风控模型开发验证报告

00 模型概要信息

项目	内容
模型名称	exp_20261010-114123-1a84
开发完成日期	2026-10-10
模型开发人员	（人工填写）
模型开发人员邮件地址	（人工填写）
模型验证人员	（人工填写）
模型验证人员邮件地址	（人工填写）
模型应用环节	preloan_approval
模型应用频率	（人工填写）
模型开发背景及业务用途描述	Local MVP full pipeline run.
模型适用产品/客户描述	（人工填写）
模型重开发原因（如有）	—
模型拟监控频率	（人工填写）
模型路线	LR + WOE 评分卡
目标变量	flag_30
实验 ID	ITE-mv240xty-2b48

待补充：模型开发/验证人员、应用频率、产品描述等字段需人工补填。

01 模型设计

建模数据样本窗口

项目	内容
切分方式	外部 data_flag 划分（TRAIN 内 6/4 随机开发/测试，VALI 跨时间，PSI 时点）
开发样本(Train)窗口	1970-01-01 ~ 1970-01-01
预留验证样本窗口	1970-01-01 ~ 1970-01-01
跨时间验证样本窗口	1970-01-01 ~ 1970-01-01
PSI时点样本窗口	1970-01-01 ~ 1970-01-01

模型好坏定义

项目	内容
目标变量	flag_30
坏样本(BAD=1)占比	22.06%
好样本(BAD=0)占比	—
不确定样本	本流程要求目标变量已预计算为 0/1 二值，不确定样本请在上游合并口径

样本排除规则

序号	排除规则	说明
1	credit_no	主键/时间/口径字段，不入模
2	apply_dt	主键/时间/口径字段，不入模
3	flag_30 为空	排除 0 行

滚动率分析

待补充：滚动率分析（M0→M6+ 状态迁移矩阵）需要逾期状态口径数据，当前流程目标变量为上游已计算的二值标签，暂未生成。

待补充：表现窗口及坏账率分析、模型细分定义需结合业务口径人工补充。

02 数据流

开发时点 — 样本排除

类别	样本数
全部样本	30000
排除：目标变量为空	0
排除后样本	30000

注：按照01模型设计的排除规则统计；当前流程的排除项为目标变量缺失。

总体样本概况

数据集	样本量	好样本	坏样本	坏样本率	占比
全部样本	30000	23383	6617	22.06%	100.00%
开发样本	10801	8453	2348	21.74%	36.00%
测试样本	7199	5635	1564	21.73%	24.00%
训练+测试样本	18000	14088	3912	21.73%	60.00%
跨时间验证样本	6000	4624	1376	22.93%	20.00%
PSI时点样本	6000	4671	1329	22.15%	20.00%

开发/预留验证样本交叉统计

类别	总样本数	开发样本数	开发占比	预留验证样本数	预留验证占比
好	23383	8453	36.15%	5635	24.10%
坏	6617	2348	35.48%	1564	23.64%
合计	30000	10801	36.00%	7199	24.00%

细致变量分析（预分箱口径，开发样本）

变量	IV	缺失率	取值集中度	最大相关系数
risk_score	0.1434	0.00%	0.91%	0.9986
risk_score_v2	0.1390	0.00%	0.94%	0.9986
bh_a001	0.1382	0.00%	0.15%	0.9298
ScoreCust2_v2	0.1321	0.00%	1.14%	0.9952
ScoreCust2	0.1277	0.00%	1.13%	0.9952
bh_a009	0.1271	0.00%	1.73%	0.8070
cust_seg2	0.0848	0.00%	30.86%	0.6662
avg_tnr	0.0841	0.00%	1.92%	0.6947
query_cnt_3m	0.0732	0.00%	16.53%	0.5822
income_grade	0.0632	0.00%	31.12%	0.5458
repay_amt_6m_grade	0.0607	0.00%	27.69%	0.5342
rare_field	0.0330	96.32%	0.76%	0.0812
tenure_m	0.0217	0.00%	5.50%	0.3328
card_usage_ratio	0.0214	0.00%	1.69%	0.3613
bank_997_cnt_3m	0.0205	0.00%	34.62%	0.2757
edu_level	0.0004	0.00%	42.13%	—
region_code	0.0004	0.00%	20.63%	—
flag_special	0.0000	0.00%	95.41%	0.0380

注：共 18 个候选变量，按 IV 降序展示前 18 个；集中度 = 最大频次取值样本数 ÷ 非空样本数；相关性为皮尔逊（仅数值变量），完整数据见 variable_detail.json。

03 单变量分析（细分箱）

risk_score_v2 — IV 0.1290，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 495.5]	1406	1353	53	3.77%	0.2336
2	(495.5, 518.5]	1105	1019	86	7.78%	0.1453
3	(518.5, 527.5]	550	481	69	12.55%	0.0507
4	(527.5, 537.5]	639	574	65	10.17%	0.0735
5	(537.5, 563.5]	1942	1656	286	14.73%	0.1126
6	(563.5, 584.5]	1585	1243	342	21.58%	0.0022
7	(584.5, 602.5]	1181	853	328	27.77%	-0.0625
8	(602.5, 615.5]	667	442	225	33.73%	-0.0759
9	(615.5, 643.5]	986	551	435	44.12%	-0.1927
10	(643.5, inf]	740	281	459	62.03%	-0.2656

risk_score — IV 0.1272，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 492.5]	1279	1232	47	3.67%	0.2165
2	(492.5, 519.5]	1276	1182	94	7.37%	0.1696
3	(519.5, 535.5]	1032	914	118	11.43%	0.1000
4	(535.5, 546.5]	801	694	107	13.36%	0.0648
5	(546.5, 564.5]	1350	1144	206	15.26%	0.0779
6	(564.5, 587.5]	1704	1320	384	22.54%	-0.0112
7	(587.5, 600.5]	870	626	244	28.05%	-0.0507
8	(600.5, 616.5]	797	531	266	33.38%	-0.0859
9	(616.5, 643.5]	955	529	426	44.61%	-0.1917
10	(643.5, inf]	737	281	456	61.87%	-0.2638

ScoreCust2_v2 — IV 0.1262，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 507.5]	1649	1574	75	4.55%	0.2546
2	(507.5, 522.5]	1083	979	104	9.60%	0.1235
3	(522.5, 536.5]	1285	1138	147	11.44%	0.1205
4	(536.5, 544.5]	790	677	113	14.30%	0.0567
5	(544.5, 553.5]	959	776	183	19.08%	0.0237
6	(553.5, 565.5]	1232	965	267	21.67%	0.0007
7	(565.5, 583.5]	1611	1171	440	27.31%	-0.0737
8	(583.5, 593.5]	655	432	223	34.05%	-0.0766
9	(593.5, 606.5]	640	370	270	42.19%	-0.1231
10	(606.5, inf]	897	371	526	58.64%	-0.2861

ScoreCust2 — IV 0.1191，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 494.5]	957	923	34	3.55%	0.1690
2	(494.5, 508.5]	749	703	46	6.14%	0.1154
3	(508.5, 528.5]	1534	1387	147	9.58%	0.1658
4	(528.5, 545.5]	1664	1438	226	13.58%	0.1168
5	(545.5, 562.5]	1785	1421	364	20.39%	0.0198
6	(562.5, 572.5]	972	735	237	24.38%	-0.0235
7	(572.5, 579.5]	636	457	179	28.14%	-0.0392
8	(579.5, 592.5]	912	609	303	33.22%	-0.0950
9	(592.5, 604.5]	615	364	251	40.81%	-0.1111
10	(604.5, inf]	977	416	561	57.42%	-0.2967

avg_tnr — IV 0.1073，7 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 2.149999976158142]	926	474	452	48.81%	-0.2194
2	(2.149999976158142, 3.350000023841858]	961	609	352	36.63%	-0.1276
3	(3.350000023841858, 4.450000047683716]	1258	903	355	28.22%	-0.0706
4	(4.450000047683716, 4.8500001430511475]	550	422	128	23.27%	-0.0083
5	(4.8500001430511475, 5.950000047683716]	1583	1247	336	21.23%	0.0069
6	(5.950000047683716, 7.3500001430511475]	2097	1722	375	17.88%	0.0646
7	(7.3500001430511475, inf]	3426	3076	350	10.22%	0.2859

cust_seg2 — IV 0.1060，4 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 3.5]	2056	1867	189	9.19%	0.2166
2	(3.5, 4.5]	3333	2822	511	15.33%	0.1501
3	(4.5, 5.5]	3330	2505	825	24.77%	-0.0668
4	(5.5, inf]	2082	1259	823	39.53%	-0.2705

bh_a009 — IV 0.0991，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 6.3500001430511475]	902	433	469	52.00%	-0.2386
2	(6.3500001430511475, 7.3500001430511475]	875	548	327	37.37%	-0.1238
3	(7.3500001430511475, 8.050000190734863]	773	509	264	34.15%	-0.0891
4	(8.050000190734863, 8.849999904632568]	1062	753	309	29.10%	-0.0697
5	(8.849999904632568, 9.25]	578	430	148	25.61%	-0.0218
6	(9.25, 10.050000190734863]	1235	982	253	20.49%	0.0138
7	(10.050000190734863, 11.449999809265137]	2187	1873	314	14.36%	0.1298
8	(11.449999809265137, 12.75]	1501	1362	139	9.26%	0.1674
9	(12.75, 13.550000190734863]	664	591	73	10.99%	0.0706
10	(13.550000190734863, inf]	1024	972	52	5.08%	0.1637

rare_field — IV 0.0827，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, -1.437000036239624]	23	21	2	8.70%	0.0847
2	(-1.437000036239624, -0.8540000021457672]	60	43	17	28.33%	-0.0735
3	(-0.8540000021457672, -0.443000003695488]	50	43	7	14.00%	0.1024
4	(-0.443000003695488, -0.25699999928474426]	25	15	10	40.00%	-0.1074
5	(-0.25699999928474426, -0.05299999937415123]	30	26	4	13.33%	0.0713
6	(-0.05299999937415123, 0.10999999940395355]	24	14	10	41.67%	-0.1134
7	(0.10999999940395355, 0.3699999898672104]	34	24	10	29.41%	-0.0554
8	(0.3699999898672104, 1.0099999904632568]	89	80	9	10.11%	0.2372
9	(1.0099999904632568, 1.324500024318695]	26	19	7	26.92%	-0.0279
10	(1.324500024318695, inf]	36	22	14	38.89%	-0.1369

income_grade — IV 0.0632，5 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 3.5]	1211	743	468	38.65%	-0.1736
2	(3.5, 4.5]	2510	1766	744	29.64%	-0.1417
3	(4.5, 5.5]	3361	2689	672	19.99%	0.0398
4	(5.5, 6.5]	2503	2150	353	14.10%	0.1484
5	(6.5, inf]	1216	1105	111	9.13%	0.1419

repay_amt_6m_grade — IV 0.0607，5 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 3.5]	1647	1047	600	36.43%	-0.1915
2	(3.5, 4.5]	2268	1634	634	27.95%	-0.1049
3	(4.5, 5.5]	2991	2384	607	20.29%	0.0305
4	(5.5, 6.5]	2286	1944	342	14.96%	0.1227
5	(6.5, inf]	1609	1444	165	10.25%	0.1624

query_cnt_3m — IV 0.0483，9 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 0.5]	550	288	262	47.64%	-0.1355
2	(0.5, 1.5]	1123	724	399	35.53%	-0.1345
3	(1.5, 2.5]	1627	1151	476	29.26%	-0.0995
4	(2.5, 3.5]	1785	1384	401	22.46%	-0.0106
5	(3.5, 4.5]	1665	1365	300	18.02%	0.0523
6	(4.5, 5.5]	1347	1127	220	16.33%	0.0646
7	(5.5, 6.5]	1026	897	129	12.57%	0.0882
8	(6.5, 8.5]	1098	970	128	11.66%	0.1031
9	(8.5, inf]	580	547	33	5.69%	0.0940

bank_997_cnt_3m — IV 0.0246，4 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 0.5]	3447	2899	548	15.90%	0.1392
2	(0.5, 1.5]	3739	2928	811	21.69%	0.0012
3	(1.5, 2.5]	2224	1655	569	25.58%	-0.0648
4	(2.5, inf]	1391	971	420	30.19%	-0.0990

card_usage_ratio — IV 0.0183，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 0.107999999076128]	922	854	68	7.38%	0.1277
2	(0.107999999076128, 0.1578500047326088]	616	511	105	17.05%	0.0285
3	(0.1578500047326088, 0.3025500029325485]	2324	1848	476	20.48%	0.0224
4	(0.3025500029325485, 0.3381499946117401]	649	545	104	16.02%	0.0364
5	(0.3381499946117401, 0.4825499951839447]	2550	1996	554	21.73%	0.0003
6	(0.4825499951839447, 0.5283499956130981]	687	497	190	27.66%	-0.0388
7	(0.5283499956130981, 0.6137499809265137]	1203	941	262	21.78%	-0.0004
8	(0.6137499809265137, 0.6709499955177307]	594	405	189	31.82%	-0.0578
9	(0.6709499955177307, 0.7716499865055084]	715	520	195	27.27%	-0.0376
10	(0.7716499865055084, inf]	541	336	205	37.89%	-0.0844

tenure_m — IV 0.0170，10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 2.5]	696	414	282	40.52%	-0.1218
2	(2.5, 10.5]	1179	891	288	24.43%	-0.0281
3	(10.5, 23.5]	2292	1813	479	20.90%	0.0148
4	(23.5, 30.5]	1310	997	313	23.89%	-0.0245
5	(30.5, 36.5]	1080	844	236	21.85%	-0.0011
6	(36.5, 39.5]	554	448	106	19.13%	0.0143
7	(39.5, 46.5]	1268	974	294	23.19%	-0.0161
8	(46.5, 53.5]	1211	970	241	19.90%	0.0199
9	(53.5, 58.5]	647	568	79	12.21%	0.0610
10	(58.5, inf]	564	534	30	5.32%	0.0937

edu_level — IV 0.0004，4 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	大专	3260	2574	686	21.04%	0.0155
2	本科	4550	3555	995	21.87%	-0.0035
3	硕士及以上	1405	1081	324	23.06%	-0.0160
4	高中及以下	1586	1243	343	21.63%	0.0015

region_code — IV 0.0004，5 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	其他	2119	1657	462	21.80%	-0.0011
2	华东	2156	1685	471	21.85%	-0.0018
3	华北	2119	1682	437	20.62%	0.0186
4	华南	2179	1701	478	21.94%	-0.0033
5	西南	2228	1728	500	22.44%	-0.0120

flag_special — IV 0.0000，1 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, inf]	10801	8453	2348	21.74%	0.0000

data_flag — IV 0.0000，1 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	TRAIN	10801	8453	2348	21.74%	0.0000

注：统计全部候选变量的自动分箱明细（初分组），按 IV 降序展示前 18 个变量，共 18 个；完整数据见 feature_report.json。

04 单变量分析（粗分箱）

risk_score_v2 — 10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 495.5]	1406	1353	53	3.77%	0.2336
2	(495.5, 518.5]	1105	1019	86	7.78%	0.1453
3	(518.5, 527.5]	550	481	69	12.55%	0.0507
4	(527.5, 537.5]	639	574	65	10.17%	0.0735
5	(537.5, 563.5]	1942	1656	286	14.73%	0.1126
6	(563.5, 584.5]	1585	1243	342	21.58%	0.0022
7	(584.5, 602.5]	1181	853	328	27.77%	-0.0625
8	(602.5, 615.5]	667	442	225	33.73%	-0.0759
9	(615.5, 643.5]	986	551	435	44.12%	-0.1927
10	(643.5, inf]	740	281	459	62.03%	-0.2656

risk_score — 10 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 492.5]	1279	1232	47	3.67%	0.2165
2	(492.5, 519.5]	1276	1182	94	7.37%	0.1696
3	(519.5, 535.5]	1032	914	118	11.43%	0.1000
4	(535.5, 546.5]	801	694	107	13.36%	0.0648
5	(546.5, 564.5]	1350	1144	206	15.26%	0.0779
6	(564.5, 587.5]	1704	1320	384	22.54%	-0.0112
7	(587.5, 600.5]	870	626	244	28.05%	-0.0507
8	(600.5, 616.5]	797	531	266	33.38%	-0.0859
9	(616.5, 643.5]	955	529	426	44.61%	-0.1917
10	(643.5, inf]	737	281	456	61.87%	-0.2638

avg_tnr — 7 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 2.149999976158142]	926	474	452	48.81%	-0.2194
2	(2.149999976158142, 3.350000023841858]	961	609	352	36.63%	-0.1276
3	(3.350000023841858, 4.450000047683716]	1258	903	355	28.22%	-0.0706
4	(4.450000047683716, 4.8500001430511475]	550	422	128	23.27%	-0.0083
5	(4.8500001430511475, 5.950000047683716]	1583	1247	336	21.23%	0.0069
6	(5.950000047683716, 7.3500001430511475]	2097	1722	375	17.88%	0.0646
7	(7.3500001430511475, inf]	3426	3076	350	10.22%	0.2859

cust_seg2 — 4 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 3.5]	2056	1867	189	9.19%	0.2166
2	(3.5, 4.5]	3333	2822	511	15.33%	0.1501
3	(4.5, 5.5]	3330	2505	825	24.77%	-0.0668
4	(5.5, inf]	2082	1259	823	39.53%	-0.2705

income_grade — 5 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 3.5]	1211	743	468	38.65%	-0.1736
2	(3.5, 4.5]	2510	1766	744	29.64%	-0.1417
3	(4.5, 5.5]	3361	2689	672	19.99%	0.0398
4	(5.5, 6.5]	2503	2150	353	14.10%	0.1484
5	(6.5, inf]	1216	1105	111	9.13%	0.1419

repay_amt_6m_grade — 5 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 3.5]	1647	1047	600	36.43%	-0.1915
2	(3.5, 4.5]	2268	1634	634	27.95%	-0.1049
3	(4.5, 5.5]	2991	2384	607	20.29%	0.0305
4	(5.5, 6.5]	2286	1944	342	14.96%	0.1227
5	(6.5, inf]	1609	1444	165	10.25%	0.1624

query_cnt_3m — 9 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 0.5]	550	288	262	47.64%	-0.1355
2	(0.5, 1.5]	1123	724	399	35.53%	-0.1345
3	(1.5, 2.5]	1627	1151	476	29.26%	-0.0995
4	(2.5, 3.5]	1785	1384	401	22.46%	-0.0106
5	(3.5, 4.5]	1665	1365	300	18.02%	0.0523
6	(4.5, 5.5]	1347	1127	220	16.33%	0.0646
7	(5.5, 6.5]	1026	897	129	12.57%	0.0882
8	(6.5, 8.5]	1098	970	128	11.66%	0.1031
9	(8.5, inf]	580	547	33	5.69%	0.0940

bank_997_cnt_3m — 4 箱

分组号	分栏	Total	Good	Bad	Bad Rate	WOE
1	(-inf, 0.5]	3447	2899	548	15.90%	0.1392
2	(0.5, 1.5]	3739	2928	811	21.69%	0.0012
3	(1.5, 2.5]	2224	1655	569	25.58%	-0.0648
4	(2.5, inf]	1391	971	420	30.19%	-0.0990

注：统计入模变量经合并调整后的最终分箱明细（开发样本口径）。当前流程细/粗分箱由同一自动分箱算法直接产出。

05 变量筛选

项目	内容
筛选优先级	黑名单 > 白名单 > 自动规则
IV 下限	0.02
缺失率上限	0.8
集中度上限	0.9
相关性上限(皮尔逊)	0.7
PSI 上限	0.25
重要性 Top-K	80
黑名单	bh_a001
白名单	risk_score

候选变量 19，成功分箱 18，入模 8

变量	白名单	入模	IV	缺失率	集中度	IV门槛	相关性	PSI	剔除原因
risk_score	白名单	Y	0.1272	PASS	PASS	—	—	0.0037
ScoreCust2	—	N	0.1191	PASS	PASS	PASS	FAIL	0.0026	与 risk_score_v2 相关>0.7
cust_seg2	—	Y	0.1060	PASS	PASS	PASS	PASS	0.0005
income_grade	—	Y	0.0632	PASS	PASS	PASS	PASS	0.0009
bh_a001	—	N	—	—	—	—	—	—	黑名单
bh_a009	—	N	0.0991	PASS	PASS	PASS	FAIL	0.0012	与 risk_score_v2 相关>0.7
bank_997_cnt_3m	—	Y	0.0246	PASS	PASS	PASS	PASS	0.0010
avg_tnr	—	Y	0.1073	PASS	PASS	PASS	PASS	0.0014
repay_amt_6m_grade	—	Y	0.0607	PASS	PASS	PASS	PASS	0.0007
tenure_m	—	N	0.0170	PASS	PASS	FAIL	—	—	IV<0.02
query_cnt_3m	—	Y	0.0483	PASS	PASS	PASS	PASS	0.0014
card_usage_ratio	—	N	0.0183	PASS	PASS	FAIL	—	—	IV<0.02
rare_field	—	N	0.0827	FAIL	PASS	—	—	—	缺失率>0.8
flag_special	—	N	0.0000	PASS	FAIL	—	—	—	集中度>0.9
edu_level	—	N	0.0004	PASS	PASS	FAIL	—	—	IV<0.02
region_code	—	N	0.0004	PASS	PASS	FAIL	—	—	IV<0.02
risk_score_v2	—	Y	0.1290	PASS	PASS	PASS	PASS	0.0032
ScoreCust2_v2	—	N	0.1262	PASS	PASS	PASS	FAIL	0.0020	与 risk_score_v2 相关>0.7
data_flag	—	N	0.0000	PASS	FAIL	—	—	—	集中度>0.9

06 回归结果

硬门槛：P≥0.1 / VIF>4.0 迭代剔除，共 1 个变量被剔除（2 轮）：risk_score。

Parameter	Label	Estimate(无惩罚)	Standard Error	Wald Chi-Square	Pr > ChiSq	Standardized Estimate
Intercept	Intercept	-1.3085	0.0277	2230.93	<0.0001	—
WOE_risk_score_v2	risk_score_v2	-4.8708	0.2901	281.99	<0.0001	-0.6949
WOE_avg_tnr	avg_tnr	-0.8455	0.1974	18.34	<0.0001	-0.1431
WOE_cust_seg2	cust_seg2	-0.3926	0.1740	5.09	0.0240	-0.0693
WOE_income_grade	income_grade	-0.6184	0.2250	7.55	0.0060	-0.0777
WOE_repay_amt_6m_grade	repay_amt_6m_grade	-0.4724	0.2295	4.24	0.0396	-0.0583
WOE_query_cnt_3m	query_cnt_3m	-0.7636	0.3375	5.12	0.0237	-0.0664
WOE_bank_997_cnt_3m	bank_997_cnt_3m	-0.7679	0.2963	6.72	0.0095	-0.0685

注：Estimate 列为无惩罚（精确推断）拟合；生产系数保持 L2 正则（model_results.json / score.py 口径），两套估计并列展示。标准误基于无惩罚似然观测信息矩阵。

07 VIF

VIF

Parameter	VIF
risk_score_v2	2.84730
avg_tnr	1.67573
cust_seg2	1.61993
income_grade	1.31935
repay_amt_6m_grade	1.33585
query_cnt_3m	1.44588
bank_997_cnt_3m	1.06835

	risk_score_v2	avg_tnr	cust_seg2	income_grade	repay_amt_6m_grade	query_cnt_3m	bank_997_cnt_3m
risk_score_v2	1.000	0.627	0.608	0.482	0.492	0.546	0.246
avg_tnr	0.627	1.000	0.434	0.344	0.353	0.382	0.174
cust_seg2	0.608	0.434	1.000	0.333	0.352	0.385	0.176
income_grade	0.482	0.344	0.333	1.000	0.277	0.310	0.152
repay_amt_6m_grade	0.492	0.353	0.352	0.277	1.000	0.305	0.137
query_cnt_3m	0.546	0.382	0.385	0.310	0.305	1.000	0.155
bank_997_cnt_3m	0.246	0.174	0.176	0.152	0.137	0.155	1.000

08 最终评分卡

标准分600

标准ODD50

PDO20

变量	分栏	WOE	Coefficient	Scorecard Points
risk_score_v2	(-inf, 495.5]	0.2336	-4.6131	106
	(495.5, 518.5]	0.1453	-4.6131	94
	(518.5, 527.5]	0.0507	-4.6131	82
	(527.5, 537.5]	0.0735	-4.6131	85
	(537.5, 563.5]	0.1126	-4.6131	90
	(563.5, 584.5]	0.0022	-4.6131	75
	(584.5, 602.5]	-0.0625	-4.6131	67
	(602.5, 615.5]	-0.0759	-4.6131	65
	(615.5, 643.5]	-0.1927	-4.6131	49
	(643.5, inf]	-0.2656	-4.6131	40
avg_tnr	(-inf, 2.149999976158142]	-0.2194	-0.8885	69
	(2.149999976158142, 3.350000023841858]	-0.1276	-0.8885	72
	(3.350000023841858, 4.450000047683716]	-0.0706	-0.8885	73
	(4.450000047683716, 4.8500001430511475]	-0.0083	-0.8885	75
	(4.8500001430511475, 5.950000047683716]	0.0069	-0.8885	75
	(5.950000047683716, 7.3500001430511475]	0.0646	-0.8885	77
	(7.3500001430511475, inf]	0.2859	-0.8885	82
cust_seg2	(-inf, 3.5]	0.2166	-0.4363	78
	(3.5, 4.5]	0.1501	-0.4363	77
	(4.5, 5.5]	-0.0668	-0.4363	74
	(5.5, inf]	-0.2705	-0.4363	72
income_grade	(-inf, 3.5]	-0.1736	-0.6832	72
	(3.5, 4.5]	-0.1417	-0.6832	72
	(4.5, 5.5]	0.0398	-0.6832	76
	(5.5, 6.5]	0.1484	-0.6832	78
	(6.5, inf]	0.1419	-0.6832	78
repay_amt_6m_grade	(-inf, 3.5]	-0.1915	-0.5348	72
	(3.5, 4.5]	-0.1049	-0.5348	73
	(4.5, 5.5]	0.0305	-0.5348	75
	(5.5, 6.5]	0.1227	-0.5348	77
	(6.5, inf]	0.1624	-0.5348	77
query_cnt_3m	(-inf, 0.5]	-0.1355	-0.7743	72
	(0.5, 1.5]	-0.1345	-0.7743	72
	(1.5, 2.5]	-0.0995	-0.7743	73
	(2.5, 3.5]	-0.0106	-0.7743	75
	(3.5, 4.5]	0.0523	-0.7743	76
	(4.5, 5.5]	0.0646	-0.7743	76
	(5.5, 6.5]	0.0882	-0.7743	77
	(6.5, 8.5]	0.1031	-0.7743	77
	(8.5, inf]	0.0940	-0.7743	77
bank_997_cnt_3m	(-inf, 0.5]	0.1392	-0.7505	78
	(0.5, 1.5]	0.0012	-0.7505	75
	(1.5, 2.5]	-0.0648	-0.7505	74
	(2.5, inf]	-0.0990	-0.7505	73

09 模型表现

模型区分度评估（按样本）

模型	样本	KS	AUC	GINI
LR + WOE 评分卡	开发样本	0.3776	0.7515	0.5030
LR + WOE 评分卡	测试样本	0.3665	0.7448	0.4896
LR + WOE 评分卡	训练+测试样本	0.3729	0.7488	0.4976
LR + WOE 评分卡	跨时间验证样本	0.3430	0.7288	0.4576
LR + WOE 评分卡	PSI时点样本	0.3771	0.7453	0.4906

LR + WOE 评分卡 — 4 样本评估表（score_cut 粒度）

开发样本（KS 0.3776，AUC 0.7515）

cuts	cnt	bad	good	bad_rate	population_pct	cum_bad_rate	cum_good_rate
(0.0431, 0.0583]	1081	41	1040	3.79%	10.01%	1.75%	12.30%
(0.0584, 0.0892]	1080	72	1008	6.67%	10.00%	4.81%	24.23%
(0.0892, 0.1110]	1080	115	965	10.65%	10.00%	9.71%	35.64%
(0.1110, 0.1309]	1081	137	944	12.67%	10.01%	15.55%	46.81%
(0.1309, 0.1580]	1079	161	918	14.92%	9.99%	22.40%	57.67%
(0.1580, 0.2089]	1080	190	890	17.59%	10.00%	30.49%	68.20%
(0.2089, 0.2635]	1080	269	811	24.91%	10.00%	41.95%	77.79%
(0.2636, 0.3287]	1080	309	771	28.61%	10.00%	55.11%	86.92%
(0.3288, 0.4879]	1080	436	644	40.37%	10.00%	73.68%	94.53%
(0.4880, 0.6538]	1080	618	462	57.22%	10.00%	100.00%	100.00%

测试样本（KS 0.3665，AUC 0.7448）

cuts	cnt	bad	good	bad_rate	population_pct	cum_bad_rate	cum_good_rate
(0.0431, 0.0572]	720	31	689	4.31%	10.00%	1.98%	12.23%
(0.0573, 0.0890]	720	47	673	6.53%	10.00%	4.99%	24.17%
(0.0891, 0.1109]	720	80	640	11.11%	10.00%	10.10%	35.53%
(0.1110, 0.1305]	720	89	631	12.36%	10.00%	15.79%	46.73%
(0.1306, 0.1547]	720	108	612	15.00%	10.00%	22.70%	57.59%
(0.1547, 0.2060]	719	138	581	19.19%	9.99%	31.52%	67.90%
(0.2060, 0.2640]	720	176	544	24.44%	10.00%	42.77%	77.55%
(0.2642, 0.3270]	720	220	500	30.56%	10.00%	56.84%	86.42%
(0.3271, 0.4794]	720	272	448	37.78%	10.00%	74.23%	94.37%
(0.4798, 0.6538]	720	403	317	55.97%	10.00%	100.00%	100.00%

训练+测试样本（KS 0.3729，AUC 0.7488）

cuts	cnt	bad	good	bad_rate	population_pct	cum_bad_rate	cum_good_rate
(0.0431, 0.0577]	1800	71	1729	3.94%	10.00%	1.81%	12.27%
(0.0577, 0.0891]	1800	119	1681	6.61%	10.00%	4.86%	24.20%
(0.0892, 0.1110]	1800	195	1605	10.83%	10.00%	9.84%	35.60%
(0.1110, 0.1307]	1801	227	1574	12.60%	10.01%	15.64%	46.77%
(0.1307, 0.1563]	1799	270	1529	15.01%	9.99%	22.55%	57.62%
(0.1563, 0.2080]	1800	328	1472	18.22%	10.00%	30.93%	68.07%
(0.2080, 0.2637]	1800	443	1357	24.61%	10.00%	42.25%	77.70%
(0.2637, 0.3279]	1800	534	1266	29.67%	10.00%	55.90%	86.69%
(0.3279, 0.4839]	1800	701	1099	38.94%	10.00%	73.82%	94.49%
(0.4839, 0.6538]	1800	1024	776	56.89%	10.00%	100.00%	100.00%

跨时间验证样本（KS 0.3430，AUC 0.7288）

cuts	cnt	bad	good	bad_rate	population_pct	cum_bad_rate	cum_good_rate
(0.0431, 0.0592]	600	20	580	3.33%	10.00%	1.45%	12.54%
(0.0592, 0.0887]	600	62	538	10.33%	10.00%	5.96%	24.18%
(0.0887, 0.1115]	600	70	530	11.67%	10.00%	11.05%	35.64%
(0.1115, 0.1307]	600	97	503	16.17%	10.00%	18.10%	46.52%
(0.1307, 0.1578]	600	87	513	14.50%	10.00%	24.42%	57.61%
(0.1580, 0.2105]	600	132	468	22.00%	10.00%	34.01%	67.73%
(0.2106, 0.2600]	600	163	437	27.17%	10.00%	45.86%	77.18%
(0.2600, 0.3282]	600	179	421	29.83%	10.00%	58.87%	86.29%
(0.3284, 0.4832]	600	244	356	40.67%	10.00%	76.60%	93.99%
(0.4832, 0.6538]	600	322	278	53.67%	10.00%	100.00%	100.00%

注：score_cut 表基于模型输出 PD 等频分 10 档（分数升序），每表附 KS/AUC；训练+测试 = TRAIN 全体。

10 KS和GINI

LR + WOE 评分卡

样本	KS	GINI	AUC
开发样本	0.3776	0.5030	0.7515
测试样本	0.3665	0.4896	0.7448
训练+测试样本	0.3729	0.4976	0.7488
跨时间验证样本	0.3430	0.4576	0.7288
PSI时点样本	0.3771	0.4906	0.7453

开发样本

测试样本

训练+测试样本

跨时间验证样本

注：GINI = 2×AUC−1。KS 图 X 轴为分数（升序），红虚线为最大间隔位置；ROC 图例标注 AUC。

11 PSI

模型稳定性评估

模型	训练集与测试集	训练集与跨时间验证	训练集与oot验证集	训练集与psi验证集
LR + WOE 评分卡	0.0025	0.0021	—	0.0021

分数段 PSI 明细（开发样本 vs 跨时间验证样本）

分数段	开发样本占比	跨时间验证样本占比	PSI 贡献	累计 PSI
(-inf,0.0583]	10.00%	9.65%	0.0001	0.0001
(0.0583,0.0892]	10.00%	10.43%	0.0002	0.0003
(0.0892,0.111]	10.00%	9.75%	0.0001	0.0004
(0.111,0.1309]	10.00%	10.27%	0.0001	0.0004
(0.1309,0.158]	10.00%	9.92%	0.0000	0.0004
(0.158,0.2089]	10.00%	9.57%	0.0002	0.0006
(0.2089,0.2635]	10.01%	11.02%	0.0010	0.0016
(0.2635,0.3287]	9.99%	9.43%	0.0003	0.0019
(0.3287,0.4879]	10.00%	10.30%	0.0001	0.0020
(0.4879,inf]	10.01%	9.67%	0.0001	0.0021

分数段 PSI 明细（开发样本 vs PSI时点样本）

分数段	开发样本占比	PSI时点占比	PSI 贡献	累计 PSI
(-inf,0.0583]	10.00%	9.83%	0.0000	0.0000
(0.0583,0.0892]	10.00%	9.72%	0.0001	0.0001
(0.0892,0.111]	10.00%	10.52%	0.0003	0.0004
(0.111,0.1309]	10.00%	10.75%	0.0005	0.0009
(0.1309,0.158]	10.00%	10.20%	0.0000	0.0010
(0.158,0.2089]	10.00%	9.88%	0.0000	0.0010
(0.2089,0.2635]	10.01%	9.48%	0.0003	0.0013
(0.2635,0.3287]	9.99%	9.17%	0.0007	0.0020
(0.3287,0.4879]	10.00%	10.28%	0.0001	0.0020
(0.4879,inf]	10.01%	10.17%	0.0000	0.0021

模型样本量分布评估

评分段	开发样本样本量	开发样本占比	测试样本样本量	测试样本占比	训练+测试样本样本量	训练+测试样本占比	跨时间验证样本样本量	跨时间验证样本占比	PSI时点样本样本量	PSI时点样本占比
(-inf, inf]	1080	10.00%	751	10.43%	1831	10.17%	579	9.65%	590	9.83%
(0.0583, 0.0892]	1080	10.00%	691	9.60%	1771	9.84%	626	10.43%	583	9.72%
(0.0892, 0.111]	1080	10.00%	720	10.00%	1800	10.00%	585	9.75%	631	10.52%
(0.111, 0.1309]	1080	10.00%	723	10.04%	1803	10.02%	616	10.27%	645	10.75%
(0.1309, 0.158]	1080	10.00%	781	10.85%	1861	10.34%	595	9.92%	612	10.20%
(0.158, 0.2089]	1080	10.00%	680	9.45%	1760	9.78%	574	9.57%	593	9.88%
(0.2089, 0.2635]	1081	10.01%	686	9.53%	1767	9.82%	661	11.02%	569	9.48%
(0.2635, 0.3287]	1079	9.99%	750	10.42%	1829	10.16%	566	9.43%	550	9.17%
(0.3287, 0.4879]	1080	10.00%	748	10.39%	1828	10.16%	618	10.30%	617	10.28%
(0.4879, inf]	1081	10.01%	669	9.29%	1750	9.72%	580	9.67%	610	10.17%
sum	10801	100.00%	7199	100.00%	18000	100.00%	6000	100.00%	6000	100.00%

变量 PSI（开发样本 vs PSI时点样本，按入模变量分箱）

特征项	PSI	状态
risk_score	0.0037	稳定
risk_score_v2	0.0032	稳定
avg_tnr	0.0014	稳定
query_cnt_3m	0.0014	稳定
bank_997_cnt_3m	0.0010	稳定
income_grade	0.0009	稳定
repay_amt_6m_grade	0.0007	稳定
cust_seg2	0.0005	稳定

risk_score_v2 — PSI 0.0032

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 495.5]	13.02%	12.23%	-0.78%	0.0005
(495.5, 518.5]	10.23%	11.20%	0.97%	0.0009
(518.5, 527.5]	5.09%	5.32%	0.22%	0.0001
(527.5, 537.5]	5.92%	6.25%	0.33%	0.0002
(537.5, 563.5]	17.98%	18.28%	0.30%	0.0001
(563.5, 584.5]	14.67%	14.03%	-0.64%	0.0003
(584.5, 602.5]	10.93%	10.13%	-0.80%	0.0006
(602.5, 615.5]	6.18%	5.78%	-0.39%	0.0003
(615.5, 643.5]	9.13%	9.52%	0.39%	0.0002
(643.5, inf]	6.85%	7.25%	0.40%	0.0002

risk_score — PSI 0.0037

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 492.5]	11.84%	10.97%	-0.87%	0.0007
(492.5, 519.5]	11.81%	12.98%	1.17%	0.0011
(519.5, 535.5]	9.55%	9.55%	-0.00%	0.0000
(535.5, 546.5]	7.42%	8.02%	0.60%	0.0005
(546.5, 564.5]	12.50%	12.57%	0.07%	0.0000
(564.5, 587.5]	15.78%	14.98%	-0.79%	0.0004
(587.5, 600.5]	8.05%	7.53%	-0.52%	0.0003
(600.5, 616.5]	7.38%	6.93%	-0.45%	0.0003
(616.5, 643.5]	8.84%	9.43%	0.59%	0.0004
(643.5, inf]	6.82%	7.03%	0.21%	0.0001

avg_tnr — PSI 0.0014

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 2.149999976158142]	8.57%	8.88%	0.31%	0.0001
(2.149999976158142, 3.350000023841858]	8.90%	8.87%	-0.03%	0.0000
(3.350000023841858, 4.450000047683716]	11.65%	11.57%	-0.08%	0.0000
(4.450000047683716, 4.8500001430511475]	5.09%	5.18%	0.09%	0.0000
(4.8500001430511475, 5.950000047683716]	14.66%	14.48%	-0.17%	0.0000
(5.950000047683716, 7.3500001430511475]	19.41%	18.15%	-1.26%	0.0009
(7.3500001430511475, inf]	31.72%	32.87%	1.15%	0.0004

cust_seg2 — PSI 0.0005

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 3.5]	19.04%	19.07%	0.03%	0.0000
(3.5, 4.5]	30.86%	30.50%	-0.36%	0.0000
(4.5, 5.5]	30.83%	31.77%	0.94%	0.0003
(5.5, inf]	19.28%	18.67%	-0.61%	0.0002

income_grade — PSI 0.0009

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 3.5]	11.21%	10.70%	-0.51%	0.0002
(3.5, 4.5]	23.24%	23.15%	-0.09%	0.0000
(4.5, 5.5]	31.12%	31.07%	-0.05%	0.0000
(5.5, 6.5]	23.17%	24.25%	1.08%	0.0005
(6.5, inf]	11.26%	10.83%	-0.42%	0.0002

repay_amt_6m_grade — PSI 0.0007

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 3.5]	15.25%	14.83%	-0.42%	0.0001
(3.5, 4.5]	21.00%	21.75%	0.75%	0.0003
(4.5, 5.5]	27.69%	26.92%	-0.78%	0.0002
(5.5, 6.5]	21.16%	21.43%	0.27%	0.0000
(6.5, inf]	14.90%	15.07%	0.17%	0.0000

query_cnt_3m — PSI 0.0014

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 0.5]	5.09%	5.28%	0.19%	0.0001
(0.5, 1.5]	10.40%	10.45%	0.05%	0.0000
(1.5, 2.5]	15.06%	14.95%	-0.11%	0.0000
(2.5, 3.5]	16.53%	16.27%	-0.26%	0.0000
(3.5, 4.5]	15.42%	15.28%	-0.13%	0.0000
(4.5, 5.5]	12.47%	13.08%	0.61%	0.0003
(5.5, 6.5]	9.50%	9.20%	-0.30%	0.0001
(6.5, 8.5]	10.17%	10.67%	0.50%	0.0002
(8.5, inf]	5.37%	4.82%	-0.55%	0.0006

bank_997_cnt_3m — PSI 0.0010

分栏	开发基准比例	PSI时点样本比例	变更	贡献
(-inf, 0.5]	31.91%	32.48%	0.57%	0.0001
(0.5, 1.5]	34.62%	35.27%	0.65%	0.0001
(1.5, 2.5]	20.59%	20.35%	-0.24%	0.0000
(2.5, inf]	12.88%	11.90%	-0.98%	0.0008

注：PSI ≤ 0.1 视为稳定，0.1~0.25 需关注，> 0.25 不稳定。

12 单变量分析

注：统计所有入模变量的单变量分析（开发样本口径）。预留验证/总体/OOT 口径的分组明细待扩展。

risk_score_v2

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 495.5]	1406	13.02%	1353	53	3.77%	25.53
2	(495.5, 518.5]	1105	23.25%	1019	86	7.78%	11.85
3	(518.5, 527.5]	550	28.34%	481	69	12.55%	6.97
4	(527.5, 537.5]	639	34.26%	574	65	10.17%	8.83
5	(537.5, 563.5]	1942	52.24%	1656	286	14.73%	5.79
6	(563.5, 584.5]	1585	66.91%	1243	342	21.58%	3.63
7	(584.5, 602.5]	1181	77.84%	853	328	27.77%	2.60
8	(602.5, 615.5]	667	84.02%	442	225	33.73%	1.96
9	(615.5, 643.5]	986	93.15%	551	435	44.12%	1.27
10	(643.5, inf]	740	100.00%	281	459	62.03%	0.61
合计		10801		8453	2348	21.74%	3.60

risk_score

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 492.5]	1279	11.84%	1232	47	3.67%	26.21
2	(492.5, 519.5]	1276	23.66%	1182	94	7.37%	12.57
3	(519.5, 535.5]	1032	33.21%	914	118	11.43%	7.75
4	(535.5, 546.5]	801	40.63%	694	107	13.36%	6.49
5	(546.5, 564.5]	1350	53.12%	1144	206	15.26%	5.55
6	(564.5, 587.5]	1704	68.90%	1320	384	22.54%	3.44
7	(587.5, 600.5]	870	76.96%	626	244	28.05%	2.57
8	(600.5, 616.5]	797	84.33%	531	266	33.38%	2.00
9	(616.5, 643.5]	955	93.18%	529	426	44.61%	1.24
10	(643.5, inf]	737	100.00%	281	456	61.87%	0.62
合计		10801		8453	2348	21.74%	3.60

avg_tnr

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 2.149999976158142]	926	8.57%	474	452	48.81%	1.05
2	(2.149999976158142, 3.350000023841858]	961	17.47%	609	352	36.63%	1.73
3	(3.350000023841858, 4.450000047683716]	1258	29.12%	903	355	28.22%	2.54
4	(4.450000047683716, 4.8500001430511475]	550	34.21%	422	128	23.27%	3.30
5	(4.8500001430511475, 5.950000047683716]	1583	48.87%	1247	336	21.23%	3.71
6	(5.950000047683716, 7.3500001430511475]	2097	68.28%	1722	375	17.88%	4.59
7	(7.3500001430511475, inf]	3426	100.00%	3076	350	10.22%	8.79
合计		10801		8453	2348	21.74%	3.60

cust_seg2

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 3.5]	2056	19.04%	1867	189	9.19%	9.88
2	(3.5, 4.5]	3333	49.89%	2822	511	15.33%	5.52
3	(4.5, 5.5]	3330	80.72%	2505	825	24.77%	3.04
4	(5.5, inf]	2082	100.00%	1259	823	39.53%	1.53
合计		10801		8453	2348	21.74%	3.60

income_grade

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 3.5]	1211	11.21%	743	468	38.65%	1.59
2	(3.5, 4.5]	2510	34.45%	1766	744	29.64%	2.37
3	(4.5, 5.5]	3361	65.57%	2689	672	19.99%	4.00
4	(5.5, 6.5]	2503	88.74%	2150	353	14.10%	6.09
5	(6.5, inf]	1216	100.00%	1105	111	9.13%	9.95
合计		10801		8453	2348	21.74%	3.60

repay_amt_6m_grade

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 3.5]	1647	15.25%	1047	600	36.43%	1.75
2	(3.5, 4.5]	2268	36.25%	1634	634	27.95%	2.58
3	(4.5, 5.5]	2991	63.94%	2384	607	20.29%	3.93
4	(5.5, 6.5]	2286	85.10%	1944	342	14.96%	5.68
5	(6.5, inf]	1609	100.00%	1444	165	10.25%	8.75
合计		10801		8453	2348	21.74%	3.60

query_cnt_3m

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 0.5]	550	5.09%	288	262	47.64%	1.10
2	(0.5, 1.5]	1123	15.49%	724	399	35.53%	1.81
3	(1.5, 2.5]	1627	30.55%	1151	476	29.26%	2.42
4	(2.5, 3.5]	1785	47.08%	1384	401	22.46%	3.45
5	(3.5, 4.5]	1665	62.49%	1365	300	18.02%	4.55
6	(4.5, 5.5]	1347	74.97%	1127	220	16.33%	5.12
7	(5.5, 6.5]	1026	84.46%	897	129	12.57%	6.95
8	(6.5, 8.5]	1098	94.63%	970	128	11.66%	7.58
9	(8.5, inf]	580	100.00%	547	33	5.69%	16.58
合计		10801		8453	2348	21.74%	3.60

bank_997_cnt_3m

组号	Value	Tot. Records	累计占比	#Goods	#Bads	Bad Rate	G/B Odds
1	(-inf, 0.5]	3447	31.91%	2899	548	15.90%	5.29
2	(0.5, 1.5]	3739	66.53%	2928	811	21.69%	3.61
3	(1.5, 2.5]	2224	87.12%	1655	569	25.58%	2.91
4	(2.5, inf]	1391	100.00%	971	420	30.19%	2.31
合计		10801		8453	2348	21.74%	3.60

13 压力测试

注：验证压力情境下模型的有效性和区分能力稳定性：a.坏浓度更高样本 b.时间外样本 c.特定特征客群 d.极端时间样本。当前流程自动生成情景1（跨时间样本）与情景2（跨时间样本剔除一半好样本，批注16）。

测试情景1：跨时间验证样本

变量贡献度

变量	贡献度
risk_score_v2	0.6949
avg_tnr	0.1431
income_grade	0.0777
cust_seg2	0.0693
bank_997_cnt_3m	0.0685
query_cnt_3m	0.0664
repay_amt_6m_grade	0.0583

区分度验证 — LR + WOE 评分卡 @ 跨时间样本

KS = 0.3430，GINI = 0.4576

组号	分数区间(PD)	样本数	累计占比	Good	Bad	累计Good占比	累计Bad占比	分组坏率	累计坏率	分组Odds	累计Odds
1	0.0431 ~ 0.0592	600	10.00%	580	20	12.54%	1.45%	3.33%	3.33%	29.00	29.00
2	0.0592 ~ 0.0887	600	20.00%	538	62	11.63%	5.96%	10.33%	6.83%	8.68	13.63
3	0.0887 ~ 0.1115	600	30.00%	530	70	11.46%	11.05%	11.67%	8.44%	7.57	10.84
4	0.1115 ~ 0.1307	600	40.00%	503	97	10.88%	18.10%	16.17%	10.38%	5.19	8.64
5	0.1307 ~ 0.1578	600	50.00%	513	87	11.09%	24.42%	14.50%	11.20%	5.90	7.93
6	0.1580 ~ 0.2105	600	60.00%	468	132	10.12%	34.01%	22.00%	13.00%	3.55	6.69
7	0.2106 ~ 0.2600	600	70.00%	437	163	9.45%	45.86%	27.17%	15.02%	2.68	5.66
8	0.2600 ~ 0.3282	600	80.00%	421	179	9.10%	58.87%	29.83%	16.88%	2.35	4.93
9	0.3284 ~ 0.4832	600	90.00%	356	244	7.70%	76.60%	40.67%	19.52%	1.46	4.12
10	0.4832 ~ 0.6538	600	100.00%	278	322	6.01%	100.00%	53.67%	22.93%	0.86	3.36
TOTALS		6000		4624	1376			22.93%		—	3.36

测试情景2：跨时间样本剔除一半好样本

指标	数值
样本量	6000 → 3688（剔除好样本 2312）
KS	0.3356
AUC	0.7252
GINI	0.4504

注：情景2 模拟好样本分布右移的压力情形（固定 seed=42，可复现）；剔除后 KS/AUC 下降幅度反映模型对好样本结构的敏感度。