||
@@ -0,0 +1,28 @@
|
||||
{
|
||||
"profile_total_asset": [
|
||||
{
|
||||
"rows_count": 1,
|
||||
"positive_assets": "0",
|
||||
"zero_assets": "1",
|
||||
"min_asset": "0.00",
|
||||
"max_asset": "0.00"
|
||||
}
|
||||
],
|
||||
"profile_investor_type": [
|
||||
{
|
||||
"investor_type": "C2",
|
||||
"rows_count": 1
|
||||
}
|
||||
],
|
||||
"holding_shape": [
|
||||
{
|
||||
"rows_count": 0,
|
||||
"null_market_value": null,
|
||||
"positive_current_value": null,
|
||||
"min_current_value": null,
|
||||
"max_current_value": null
|
||||
}
|
||||
],
|
||||
"subscription_pairs": [],
|
||||
"exemptible_pairs_detail": []
|
||||
}
|
||||
@@ -27,12 +27,17 @@
|
||||
|
||||
| 项目 | 说明 |
|
||||
|---|---|
|
||||
| 场景 | 客户风险承受等级低于产品风险等级，且交易留痕不完整 |
|
||||
| 核心条件 | 产品风险等级高于客户等级；缺少风险揭示、二次确认或录音留痕 |
|
||||
| 场景 | 客户风险承受等级低于产品风险等级，且交易留痕不完整或超出豁免额度 |
|
||||
| 核心条件 | 产品风险等级高于客户等级；且（缺少风险揭示、二次确认或录音留痕，**或**属第十五条可豁免情形但单只持仓占比超过额度） |
|
||||
| 风险等级 | 等级差大于等于 2 时高风险；等级差为 1 时中风险 |
|
||||
| 关键证据 | 客户等级、产品等级、风险揭示、二次确认和录音编号 |
|
||||
| 风险结论 | 存在等级差且留痕缺失时支持风险判断 |
|
||||
| 误报关注 | 当前等级不再错配，或要求的留痕已完整存在 |
|
||||
| 关键证据 | 客户等级、产品等级、风险揭示、二次确认、录音编号、豁免额度与单只持仓占比 |
|
||||
| 风险结论 | 存在等级差且（留痕缺失或超出豁免额度）时支持风险判断 |
|
||||
| 误报关注 | 当前等级不再错配；或留痕完整**且**单只持仓在豁免额度内 |
|
||||
|
||||
**第十五条豁免额度**（《个人投资者适当性管理指南》）：C3 买 R4 单只持仓不超过总资产
|
||||
20%，C4 买 R5 不超过 10%。越级购买本身不是违规，**超出额度**才是。额度需要总资产与
|
||||
单只持仓快照才能核算；数据未落地时扫描侧不判超限，研判侧返回"继续复核"提示人工补查，
|
||||
不会凭缺失数据直接定案。
|
||||
|
||||
## RW-012 老年客户异常大额赎回
|
||||
|
||||
|
||||
@@ -24,10 +24,14 @@
|
||||
|
||||
## RW-007 研判
|
||||
|
||||
- 风险成立：客户风险等级低于产品风险等级，且所需留痕存在缺失。
|
||||
- 疑似误报：当前客户等级与产品等级不再错配，或风险揭示、二次确认和录音留痕完整。
|
||||
- 继续复核：缺少客户等级或产品等级。
|
||||
- 复核动作：核对最新风险测评、留痕时间和录音编号真实性。
|
||||
- 风险成立：客户风险等级低于产品风险等级，且所需留痕存在缺失；或留痕完整但单只持仓
|
||||
占比超过第十五条豁免额度（C3→R4 为 20%，C4→R5 为 10%）。
|
||||
- 疑似误报：当前客户等级与产品等级不再错配，或风险揭示、二次确认和录音留痕完整**且**
|
||||
单只持仓在豁免额度内。
|
||||
- 继续复核：缺少客户等级或产品等级；或属可豁免情形、留痕完整但缺少总资产/持仓快照，
|
||||
无法核算豁免额度。
|
||||
- 复核动作：核对最新风险测评、留痕时间和录音编号真实性；必要时补查客户总资产与单只
|
||||
产品持仓市值。
|
||||
|
||||
## RW-012 研判
|
||||
|
||||
|
||||
@@ -0,0 +1,117 @@
|
||||
"""RW-007 研判必须复核第十五条豁免额度（`docs/25` 第七节 #2）。
|
||||
|
||||
政策原文（`knowledge/policy/个人投资者适当性管理指南.md:334-341`）：
|
||||
|
||||
- C3 买 R4：签署《产品风险超越投资者风险承受能力揭示书》后**可买**，但单只 R4 持仓
|
||||
不超过总资产 **20%**；
|
||||
- C4 买 R5：同理，上限 **10%**。
|
||||
|
||||
也就是说越级购买本身不是违规，**超出额度**才是。原先 `_assess_rw007` 只看留痕：
|
||||
只要揭示书、二次确认、录音都齐，就判"疑似误报" —— 而这三样恰恰是豁免的**前提条件**，
|
||||
把前提当成结论，于是"签了字但买超了额度"被静默放过。
|
||||
|
||||
数据缺失的情况单独处理：额度要靠总资产与持仓快照才能核算，本项目的画像与持仓由上游
|
||||
流程写入（实测 `total_asset` 全为 0、`fin_holding` 为空），既不能默认"没超"判误报，
|
||||
也不能默认"超了"判风险 —— 那会把豁免规则变成新的误报源。
|
||||
"""
|
||||
|
||||
from typing import Any
|
||||
|
||||
from app.service.risk_judgement_service import (
|
||||
VERDICT_CONTINUE_REVIEW,
|
||||
VERDICT_RISK_SUPPORTED,
|
||||
VERDICT_SUSPECTED_FALSE_POSITIVE,
|
||||
_assess_rw007,
|
||||
)
|
||||
|
||||
COMPLETE_WORK_ORDER: dict[str, Any] = {
|
||||
"risk_disclosure_ack_at": "2026-09-01T00:00:00",
|
||||
"second_confirmation_at": "2026-09-01T00:00:00",
|
||||
"recording_reference": "REC-1",
|
||||
}
|
||||
|
||||
REQUIRING_PRODUCT: dict[str, Any] = {
|
||||
"risk_level": "R4",
|
||||
"risk_disclosure_required": True,
|
||||
"second_confirmation_required": True,
|
||||
"recording_required": True,
|
||||
}
|
||||
|
||||
|
||||
def _detail(
|
||||
snapshot: dict[str, Any],
|
||||
*,
|
||||
work_order: dict[str, Any] | None = None,
|
||||
investor_type: str = "C3",
|
||||
) -> dict[str, Any]:
|
||||
"""一条 C3→R4（相差 1 级、属豁免情形）的 RW-007 详情。"""
|
||||
return {
|
||||
"customer": {"investor_type": investor_type},
|
||||
"product": dict(REQUIRING_PRODUCT),
|
||||
"work_order": dict(COMPLETE_WORK_ORDER if work_order is None else work_order),
|
||||
"evidence_snapshot": snapshot,
|
||||
}
|
||||
|
||||
|
||||
def test_limit_breach_is_risk_supported_even_with_complete_trace() -> None:
|
||||
"""这是本次补上的判断：留痕齐全 ≠ 豁免成立，额度超了就是违规。"""
|
||||
result = _assess_rw007(
|
||||
_detail({"exemption_limit": "0.20", "exemption_ratio": "0.35"})
|
||||
)
|
||||
|
||||
assert VERDICT_RISK_SUPPORTED in str(result)
|
||||
assert "35.00%" in str(result)
|
||||
assert "20%" in str(result)
|
||||
|
||||
|
||||
def test_within_limit_with_complete_trace_is_a_false_positive() -> None:
|
||||
result = _assess_rw007(
|
||||
_detail({"exemption_limit": "0.20", "exemption_ratio": "0.10"})
|
||||
)
|
||||
|
||||
assert VERDICT_SUSPECTED_FALSE_POSITIVE in str(result)
|
||||
|
||||
|
||||
def test_exact_limit_is_not_a_breach() -> None:
|
||||
"""政策写的是"不超过"，恰好等于上限属于合规。"""
|
||||
result = _assess_rw007(
|
||||
_detail({"exemption_limit": "0.20", "exemption_ratio": "0.2"})
|
||||
)
|
||||
|
||||
assert VERDICT_SUSPECTED_FALSE_POSITIVE in str(result)
|
||||
|
||||
|
||||
def test_missing_snapshot_data_asks_for_manual_review() -> None:
|
||||
"""额度核算不出结果时，既不判误报也不判风险。"""
|
||||
result = _assess_rw007(
|
||||
_detail(
|
||||
{
|
||||
"exemption_limit": "0.20",
|
||||
"exemption_ratio": None,
|
||||
"exemption_data_missing": True,
|
||||
}
|
||||
)
|
||||
)
|
||||
|
||||
assert VERDICT_CONTINUE_REVIEW in str(result)
|
||||
assert "总资产" in str(result)
|
||||
|
||||
|
||||
def test_missing_trace_still_outranks_the_exemption_path() -> None:
|
||||
"""留痕不完整仍然直接判风险 —— 豁免的**前提**没满足，谈额度没有意义。"""
|
||||
result = _assess_rw007(
|
||||
_detail(
|
||||
{"exemption_limit": "0.20", "exemption_ratio": "0.01"},
|
||||
work_order={},
|
||||
)
|
||||
)
|
||||
|
||||
assert VERDICT_RISK_SUPPORTED in str(result)
|
||||
assert "缺少交易留痕" in str(result)
|
||||
|
||||
|
||||
def test_pairs_outside_the_exemption_table_keep_the_old_behaviour() -> None:
|
||||
"""C2→R5 不属豁免情形，快照里也不会有额度字段：行为必须与改动前一致。"""
|
||||
result = _assess_rw007(_detail({}, investor_type="C2"))
|
||||
|
||||
assert VERDICT_SUSPECTED_FALSE_POSITIVE in str(result)
|
||||
@@ -473,6 +473,80 @@ async def test_suitability_mismatch_rejects_complete_trace_and_matching_level()
|
||||
assert await RiskRuleEngine(session)._suitability_mismatch() == []
|
||||
|
||||
|
||||
def _complete_trace() -> RiskWorkOrder:
|
||||
return work_order(
|
||||
disclosure_at=datetime(2026, 9, 1),
|
||||
confirmation_at=datetime(2026, 9, 1),
|
||||
recording_reference="REC-1",
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_suitability_exemption_limit_breach_raises_alert() -> None:
|
||||
"""C3→R4 属第十五条允许的越级购买，但单只持仓超过总资产 20% 仍要预警。
|
||||
|
||||
原先扫描侧只看"留痕是否齐全"：签了揭示书、留痕齐全就直接不报 —— 于是"签了字
|
||||
但买超额度"这种明确违规反而没有预警。
|
||||
"""
|
||||
session = FakeSession(
|
||||
rows=[transaction()],
|
||||
get_values=[risk_user("C3"), product("R4"), _complete_trace()],
|
||||
scalar_values=[None, Decimal("100000.00"), Decimal("30000.00")],
|
||||
)
|
||||
|
||||
alerts = await RiskRuleEngine(session)._suitability_mismatch()
|
||||
|
||||
assert len(alerts) == 1
|
||||
assert alerts[0].alert_level == "中"
|
||||
assert "20%" in alerts[0].evidence_summary
|
||||
assert alerts[0].evidence_snapshot["exemption_ratio"] == "0.3"
|
||||
assert alerts[0].evidence_snapshot["exemption_limit"] == "0.20"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_suitability_exemption_within_limit_is_not_an_alert() -> None:
|
||||
"""留痕齐全且占比未超额度 → 豁免成立，不该产生预警。"""
|
||||
session = FakeSession(
|
||||
rows=[transaction()],
|
||||
get_values=[risk_user("C3"), product("R4"), _complete_trace()],
|
||||
scalar_values=[None, Decimal("100000.00"), Decimal("10000.00")],
|
||||
)
|
||||
|
||||
assert await RiskRuleEngine(session)._suitability_mismatch() == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_suitability_exemption_missing_asset_data_does_not_create_alerts() -> None:
|
||||
"""总资产为 0（上游未落地）时不能算成"超限"。
|
||||
|
||||
本项目的画像与持仓由本项目之外的流程写入，拿 0 去算会让每一笔 C3→R4 都变成
|
||||
违规 —— 豁免规则就成了新的误报源。缺失只如实记录，交给研判侧提示人工确认。
|
||||
"""
|
||||
session = FakeSession(
|
||||
rows=[transaction()],
|
||||
get_values=[risk_user("C3"), product("R4"), _complete_trace()],
|
||||
scalar_values=[None, Decimal("0"), Decimal("10000.00")],
|
||||
)
|
||||
|
||||
assert await RiskRuleEngine(session)._suitability_mismatch() == []
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_suitability_missing_trace_still_alerts_without_exemption_data() -> None:
|
||||
"""留痕不完整这条老语义不能被新增的额度逻辑冲掉。"""
|
||||
session = FakeSession(
|
||||
rows=[transaction()],
|
||||
get_values=[risk_user("C3"), product("R4"), work_order()],
|
||||
scalar_values=[None, Decimal("0"), None],
|
||||
)
|
||||
|
||||
alerts = await RiskRuleEngine(session)._suitability_mismatch()
|
||||
|
||||
assert len(alerts) == 1
|
||||
assert "交易留痕不完整" in alerts[0].evidence_summary
|
||||
assert alerts[0].evidence_snapshot["exemption_data_missing"] is True
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_elderly_redemption_requires_age_amount_average_and_uncommon_device() -> None:
|
||||
login = RiskLoginRecord(
|
||||
|
||||
@@ -0,0 +1,101 @@
|
||||
"""只读探查：第十五条豁免规则（持仓占比）所需的数据是否齐备。
|
||||
|
||||
只做 SELECT。结果写 `docs/evidence/exemption-data-probe.json`：
|
||||
|
||||
python tools/probe_exemption_data.py
|
||||
|
||||
要回答的问题：
|
||||
1. `fin_customer_profile.total_asset` 有没有值、是否为正；
|
||||
2. `fin_holding` 有没有行、`market_value` / `current_value` 是否可用；
|
||||
3. 库内是否存在 C3→R4 / C4→R5 的申购交易 —— 即这条豁免规则是否真的会被触发。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
from sqlalchemy import text
|
||||
|
||||
from app.infrastructure.db import SessionFactory
|
||||
|
||||
OUTPUT = Path("docs/evidence/exemption-data-probe.json")
|
||||
|
||||
QUERIES: dict[str, str] = {
|
||||
"profile_total_asset": """
|
||||
SELECT COUNT(*) AS rows_count,
|
||||
SUM(total_asset > 0) AS positive_assets,
|
||||
SUM(total_asset = 0) AS zero_assets,
|
||||
MIN(total_asset) AS min_asset,
|
||||
MAX(total_asset) AS max_asset
|
||||
FROM fin_customer_profile
|
||||
""",
|
||||
"profile_investor_type": """
|
||||
SELECT investor_type, COUNT(*) AS rows_count
|
||||
FROM fin_customer_profile GROUP BY investor_type ORDER BY investor_type
|
||||
""",
|
||||
"holding_shape": """
|
||||
SELECT COUNT(*) AS rows_count,
|
||||
SUM(market_value IS NULL) AS null_market_value,
|
||||
SUM(current_value > 0) AS positive_current_value,
|
||||
MIN(current_value) AS min_current_value,
|
||||
MAX(current_value) AS max_current_value
|
||||
FROM fin_holding
|
||||
""",
|
||||
"subscription_pairs": """
|
||||
SELECT c.investor_type AS customer_level,
|
||||
p.risk_level AS product_level,
|
||||
COUNT(*) AS transactions
|
||||
FROM fin_transaction t
|
||||
JOIN fin_customer_profile c ON c.customer_id = t.customer_id
|
||||
JOIN fin_product p ON p.id = t.product_id
|
||||
WHERE t.transaction_type = '申购'
|
||||
GROUP BY c.investor_type, p.risk_level
|
||||
ORDER BY c.investor_type, p.risk_level
|
||||
""",
|
||||
"exemptible_pairs_detail": """
|
||||
SELECT t.transaction_no,
|
||||
c.investor_type AS customer_level,
|
||||
p.risk_level AS product_level,
|
||||
c.total_asset,
|
||||
(
|
||||
SELECT h.current_value FROM fin_holding h
|
||||
WHERE h.customer_id = t.customer_id AND h.product_id = t.product_id
|
||||
ORDER BY h.id DESC LIMIT 1
|
||||
) AS holding_current_value
|
||||
FROM fin_transaction t
|
||||
JOIN fin_customer_profile c ON c.customer_id = t.customer_id
|
||||
JOIN fin_product p ON p.id = t.product_id
|
||||
WHERE t.transaction_type = '申购'
|
||||
AND (
|
||||
(c.investor_type = 'C3' AND p.risk_level = 'R4')
|
||||
OR (c.investor_type = 'C4' AND p.risk_level = 'R5')
|
||||
)
|
||||
ORDER BY t.id
|
||||
""",
|
||||
}
|
||||
|
||||
|
||||
async def collect() -> dict[str, Any]:
|
||||
report: dict[str, Any] = {}
|
||||
async with SessionFactory() as session:
|
||||
for name, sql in QUERIES.items():
|
||||
rows = (await session.execute(text(sql))).mappings().all()
|
||||
report[name] = [dict(row) for row in rows]
|
||||
return report
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
report = await collect()
|
||||
OUTPUT.parent.mkdir(parents=True, exist_ok=True)
|
||||
OUTPUT.write_text(
|
||||
json.dumps(report, ensure_ascii=False, indent=2, default=str),
|
||||
encoding="utf-8",
|
||||
)
|
||||
print(f"wrote {OUTPUT}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
Reference in New Issue
Block a user