风控模型开发验证报告

实验 ID: DEV-mvgb3cba-b872 · 生成时间: 2026-10-20 14:32 (GMT+8) · 报告结构:标准14节模型开发验证模板

00 模型概要信息

项目内容
模型名称exp_DEV-mvga8dob-1994
开发完成日期2026-10-20
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inloan_warning
模型应用频率(人工填写)
模型开发背景及业务用途描述Develop run with tuning
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LightGBM
目标变量gbflag
实验 IDDEV-mvgb3cba-b872
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2021-10-17 ~ 2026-04-30
预留验证样本窗口2024-04-30 ~ 2026-04-30
跨时间验证样本窗口2021-12-31 ~ 2026-06-30
PSI时点样本窗口2023-11-18 ~ 2026-07-31

模型好坏定义

项目内容
目标变量gbflag
坏样本(BAD=1)占比8.03%
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
1id_no主键/时间/口径字段,不入模
2create_time主键/时间/口径字段,不入模
3data_flag主键/时间/口径字段,不入模
4gbflag 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115682
排除:目标变量为空0
排除后样本115682

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11568210638992938.03%100.00%
开发样本380883493731518.27%32.92%
测试样本253912329121008.27%21.95%
训练+测试样本634795822852518.27%54.87%
跨时间验证样本347303229824327.00%30.02%
PSI时点样本17473158631610—15.10%

开发/预留验证样本交叉统计

类别开发+预留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582283493760.00%2329140.00%
坏5251315160.01%210039.99%
合计634793808860.00%2539140.00%

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
due_day_my1.68520.00%46.32%0.0972
last_od_to_cur_freq0.05780.02%70.20%0.4978
max_od_days0.04250.02%25.81%0.5557
last_loan_setl_tnr0.03850.02%18.96%0.3034
apprv_amt_day0.03840.02%79.67%0.6396
ps_perd_no0.03510.00%13.10%0.6425
available_limit_amt0.03230.02%32.48%0.8089
end_loan_to_cur_freq0.03220.02%6.32%0.6425
last_od_num_m60.03130.02%78.72%0.6476
shd_pre_repay_due_rate0.03101.11%16.57%0.5562
odgt0_m12_subcurmonth0.03060.07%34.86%0.7415
cre_l60_used_limit_rate_min0.03060.06%10.21%0.7274
shd_max_dpd0.03011.05%74.62%0.3801
cre_l30_l90_used_amt_d_max0.02990.34%21.39%0.6593
setl_prcp_ratio0.02830.02%21.83%0.6593
acc_ps_perd_no0.02770.02%25.81%0.4281
cre_l90_used_limit_amt_min0.02610.06%14.62%0.7390
shd_l30_max_dpd0.02472.96%71.65%0.7038
cre_l30_l90_used_amt_m_max0.02450.06%21.48%0.6810
loan_os_prcp_credit_amount_m60.02430.07%2.98%0.5204
f_ps_od_days_max0.02290.02%53.63%0.5202
apprv_num_m30.02280.02%52.89%0.7533
cre_now_l60_used_amt_m_min0.02020.06%74.02%0.6396
loan_os_prcp_credit_amount_m30.02020.07%9.66%0.5204
cre_l60_used_limit_rate_max0.01780.06%6.42%0.7274
useratemore50maxcontimonsm120.01740.07%10.71%0.6543
orig_prcp_avg_m30.01690.02%60.04%0.5989
s_ps_od_days_max0.01660.02%54.12%0.5455
cre_now_l60_limit_left_d_max0.01650.48%67.92%0.7660
od_amt_m6_loan_os_prcp_m6_pc0.01630.07%93.14%0.6644
useratemore70_m6_num0.01590.07%28.42%0.6941
cre_l30_limit_left_amt_min0.01490.06%4.18%0.7875
repay_amount_m3_loan_os_prcp_pc0.01470.07%38.42%0.6366
t_ps_od_days_max0.01440.02%54.18%0.5455
loan_os_prcp_credit_amount_m120.01440.07%0.23%0.2371
ps_int_amt_mon0.01410.02%5.50%0.7503
od_amt_m12_loan_os_prcp_m12_pc0.01410.07%92.39%0.6644
suc_apprv_num_m60.01390.02%34.85%0.7214
cre_now_p1m_used_rate_d0.01365.64%4.54%0.9733
odgt0_m12_mob_pc0.01200.07%33.87%0.6158
useratemore70monthsubcurmonth0.01200.07%35.85%0.6077
avg_tnr0.01170.02%30.34%0.6841
apprv_num_m10.01140.02%73.93%0.7533
shd_pre_repay_amt_rate0.01130.08%1.29%0.6789
cre_now_l30_used_amt_d_min0.01095.71%86.91%0.9733
cre_now_l30_used_amt_d_max0.01080.52%14.27%0.6000
cre_now_l60_used_amt_m_max0.01080.06%11.21%0.6810
min_tnr0.01060.02%53.18%0.6841
ps_int_amt_sum0.01040.02%1.21%0.7396
suc_apprv_num_m10.01040.02%79.23%0.6800
orig_prcp_avg_m120.01030.02%3.24%0.6695
odgt0_m12_num0.01020.07%34.86%0.7141
useratemore90maxcontimonsm120.01010.07%24.43%0.6895
useratemore90_m3_num0.00970.07%61.13%0.6941
repay_amount_m6_all_shd_amt_pc0.00940.07%3.66%0.7885
cre_l30_l90_usedrate_m_max0.00880.06%26.85%0.7107
max_loan_os_prcp_m120.00840.07%4.04%0.7503
m_s_ps_instm_amt0.00810.02%70.25%0.4301
cre_now_l60_limit_left_d_min0.00775.74%11.24%0.8178
cre_now_l60_usedrate_m_max0.00760.06%13.38%0.7107
cre_now_p2m_used_rate_m0.00751.66%2.23%0.7553
cre_now_l30_limit_left_d_min0.00744.23%14.95%0.3058
last_clear_num_m30.00730.02%57.66%0.7214
ps_int_amt_avg0.00730.02%1.21%0.6095
cre_l30_l90_used_amt_m_min0.00720.06%78.40%0.5989
cre_now_l60_used_amt_d_min0.007210.25%81.68%0.7521
min_apply_amt0.00670.02%10.57%0.4938
shd_instm_amt_sum0.00640.08%0.03%0.7396
cre_now_l90_limit_left_d_min0.00606.91%9.77%0.8178
cre_usedrate_u30_daydelta_max0.005812.49%83.72%0.6366
shd_l180_instm_amt_sum0.00560.08%0.11%0.7458
cre_now_p3m_used_rate_d0.005611.82%1.60%0.7521
repay_amount_m6_loan_os_prcp_pc0.00550.07%54.31%0.5912
account_age0.00530.07%4.74%0.7206
repay_amount_all_shd_amt_pc0.00510.07%5.67%0.6536
odgt0_m3_num0.00500.07%53.85%0.7141
shd_pre_repay_cnt0.00490.08%1.22%0.5711
shd_l60_min_dpd0.00472.50%51.07%0.7466
ps_prcp_amt_mon0.00420.02%4.60%0.7458
loan_os_prcp_gt0_m12_num_pc0.00410.07%61.32%0.5912
cre_now_p1m_used_rate_m0.00390.93%4.84%0.7553
shd_remain_actual_cnt0.00370.08%7.33%0.6008
min_apprv_amt0.00330.02%29.17%0.5699
max_int_rat0.00310.02%34.15%0.4054
account_age_loan_day0.00310.07%2.11%0.7206
shd_l90_ps_due_cnt0.00310.08%17.68%0.6782
end_loan_to_rep_loan_freq0.00300.02%6.97%0.4280
shd_l30_pre_repay_due_rate0.00293.11%48.56%0.7855
sum_apply_amt0.00260.02%10.45%0.4938
grade_limit_amount0.00260.02%38.22%0.4065
shd_l180_max_dpd0.00211.69%57.75%0.7885
last_apply_freq0.00190.02%87.14%0.6518
setl_rem_prcp_paym_last_month_lo0.00170.07%87.85%0.6536
shd_remain_actual_rate0.00160.41%66.46%0.7855
shd_min_dpd0.00161.06%26.93%0.7113
last_clear_num_m10.00150.02%79.20%0.7141
age0.00140.02%4.89%0.1655
cre_now_l30_limit_left_d_max0.00130.72%79.30%0.7660
setl_rem_prcp_paym_m12_loan_os_p0.00130.07%36.61%0.3691
setl_prcp_mon_ratio0.00100.07%6.05%0.4346

注:共 125 个候选变量,按 IV 降序展示前 100 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)

max_od_days — IV 0.0930,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]98278680114711.67%-0.1437
2(0.5, 5.5]215682048210865.04%0.2515
3(5.5, 7.5]231721142038.76%-0.0070
4(7.5, 12.5]2223194827512.37%-0.0552
5(12.5, inf]2145170643920.47%-0.1527
f_ps_od_days_max — IV 0.0585,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2042218144227811.15%-0.1822
2(0.5, 1.5]844180024395.20%0.1313
3(1.5, 2.5]342032751454.24%0.0838
4(2.5, 4.5]359034531373.82%0.0970
5(4.5, inf]220720561516.84%0.0197
last_od_to_cur_freq — IV 0.0513,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.5]4011321679519.82%-0.2396
2(1.5, 3.5]260823722369.05%-0.0123
3(3.5, 8.5]20511970813.95%0.0567
4(8.5, 50042.0]26782607712.65%0.0950
5(50042.0, inf]267322476519677.36%0.0725
ovd_days_d3_num_m1 — IV 0.0484,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]346763222824487.06%0.1079
2(0.5, inf]3404270270220.62%-0.2248
odgt0_m12_subcurmonth — IV 0.0471,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]98048659114511.68%-0.1437
2(0.5, 2.5]794975344155.22%0.1249
3(2.5, 5.5]402238601624.03%0.1018
4(5.5, 50005.0]30172932852.82%0.1027
5(50005.0, inf]1326811926134210.11%-0.0957
end_loan_to_cur_freq — IV 0.0457,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -95.5]2062418471215310.44%-0.1401
2(-95.5, -68.5]301127622498.27%0.0000
3(-68.5, -22.5]632459293956.25%0.0685
4(-22.5, -0.5]571355651482.59%0.1868
5(-0.5, inf]240822032058.51%-0.0036
orig_prcp_avg_m3 — IV 0.0438,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 23.449999809265137]2286420513235110.28%-0.1366
2(23.449999809265137, 1920.6666259765625]782875103184.06%0.1738
3(1920.6666259765625, 3515.75]293827901485.04%0.0584
4(3515.75, 6174.75]198018531276.41%0.0233
5(6174.75, inf]247022642068.34%-0.0010
t_ps_od_days_max — IV 0.0423,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2063318517211610.26%-0.1288
2(0.5, 2.5]11097105245735.16%0.1613
3(2.5, 3.5]20481977713.47%0.0631
4(3.5, 5.5]219720751225.55%0.0377
5(5.5, inf]2105183726812.73%-0.0571
s_ps_od_days_max — IV 0.0405,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2061018430218010.58%-0.1484
2(0.5, 1.5]795175284235.32%0.1205
3(1.5, 2.5]346533031624.68%0.0753
4(2.5, 4.5]349433261684.81%0.0730
5(4.5, inf]256023432178.48%-0.0032
shd_pre_repay_due_rate — IV 0.0386,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.868800014257431]1047399205535.28%0.1510
2(0.868800014257431, 0.9498499929904938]654960524977.59%0.0243
3(0.9498499929904938, 0.9933499991893768]563651215159.14%-0.0251
4(0.9933499991893768, 1.0524500012397766]95728408116412.16%-0.1599
5(1.0524500012397766, inf]543450373977.31%0.0296
last_loan_setl_tnr — IV 0.0380,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]723969942453.38%0.1922
2(0.5, 3.5]11453105429117.95%0.0158
3(3.5, 4.5]2791244234912.50%-0.0693
4(4.5, 8.5]106849521116310.89%-0.1179
5(8.5, inf]591354314828.15%0.0038
available_limit_amt — IV 0.0357,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.03499999921768904]1238510918146711.85%-0.1727
2(0.03499999921768904, 468.864990234375]452342472766.10%0.0562
3(468.864990234375, 4307.300048828125]11998111488507.08%0.0621
4(4307.300048828125, 27316.265625]725067884626.37%0.0711
5(27316.265625, inf]19241829954.94%0.0410
setl_prcp_ratio — IV 0.0338,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.035099999979138374]832579603654.38%0.1671
2(0.035099999979138374, 0.1652499958872795]448840913978.85%-0.0143
3(0.1652499958872795, 0.3135499954223633]4253372752612.37%-0.0947
4(0.3135499954223633, 0.6564500033855438]1207710849122810.17%-0.0933
5(0.6564500033855438, inf]893783036347.09%0.0507
cre_l30_l90_used_amt_d_max — IV 0.0332,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.508650004863739]289127071846.36%0.0340
2(0.508650004863739, 0.6789500117301941]800773646438.03%0.0102
3(0.6789500117301941, 0.8662499785423279]1519013563162710.71%-0.1338
4(0.8662499785423279, 0.9735499918460846]308228212618.47%-0.0033
5(0.9735499918460846, inf]879083584324.91%0.1496
ps_perd_no — IV 0.0308,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.5]499148451462.93%0.1562
2(1.5, 2.5]317029961745.49%0.0535
3(2.5, 3.5]322530072186.76%0.0292
4(3.5, 9.5]1737515601177410.21%-0.1160
5(9.5, inf]932784888399.00%-0.0309
last_od_num_m6 — IV 0.0306,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]299772791920586.87%0.1192
2(0.5, 3.5]4179362155813.35%-0.1149
3(3.5, 7.5]1999171028914.46%-0.0751
4(7.5, inf]1925168024512.73%-0.0527
apprv_num_m3 — IV 0.0302,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2013918040209910.42%-0.1376
2(0.5, 1.5]663762224156.25%0.0708
3(1.5, 2.5]356333532105.89%0.0505
4(2.5, 4.5]361034311794.96%0.0717
5(4.5, inf]413138842475.98%0.0551
shd_max_dpd — IV 0.0301,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]95658427113811.90%-0.1498
2(0.5, inf]281222613419887.07%0.1006
loan_os_prcp_credit_amount_m3 — IV 0.0294,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -4999.0]3677329937810.28%-0.0421
2(-4999.0, 35.125]831579333824.59%0.1574
3(35.125, 100.47500228881836]191161761015067.88%0.0264
4(100.47500228881836, 124.34499740600586]2717241230511.23%-0.0476
5(124.34499740600586, inf]4235365757813.65%-0.1225
suc_apprv_num_m1 — IV 0.0288,3 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]301692728728829.55%-0.0993
2(0.5, 1.5]478745911964.09%0.1161
3(1.5, inf]31243052722.30%0.1164
max_od_due — IV 0.0279,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]98078661114611.69%-0.1440
2(0.5, inf]282532625020037.09%0.0971
apprv_num_m1 — IV 0.0268,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]281522542527279.69%-0.1064
2(0.5, 1.5]535051072434.54%0.1130
3(1.5, 2.5]19891914753.77%0.0575
4(2.5, inf]258924841054.06%0.0684
cre_l60_used_limit_rate_min — IV 0.0264,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.019700000062584877]444143061353.04%0.1382
2(0.019700000062584877, 0.09174999967217445]281326561575.58%0.0466
3(0.09174999967217445, 0.2787500023841858]732368075167.05%0.0459
4(0.2787500023841858, 0.9161500036716461]188991715717429.22%-0.0603
5(0.9161500036716461, inf]4589398960013.07%-0.1170
cre_now_l60_used_amt_m_min — IV 0.0256,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.7799999713897705]282012545827439.73%-0.1091
2(1.7799999713897705, 869.5950012207031]247623681084.36%0.0609
3(869.5950012207031, 1999.7100219726562]20602009512.48%0.0771
4(1999.7100219726562, 6462.93505859375]312530091163.71%0.0880
5(6462.93505859375, inf]220320711325.99%0.0316
cre_l30_l90_used_amt_m_max — IV 0.0252,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 35.010000228881836]863382194144.80%0.1524
2(35.010000228881836, 350.3800048828125]631158194927.80%0.0158
3(350.3800048828125, 1554.1449584960938]132551202012359.32%-0.0551
4(1554.1449584960938, 1951.3800048828125]205918961637.92%0.0046
5(1951.3800048828125, inf]7807696184610.84%-0.0944
apprv_amt_day — IV 0.0250,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 11.0]303442745228929.53%-0.0978
2(11.0, 1000.5]25062421853.39%0.0773
3(1000.5, 5995.0]33043220842.54%0.1172
4(5995.0, inf]19261837894.62%0.0450
acc_ps_perd_no — IV 0.0247,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]98278680114711.67%-0.1437
2(0.5, 7.5]132211211111108.40%-0.0067
3(7.5, 23.5]846178965656.68%0.0665
4(23.5, 65.5]462543732525.45%0.0750
5(65.5, inf]19461870763.91%0.0546
shd_l30_max_dpd — IV 0.0247,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]278582582320357.30%0.0899
2(0.5, inf]91018026107511.81%-0.1374
loan_os_prcp_credit_amount_m6 — IV 0.0239,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 4.129999876022339]191717931246.47%0.0220
2(4.129999876022339, 33.795000076293945]621059412694.33%0.1352
3(33.795000076293945, 48.94499969482422]443741412966.67%0.0406
4(48.94499969482422, 107.59499740600586]187351707416618.87%-0.0381
5(107.59499740600586, inf]6761596279911.82%-0.1166
cre_l90_used_limit_amt_min — IV 0.0232,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 21.640000343322754]561854082103.74%0.1447
2(21.640000343322754, 748.7099914550781]807675265506.81%0.0589
3(748.7099914550781, 8516.22998046875]201721835418189.01%-0.0490
4(8516.22998046875, 14597.384765625]2267199027712.22%-0.0541
5(14597.384765625, inf]1932163729515.27%-0.0821
cre_now_l60_limit_left_d_max — IV 0.0188,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -0.013299999758601189]2253199925411.27%-0.0417
2(-0.013299999758601189, 0.3223000019788742]393537202155.46%0.0651
3(0.3223000019788742, 0.6971500217914581]239722881094.55%0.0562
4(0.6971500217914581, 0.9999499917030334]28902809812.80%0.0993
5(0.9999499917030334, inf]264292396024699.34%-0.0810
cre_l30_limit_left_amt_min — IV 0.0169,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -132.05500030517578]7225636985611.85%-0.1230
2(-132.05500030517578, 101.06500244140625]428240322505.84%0.0605
3(101.06500244140625, 432.6999969482422]312328952287.30%0.0182
4(432.6999969482422, 2482.1400146484375]1019293188748.58%-0.0137
5(2482.1400146484375, inf]13243123019427.11%0.0645
avg_od_amt_m6_orig_prcp_pc — IV 0.0166,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5699999928474426]355683286627027.60%0.0596
2(0.5699999928474426, inf]2492204544717.94%-0.1391
od_amt_m6_loan_os_prcp_m6_pc — IV 0.0163,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.38500000536441803]355693286527047.60%0.0591
2(0.38500000536441803, inf]2491204644517.86%-0.1381
repay_amount_m3_loan_os_prcp_pc — IV 0.0159,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -4999.0]480445542505.20%0.0845
2(-4999.0, 31.585000038146973]5227462060711.61%-0.0913
3(31.585000038146973, 41.34499931335449]3887349639110.06%-0.0393
4(41.34499931335449, 74.81499862670898]943485768589.09%-0.0353
5(74.81499862670898, inf]147081366510437.09%0.0699
cre_now_l30_limit_left_d_max — IV 0.0155,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.0002500000045984052]196918101598.08%0.0025
2(0.0002500000045984052, 0.42524999380111694]220321031004.54%0.0525
3(0.42524999380111694, 0.9999499917030334]30422974682.24%0.1157
4(0.9999499917030334, inf]306002779828029.16%-0.0698
cre_now_l60_limit_left_d_min — IV 0.0154,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.04739999957382679]363233442887.93%0.0107
2(0.04739999957382679, 0.9717499911785126]4407384256512.82%-0.1076
3(0.9717499911785126, 1.149049997329712]931387205936.37%0.0945
4(1.149049997329712, 3.562299966812134]152411389013518.86%-0.0263
5(3.562299966812134, inf]330830832256.80%0.0331
loan_os_prcp_credit_amount_m12 — IV 0.0153,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 16.18000030517578]316430581063.35%0.0963
2(16.18000030517578, 44.21000099182129]603356713626.00%0.0744
3(44.21000099182129, 77.875]144531322312308.51%-0.0134
4(77.875, 95.76499938964844]663560086279.45%-0.0394
5(95.76499938964844, inf]7775695182410.60%-0.0857
cre_now_l90_limit_left_d_min — IV 0.0151,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -0.6798500120639801]270025101907.04%0.0236
2(-0.6798500120639801, 0.1424499973654747]288626242629.08%-0.0123
3(0.1424499973654747, 0.9937500059604645]4103356354013.16%-0.1111
4(0.9937500059604645, 1.1872499585151672]791274344786.04%0.0985
5(1.1872499585151672, inf]178551634715088.45%-0.0030
od_amt_m12_loan_os_prcp_m12_pc — IV 0.0143,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.0950000025331974]352223253226907.64%0.0557
2(0.0950000025331974, inf]2838237945916.17%-0.1281
shd_l30_pre_repay_due_rate — IV 0.0142,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.8838499784469604]6969614482511.84%-0.1156
2(0.8838499784469604, 1.0121999979019165]179551658813677.61%0.0530
3(1.0121999979019165, 1.781749963760376]287526032729.46%-0.0180
4(1.781749963760376, 4.9175498485565186]709165455467.70%0.0264
5(4.9175498485565186, inf]20131914994.92%0.0456
suc_apprv_num_m6 — IV 0.0138,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]132721196013129.89%-0.0843
2(0.5, 1.5]873979657748.86%-0.0240
3(1.5, 2.5]477044383326.96%0.0351
4(2.5, 3.5]304228022407.89%0.0070
5(3.5, inf]825777654925.96%0.0960
ps_int_amt_mon — IV 0.0136,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.475000023841858]23542275793.36%0.0735
2(1.475000023841858, 19.704999923706055]933887056336.78%0.0666
3(19.704999923706055, 132.375]194131782715868.17%0.0068
4(132.375, 296.6699981689453]4803426753611.16%-0.0743
5(296.6699981689453, inf]2172185631614.55%-0.0819
cre_now_l30_used_amt_d_min — IV 0.0132,3 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.0000500082969666]312112827329389.41%-0.0631
2(1.0000500082969666, 1.382200002670288]19331860733.78%0.0612
3(1.382200002670288, inf]27682687812.93%0.1006
shd_pre_repay_amt_rate — IV 0.0132,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.6238499879837036]12637118148236.51%0.0964
2(0.6238499879837036, 0.7506499886512756]863179446877.96%0.0130
3(0.7506499886512756, 0.8537499904632568]906682188489.35%-0.0450
4(0.8537499904632568, 0.9255499839782715]5759513162810.90%-0.0780
5(0.9255499839782715, inf]196618031638.29%-0.0002
cre_l60_used_limit_rate_max — IV 0.0132,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.22405000030994415]426540422235.23%0.0758
2(0.22405000030994415, 0.9925500154495239]205931889516988.25%0.0020
3(0.9925500154495239, 1.2138000130653381]592755623656.16%0.0681
4(1.2138000130653381, 1.424750030040741]2499215134813.93%-0.0834
5(1.424750030040741, inf]4781426551610.79%-0.0648
cre_now_l30_used_amt_d_max — IV 0.0129,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.6786499917507172]737668984786.48%0.0691
2(0.6786499917507172, 0.7513499855995178]240421862189.07%-0.0112
3(0.7513499855995178, 0.7632499933242798]191617791377.15%0.0140
4(0.7632499933242798, 0.9139499962329865]174711577117009.73%-0.0866
5(0.9139499962329865, inf]872481106147.04%0.0537
useratemore70_m6_num — IV 0.0128,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]10817101466716.20%0.1032
2(0.5, 1.5]443541153207.22%0.0267
3(1.5, 4.5]144121310413089.08%-0.0447
4(4.5, 5.5]346831323369.69%-0.0284
5(5.5, inf]4928441451410.43%-0.0571
odgt0_m12_num — IV 0.0127,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]1326811926134210.11%-0.0957
2(0.5, 1.5]773771006378.23%0.0015
3(1.5, 2.5]553450984367.88%0.0118
4(2.5, 5.5]832177475746.90%0.0565
5(5.5, inf]320030401605.00%0.0638
useratemore50maxcontimonsm12 — IV 0.0122,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]407638891874.59%0.0889
2(0.5, 1.5]200318701336.64%0.0207
3(1.5, 2.5]228621651215.29%0.0429
4(2.5, 4.5]589354014928.35%-0.0023
5(4.5, inf]238022158622169.31%-0.0736
odgt0_m12_mob_pc — IV 0.0121,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 4.164999961853027]1327211930134210.11%-0.0956
2(4.164999961853027, 20.130000114440918]125321151210208.14%0.0071
3(20.130000114440918, 37.14500045776367]653261104226.46%0.0627
4(37.14500045776367, 57.670000076293945]347132192527.26%0.0208
5(57.670000076293945, inf]225321401135.02%0.0463
min_tnr — IV 0.0121,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.5]268824342549.45%-0.0190
2(1.5, 5.0]202611882614357.08%0.0837
3(5.0, 8.5]301227372759.13%-0.0153
4(8.5, inf]121191093311869.79%-0.0752
cre_now_l60_used_amt_d_min — IV 0.0121,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.000950038433075]279432520527389.80%-0.0698
2(1.000950038433075, 1.4549500346183777]235622351215.14%0.0572
3(1.4549500346183777, 2.305649995803833]18601789713.82%0.0629
4(2.305649995803833, inf]202619261004.94%0.0527
cre_now_l30_limit_left_d_min — IV 0.0114,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.26759999990463257]261323772369.03%-0.0106
2(0.26759999990463257, 0.997050017118454]3523306645712.97%-0.0931
3(0.997050017118454, 1.1242499947547913]137731277010037.28%0.0632
4(1.1242499947547913, 1.7257500290870667]116271058510428.96%-0.0291
5(1.7257500290870667, inf]493946203196.46%0.0546
max_loan_os_prcp_m12 — IV 0.0113,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1747.2849731445312]410138602415.88%0.0574
2(1747.2849731445312, 2010.25]280625622448.70%-0.0071
3(2010.25, 13572.5849609375]224802076617147.62%0.0473
4(13572.5849609375, 20848.58984375]361932783419.42%-0.0239
5(20848.58984375, inf]5054444560912.05%-0.1001
repay_amount_m6_all_shd_amt_pc — IV 0.0111,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 93.98500061035156]132571194613119.89%-0.0844
2(93.98500061035156, 95.59499740600586]303328122217.29%0.0180
3(95.59499740600586, 96.48500061035156]297526942819.45%-0.0207
4(96.48500061035156, 99.48500061035156]137351268710487.63%0.0361
5(99.48500061035156, inf]506047722885.69%0.0737
setl_rem_prcp_paym_m3_num — IV 0.0110,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]320942924028548.89%-0.0501
2(0.5, inf]596656712954.94%0.1096
orig_prcp_avg_m12 — IV 0.0107,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1031.9722290039062]11498107357636.64%0.0841
2(1031.9722290039062, 1871.875]692564055207.51%0.0271
3(1871.875, 3819.857177734375]872779937348.41%-0.0057
4(3819.857177734375, 13787.5]890980418689.74%-0.0603
5(13787.5, inf]2021175626513.11%-0.0597
avg_tnr — IV 0.0106,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 3.5]24362340963.94%0.0666
2(3.5, 5.5]367234422306.26%0.0436
3(5.5, 6.5]266024721887.07%0.0196
4(6.5, 10.5]126711164510268.10%0.0092
5(10.5, inf]166411503116109.67%-0.0833
ps_int_amt_sum — IV 0.0105,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 209.51499938964844]317330021715.39%0.0555
2(209.51499938964844, 815.2900085449219]1035696177397.14%0.0539
3(815.2900085449219, 1891.7449951171875]1042996138167.82%0.0211
4(1891.7449951171875, 10533.93994140625]113161027610409.19%-0.0443
5(10533.93994140625, inf]2806242238413.69%-0.0883
m_s_ps_instm_amt — IV 0.0103,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 33.55999946594238]268902491619747.34%0.0741
2(33.55999946594238, 371.93499755859375]5271473953210.09%-0.0509
3(371.93499755859375, 614.2250061035156]2004177423011.48%-0.0396
4(614.2250061035156, 1121.7000122070312]196017851758.93%-0.0080
5(1121.7000122070312, inf]1955171623912.23%-0.0476
useratemore70monthsubcurmonth — IV 0.0101,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]136451244412018.80%-0.0287
2(0.5, 2.5]658659736139.31%-0.0345
3(2.5, 4.5]519846855139.87%-0.0443
4(4.5, 9.5]603755644737.83%0.0140
5(9.5, inf]659462453495.29%0.1056
cre_now_p1m_used_rate_d — IV 0.0099,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.6786499917507172]654861234256.49%0.0730
2(0.6786499917507172, 0.9951499998569489]218641984220229.25%-0.0466
3(0.9951499998569489, 1.0000500082969666]1839157826114.19%-0.0649
4(1.0000500082969666, 1.7942500114440918]380435272777.28%0.0291
5(1.7942500114440918, inf]18851790955.04%0.0436
cre_now_l60_used_amt_m_max — IV 0.0098,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 83.30500030517578]514849042444.74%0.1035
2(83.30500030517578, 1001.9599914550781]169371556813698.08%0.0120
3(1001.9599914550781, 2003.010009765625]715165156368.89%-0.0221
4(2003.010009765625, 2696.469970703125]2318205426411.39%-0.0437
5(2696.469970703125, inf]651158746379.78%-0.0496
loan_os_prcp_gt0_m3_num_pc — IV 0.0091,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 68.16500091552734]335432521023.04%0.1081
2(68.16500091552734, inf]347063165930478.78%-0.0423
useratemore90maxcontimonsm12 — IV 0.0090,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]929887235756.18%0.0940
2(0.5, 1.5]690363495548.03%0.0087
3(1.5, 4.5]147501346112898.74%-0.0265
4(4.5, 7.5]465241884649.97%-0.0432
5(7.5, inf]2457219026710.87%-0.0384
cre_now_p1m_used_rate_m — IV 0.0089,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -0.13974999636411667]513748073306.42%0.0538
2(-0.13974999636411667, -4.999999873689376e-05]21512063884.09%0.0579
3(-4.999999873689376e-05, 0.0002500000045984052]1903165724612.93%-0.0546
4(0.0002500000045984052, 0.04154999926686287]429440022926.80%0.0369
5(0.04154999926686287, inf]242492207621738.96%-0.0485
last_clear_num_m3 — IV 0.0087,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]219561990820489.33%-0.0723
2(0.5, 1.5]704365255187.35%0.0331
3(1.5, 2.5]341731772407.02%0.0253
4(2.5, 3.5]203219031296.35%0.0247
5(3.5, inf]363234172155.92%0.0507
cre_l30_l90_usedrate_m_max — IV 0.0087,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.025150000117719173]11879110807996.73%0.0811
2(0.025150000117719173, 0.0799499973654747]331030532577.76%0.0100
3(0.0799499973654747, 0.1587500050663948]6612594866410.04%-0.0586
4(0.1587500050663948, 0.5746999979019165]143061303312738.90%-0.0347
5(0.5746999979019165, inf]195818011578.02%0.0032
cre_l30_l90_used_amt_m_min — IV 0.0087,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.6299999952316284]298562718526718.95%-0.0528
2(0.6299999952316284, 1107.5999755859375]285827421164.06%0.0748
3(1107.5999755859375, 5082.195068359375]325830821765.40%0.0566
4(5082.195068359375, inf]209319061878.93%-0.0086
useratemore90_m3_num — IV 0.0084,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]232662150117657.59%0.0509
2(0.5, 1.5]611756464717.70%0.0185
3(1.5, 2.5]397936233568.95%-0.0152
4(2.5, inf]4698414155711.86%-0.0900
ps_int_amt_avg — IV 0.0082,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 4.333299875259399]408338572265.54%0.0655
2(4.333299875259399, 13.080849647521973]12227113149137.47%0.0422
3(13.080849647521973, 15.02239990234375]204518412049.98%-0.0216
4(15.02239990234375, 38.24515151977539]123061126510418.46%-0.0096
5(38.24515151977539, inf]7419665376610.32%-0.0736
cre_usedrate_u30_daydelta_max — IV 0.0079,3 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 57.5]282927001294.56%0.0781
2(57.5, 85.5]211219921205.68%0.0435
3(85.5, inf]283912574126509.33%-0.0495
min_apply_amt — IV 0.0074,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1135.0]3388301037811.16%-0.0561
2(1135.0, 2270.0]514247344087.93%0.0095
3(2270.0, 4180.0]128411167911629.05%-0.0406
4(4180.0, 7300.0]922184907317.93%0.0149
5(7300.0, inf]748870174716.29%0.0761
cre_now_p2m_used_rate_m — IV 0.0071,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -0.11755000054836273]793973805597.04%0.0504
2(-0.11755000054836273, -0.00014999999621068127]239722681295.38%0.0443
3(-0.00014999999621068127, 0.0799499973654747]533549014348.13%0.0049
4(0.0799499973654747, 0.35944999754428864]170241542615989.39%-0.0659
5(0.35944999754428864, inf]476243723908.19%0.0030
cre_now_p3m_used_rate_d — IV 0.0071,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.40674999356269836]436340892746.28%0.0653
2(0.40674999356269836, 0.5166500210762024]454141643778.30%0.0116
3(0.5166500210762024, 0.8346999883651733]128661159012769.92%-0.0626
4(0.8346999883651733, 1.7775499820709229]847277047689.07%-0.0138
5(1.7775499820709229, inf]334331042397.15%0.0335
cre_now_l60_usedrate_m_max — IV 0.0069,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 4.999999873689376e-05]509447493456.77%0.0425
2(4.999999873689376e-05, 0.039750000461936]263224991335.05%0.0527
3(0.039750000461936, 0.08044999837875366]307928462337.57%0.0131
4(0.08044999837875366, 0.5794999897480011]244692224522249.09%-0.0588
5(0.5794999897480011, inf]279125762157.70%0.0097
repay_amount_all_shd_amt_pc — IV 0.0068,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -4999.0]215920171426.58%0.0230
2(-4999.0, 90.52499771118164]920783069019.79%-0.0633
3(90.52499771118164, 97.21500015258789]160891468914008.70%-0.0256
4(97.21500015258789, 98.58499908447266]698264825007.16%0.0400
5(98.58499908447266, inf]362334172065.69%0.0558
account_age — IV 0.0064,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 21.5]178221650113217.41%0.0562
2(21.5, 24.5]323129502818.70%-0.0081
3(24.5, 29.5]428339473367.85%0.0104
4(29.5, 81.5]996589939729.75%-0.0652
5(81.5, inf]275925202398.66%-0.0065
shd_pre_repay_cnt — IV 0.0061,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 25.5]956088766847.15%0.0504
2(25.5, 91.5]11526105489788.49%-0.0104
3(91.5, 237.5]753169775547.36%0.0348
4(237.5, 362.5]253723142238.79%-0.0080
5(362.5, inf]6905619571010.28%-0.0685
repay_amount_m6_loan_os_prcp_pc — IV 0.0055,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -4999.0]682863534756.96%0.0467
2(-4999.0, 51.885000228881836]1923168224112.53%-0.0504
3(51.885000228881836, 61.88999938964844]2837253829910.54%-0.0381
4(61.88999938964844, 93.5250015258789]578952605299.14%-0.0263
5(93.5250015258789, inf]206831907816057.76%0.0358
grade_limit_amount — IV 0.0055,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 84500.0]2178194523310.70%-0.0324
2(84500.0, 115500.0]941686567608.07%0.0088
3(115500.0, 137500.0]203319001336.54%0.0222
4(137500.0, 180500.0]6132550163110.29%-0.0631
5(180500.0, inf]183211692813937.60%0.0440
tothismonthodcontiaddnumm12 — IV 0.0054,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]330573046325947.85%0.0362
2(0.5, inf]5003444855511.09%-0.0750
shd_l180_instm_amt_sum — IV 0.0052,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 5366.869873046875]147451367710687.24%0.0608
2(5366.869873046875, 6463.929931640625]205118541979.61%-0.0169
3(6463.929931640625, 34552.490234375]166591528313768.26%0.0009
4(34552.490234375, 55994.666015625]2458220725110.21%-0.0289
5(55994.666015625, inf]2146188925711.98%-0.0484
tothismonthodcontireducenumm12 — IV 0.0050,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]328993004428558.68%-0.0333
2(0.5, inf]516148672945.70%0.0747
max_int_rat — IV 0.0048,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.2142000049352646]372734912366.33%0.0426
2(0.2142000049352646, 0.2332499995827675]1080998809298.59%-0.0153
3(0.2332499995827675, 0.23605000227689743]1006891099599.53%-0.0558
4(0.23605000227689743, inf]134761245010267.61%0.0365
last_clear_num_m1 — IV 0.0047,3 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]301612750926528.79%-0.0414
2(0.5, 1.5]491645943226.55%0.0475
3(1.5, inf]300328271765.86%0.0441
shd_l90_ps_due_cnt — IV 0.0046,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 2.5]248623831034.14%0.0646
2(2.5, 5.5]935585747818.35%-0.0032
3(5.5, 9.5]879379678269.39%-0.0457
4(9.5, 17.5]708265465367.57%0.0255
5(17.5, inf]1034394409038.73%-0.0210
ps_prcp_amt_mon — IV 0.0046,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 38.48500061035156]206919661034.98%0.0433
2(38.48500061035156, 955.4700012207031]225732080117727.85%0.0306
3(955.4700012207031, 2836.0150146484375]911382578569.39%-0.0469
4(2836.0150146484375, 4656.4951171875]226720851828.03%0.0034
5(4656.4951171875, inf]2058182123711.52%-0.0410
shd_instm_amt_sum — IV 0.0045,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 14048.51513671875]12742117869567.50%0.0415
2(14048.51513671875, 17727.4052734375]271225471656.08%0.0365
3(17727.4052734375, 134568.0234375]178261634114858.33%-0.0036
4(134568.0234375, 248682.5859375]2691240928210.48%-0.0355
5(248682.5859375, inf]2088182726112.50%-0.0538
shd_l60_min_dpd — IV 0.0045,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -286.5]11318103389808.66%-0.0135
2(-286.5, -151.5]205219031497.26%0.0146
3(-151.5, -0.5]18831799844.46%0.0480
4(-0.5, 0.5]189651742415418.13%0.0171
5(0.5, inf]2917255835912.31%-0.0675
shd_remain_actual_cnt — IV 0.0045,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 2.5]433940353047.01%0.0314
2(2.5, 3.5]279026271635.84%0.0417
3(3.5, 5.5]413137923398.21%0.0016
4(5.5, 35.5]218761990819689.00%-0.0498
5(35.5, inf]492345483757.62%0.0179
odgt0_m3_num — IV 0.0044,4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]204941889715977.79%0.0333
2(0.5, 1.5]956088227387.72%0.0247
3(1.5, 2.5]536648824849.02%-0.0214
4(2.5, inf]2640231033012.50%-0.0660
loan_os_prcp_gt0_m12_num_pc — IV 0.0039,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 57.73500061035156]329831381604.85%0.0685
2(57.73500061035156, 72.08000183105469]263124172148.13%0.0022
3(72.08000183105469, 76.01499938964844]196117841779.03%-0.0092
4(76.01499938964844, 92.31500244140625]664060945468.22%0.0017
5(92.31500244140625, inf]235302147820528.72%-0.0321
account_age_loan_day — IV 0.0039,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 2.603700041770935]140391283012098.61%-0.0188
2(2.603700041770935, 6.708349943161011]931986676527.00%0.0566
3(6.708349943161011, 10.562049865722656]397036613097.78%0.0112
4(10.562049865722656, 25.645400047302246]575552005559.64%-0.0412
5(25.645400047302246, inf]497745534248.52%-0.0067
end_loan_to_rep_loan_freq — IV 0.0037,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1003.5]286772641922587.87%0.0320
2(1003.5, 1935.5]201218191939.59%-0.0165
3(1935.5, 2132.5]2266198428212.44%-0.0571
4(2132.5, 2322.5]266624172499.34%-0.0172
5(2322.5, inf]245922911686.83%0.0219
min_apprv_amt — IV 0.0037,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.25]125741144611288.97%-0.0361
2(1.25, 127.5]748469705146.87%0.0534
3(127.5, 424.5]499445784168.33%-0.0016
4(424.5, 1202.0]667261545187.76%0.0175
5(1202.0, inf]635657825749.03%-0.0248
sum_apply_amt — IV 0.0034,5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 4180.0]181321653116018.83%-0.0353
2(4180.0, 7925.0]988690877998.08%0.0086
3(7925.0, 11214.5]558952263636.49%0.0544
4(11214.5, 15038.6298828125]248022901907.66%0.0093
5(15038.6298828125, inf]199317961979.88%-0.0200
last_apply_freq — IV 0.0034,3 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 6.5]333023067926237.88%0.0336
2(6.5, 498.5]2175192425111.54%-0.0434
3(498.5, inf]2603232727610.60%-0.0364
bh_cur_od_num — IV 0.0031,2 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -49999.5]150401368213589.03%-0.0433
2(-49999.5, inf]230402124817927.78%0.0362

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 100 个变量,共 124 个;完整数据见 feature_report.json。

04 单变量分析(粗分箱)

f_ps_od_days_max — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2042218144227811.15%-0.1822
2(0.5, 1.5]844180024395.20%0.1313
3(1.5, 2.5]342032751454.24%0.0838
4(2.5, 4.5]359034531373.82%0.0970
5(4.5, inf]220720561516.84%0.0197
2026-10-20T14:32:50.445655 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(11.15% → 11.15% → 6.84%),如需严格单调可考虑调整切点或合并分箱。IV=0.0585,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 4→5 箱有局部反弹:Bad Rate 由 3.82% 回升至 6.84%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 11.15%,可作为拒绝或重点风控策略的阈值参考

t_ps_od_days_max — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2063318517211610.26%-0.1288
2(0.5, 2.5]11097105245735.16%0.1613
3(2.5, 3.5]20481977713.47%0.0631
4(3.5, 5.5]219720751225.55%0.0377
5(5.5, inf]2105183726812.73%-0.0571
2026-10-20T14:32:50.568301 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.26% → 12.73% → 12.73%),如需严格单调可考虑调整切点或合并分箱。IV=0.0423,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 1→2 箱有局部反弹:Bad Rate 由 10.26% 回落至 5.16%,如需严格单调可考虑合并这两箱

第 5 箱((5.5, inf])为坏率最高区间:坏率高达 12.73%,可作为拒绝或重点风控策略的阈值参考

s_ps_od_days_max — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2061018430218010.58%-0.1484
2(0.5, 1.5]795175284235.32%0.1205
3(1.5, 2.5]346533031624.68%0.0753
4(2.5, 4.5]349433261684.81%0.0730
5(4.5, inf]256023432178.48%-0.0032
2026-10-20T14:32:50.688305 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.58% → 10.58% → 8.48%),如需严格单调可考虑调整切点或合并分箱。IV=0.0405,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 3→4 箱有局部反弹:Bad Rate 由 4.68% 回升至 4.81%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 10.58%,可作为拒绝或重点风控策略的阈值参考

available_limit_amt — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.03499999921768904]1238510918146711.85%-0.1727
2(0.03499999921768904, 468.864990234375]452342472766.10%0.0562
3(468.864990234375, 4307.300048828125]11998111488507.08%0.0621
4(4307.300048828125, 27316.265625]725067884626.37%0.0711
5(27316.265625, inf]19241829954.94%0.0410
2026-10-20T14:32:50.812274 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(11.85% → 11.85% → 4.94%),如需严格单调可考虑调整切点或合并分箱。IV=0.0357,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 2→3 箱有局部反弹:Bad Rate 由 6.10% 回升至 7.08%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.03499999921768904])为坏率最高区间:坏率高达 11.85%,可作为拒绝或重点风控策略的阈值参考

apprv_num_m3 — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]2013918040209910.42%-0.1376
2(0.5, 1.5]663762224156.25%0.0708
3(1.5, 2.5]356333532105.89%0.0505
4(2.5, 4.5]361034311794.96%0.0717
5(4.5, inf]413138842475.98%0.0551
2026-10-20T14:32:50.934321 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.42% → 10.42% → 5.98%),如需严格单调可考虑调整切点或合并分箱。IV=0.0302,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 4→5 箱有局部反弹:Bad Rate 由 4.96% 回升至 5.98%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 10.42%,可作为拒绝或重点风控策略的阈值参考

loan_os_prcp_credit_amount_m3 — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, -4999.0]3677329937810.28%-0.0421
2(-4999.0, 35.125]831579333824.59%0.1574
3(35.125, 100.47500228881836]191161761015067.88%0.0264
4(100.47500228881836, 124.34499740600586]2717241230511.23%-0.0476
5(124.34499740600586, inf]4235365757813.65%-0.1225
2026-10-20T14:32:51.053564 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.28% → 13.65% → 13.65%),如需严格单调可考虑调整切点或合并分箱。IV=0.0294,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 1→2 箱有局部反弹:Bad Rate 由 10.28% 回落至 4.59%,如需严格单调可考虑合并这两箱

第 5 箱((124.34499740600586, inf])为坏率最高区间:坏率高达 13.65%,可作为拒绝或重点风控策略的阈值参考

suc_apprv_num_m1 — 3 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.5]301692728728829.55%-0.0993
2(0.5, 1.5]478745911964.09%0.1161
3(1.5, inf]31243052722.30%0.1164
2026-10-20T14:32:51.172074 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性良好:随分栏增大,Bad Rate 单调下降(9.55% → 2.30%),WOE 单调上升(-0.0993 → 0.1164),符合风控分箱预期。IV=0.0288,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 2 箱 WOE<0(风险高于平均)

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 9.55%,可作为拒绝或重点风控策略的阈值参考

cre_l60_used_limit_rate_min — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 0.019700000062584877]444143061353.04%0.1382
2(0.019700000062584877, 0.09174999967217445]281326561575.58%0.0466
3(0.09174999967217445, 0.2787500023841858]732368075167.05%0.0459
4(0.2787500023841858, 0.9161500036716461]188991715717429.22%-0.0603
5(0.9161500036716461, inf]4589398960013.07%-0.1170
2026-10-20T14:32:51.288593 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性良好:随分栏增大,Bad Rate 单调上升(3.04% → 13.07%),WOE 单调下降(0.1382 → -0.1170),符合风控分箱预期。IV=0.0264,该变量区分度偏弱但可用。

WOE 在第 3、4 箱之间穿越 0 线:前 3 箱 WOE>0(客户质量优于整体),后 2 箱 WOE<0(风险高于平均)

第 5 箱((0.9161500036716461, inf])为坏率最高区间:坏率高达 13.07%,可作为拒绝或重点风控策略的阈值参考

cre_now_l60_used_amt_m_min — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 1.7799999713897705]282012545827439.73%-0.1091
2(1.7799999713897705, 869.5950012207031]247623681084.36%0.0609
3(869.5950012207031, 1999.7100219726562]20602009512.48%0.0771
4(1999.7100219726562, 6462.93505859375]312530091163.71%0.0880
5(6462.93505859375, inf]220320711325.99%0.0316
2026-10-20T14:32:51.421277 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(9.73% → 9.73% → 5.99%),如需严格单调可考虑调整切点或合并分箱。IV=0.0256,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 3→4 箱有局部反弹:Bad Rate 由 2.48% 回升至 3.71%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 1.7799999713897705])为坏率最高区间:坏率高达 9.73%,可作为拒绝或重点风控策略的阈值参考

apprv_amt_day — 4 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 11.0]303442745228929.53%-0.0978
2(11.0, 1000.5]25062421853.39%0.0773
3(1000.5, 5995.0]33043220842.54%0.1172
4(5995.0, inf]19261837894.62%0.0450
2026-10-20T14:32:51.546932 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(9.53% → 9.53% → 4.62%),如需严格单调可考虑调整切点或合并分箱。IV=0.0250,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 3 箱 WOE<0(风险高于平均)

第 3→4 箱有局部反弹:Bad Rate 由 2.54% 回升至 4.62%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 11.0])为坏率最高区间:坏率高达 9.53%,可作为拒绝或重点风控策略的阈值参考

loan_os_prcp_credit_amount_m6 — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 4.129999876022339]191717931246.47%0.0220
2(4.129999876022339, 33.795000076293945]621059412694.33%0.1352
3(33.795000076293945, 48.94499969482422]443741412966.67%0.0406
4(48.94499969482422, 107.59499740600586]187351707416618.87%-0.0381
5(107.59499740600586, inf]6761596279911.82%-0.1166
2026-10-20T14:32:51.670180 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(6.47% → 11.82% → 11.82%),如需严格单调可考虑调整切点或合并分箱。IV=0.0239,该变量区分度偏弱但可用。

WOE 在第 3、4 箱之间穿越 0 线:前 3 箱 WOE>0(客户质量优于整体),后 2 箱 WOE<0(风险高于平均)

第 1→2 箱有局部反弹:Bad Rate 由 6.47% 回落至 4.33%,如需严格单调可考虑合并这两箱

第 5 箱((107.59499740600586, inf])为坏率最高区间:坏率高达 11.82%,可作为拒绝或重点风控策略的阈值参考

cre_l90_used_limit_amt_min — 5 箱
分组号分栏TotalGoodBadBad RateWOE
1(-inf, 21.640000343322754]561854082103.74%0.1447
2(21.640000343322754, 748.7099914550781]807675265506.81%0.0589
3(748.7099914550781, 8516.22998046875]201721835418189.01%-0.0490
4(8516.22998046875, 14597.384765625]2267199027712.22%-0.0541
5(14597.384765625, inf]1932163729515.27%-0.0821
2026-10-20T14:32:51.851885 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性良好:随分栏增大,Bad Rate 单调上升(3.74% → 15.27%),WOE 单调下降(0.1447 → -0.0821),符合风控分箱预期。IV=0.0232,该变量区分度偏弱但可用。

WOE 在第 2、3 箱之间穿越 0 线:前 2 箱 WOE>0(客户质量优于整体),后 3 箱 WOE<0(风险高于平均)

第 5 箱((14597.384765625, inf])为坏率最高区间:坏率高达 15.27%,可作为拒绝或重点风控策略的阈值参考

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0.95
相关性上限(皮尔逊)0.7
PSI 上限0.25
重要性 Top-K80
黑名单due_day_my
白名单无

候选变量 125,成功分箱 124,入模 12

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
ps_perd_no—N0.0308PASSPASSPASS—0.3217PSI>0.25
due_day_my—N——————黑名单
age—N0.0010PASSPASSFAIL——IV<0.02
max_int_rat—N0.0048PASSPASSFAIL——IV<0.02
min_int_rat—N0.0009PASSPASSFAIL——IV<0.02
avg_tnr—N0.0106PASSPASSFAIL——IV<0.02
min_tnr—N0.0121PASSPASSFAIL——IV<0.02
sum_apply_amt—N0.0034PASSPASSFAIL——IV<0.02
min_apply_amt—N0.0074PASSPASSFAIL——IV<0.02
min_apprv_amt—N0.0037PASSPASSFAIL——IV<0.02
apprv_amt_day—Y0.0250PASSPASSPASSPASS0.1356
end_loan_to_rep_loan_freq—N0.0037PASSPASSFAIL——IV<0.02
end_loan_to_cur_freq—N0.0457PASSPASSPASS—0.2531PSI>0.25
f_rep_loan_to_f_apply_dt_freq—N0.0011PASSPASSFAIL——IV<0.02
ps_prcp_amt_mon—N0.0046PASSPASSFAIL——IV<0.02
ps_int_amt_mon—N0.0136PASSPASSFAIL——IV<0.02
ps_int_amt_sum—N0.0105PASSPASSFAIL——IV<0.02
ps_prcp_amt_avg—N0.0015PASSPASSFAIL——IV<0.02
ps_int_amt_avg—N0.0082PASSPASSFAIL——IV<0.02
setl_prcp_mon_ratio—N0.0024PASSPASSFAIL——IV<0.02
acc_ps_perd_no—N0.0247PASSPASSPASS—0.4588PSI>0.25
max_od_days—N0.0930PASSPASSPASS—0.5635PSI>0.25
m_s_ps_instm_amt—N0.0103PASSPASSFAIL——IV<0.02
f_ps_od_days_max—Y0.0585PASSPASSPASSPASS0.1507
s_ps_od_days_max—Y0.0405PASSPASSPASSPASS0.1952
t_ps_od_days_max—Y0.0423PASSPASSPASSPASS0.2430
ovd_days_d3_num_m1—N0.0484PASSPASSPASS—0.4567PSI>0.25
orig_prcp_avg_m3—N0.0438PASSPASSPASS—0.2678PSI>0.25
orig_prcp_avg_m12—N0.0107PASSPASSFAIL——IV<0.02
suc_apply_trench_num—N0.0016PASSPASSFAIL——IV<0.02
suc_apply_top_pc_code_num—N0.0011PASSPASSFAIL——IV<0.02
suc_apprv_num_m1—Y0.0288PASSPASSPASSPASS0.1386
apprv_num_m1—N0.0268PASSPASSPASSFAIL0.1088与 apprv_num_m3 相关>0.7
suc_apply_num_m3—N0.0000PASSFAIL———集中度>0.95
apprv_num_m3—Y0.0302PASSPASSPASSPASS0.2416
suc_apprv_num_m6—N0.0138PASSPASSFAIL——IV<0.02
apply_num_m12—N0.0002PASSPASSFAIL——IV<0.02
last_apply_od_num_m12—N0.0015PASSPASSFAIL——IV<0.02
last_apply_freq—N0.0034PASSPASSFAIL——IV<0.02
dec_loan_num—N0.0004PASSPASSFAIL——IV<0.02
bh_cur_od_num—N0.0031PASSPASSFAIL——IV<0.02
hj_cur_od_num—N0.0000PASSPASSFAIL——IV<0.02
setl_prcp_ratio—N0.0338PASSPASSPASS—0.2983PSI>0.25
last_loan_setl_tnr—N0.0380PASSPASSPASS—0.2903PSI>0.25
last_od_num_m6—N0.0306PASSPASSPASS—0.6013PSI>0.25
last_od_to_cur_freq—N0.0513PASSPASSPASS—0.8376PSI>0.25
last_clear_num_m1—N0.0047PASSPASSFAIL——IV<0.02
last_clear_num_m3—N0.0087PASSPASSFAIL——IV<0.02
grade_limit_amount—N0.0055PASSPASSFAIL——IV<0.02
exposure—N0.0029PASSPASSFAIL——IV<0.02
available_limit_amt—Y0.0357PASSPASSPASSPASS0.0138
account_age—N0.0064PASSPASSFAIL——IV<0.02
account_age_loan_day—N0.0039PASSPASSFAIL——IV<0.02
max_od_due—N0.0279PASSPASSPASS—0.4345PSI>0.25
odgt0_m12_mob_pc—N0.0121PASSPASSFAIL——IV<0.02
odgt0_m3_num—N0.0044PASSPASSFAIL——IV<0.02
odgt0_m12_num—N0.0127PASSPASSFAIL——IV<0.02
odgt0_m12_subcurmonth—N0.0471PASSPASSPASS—2.5210PSI>0.25
tothismonthodcontiaddnumm12—N0.0054PASSPASSFAIL——IV<0.02
tothismonthodcontireducenumm12—N0.0050PASSPASSFAIL——IV<0.02
od_amt_m6_loan_os_prcp_m6_pc—N0.0163PASSPASSFAIL——IV<0.02
od_amt_m12_loan_os_prcp_m12_pc—N0.0143PASSPASSFAIL——IV<0.02
avg_od_amt_m6_orig_prcp_pc—N0.0166PASSPASSFAIL——IV<0.02
max_loan_os_prcp_m12—N0.0113PASSPASSFAIL——IV<0.02
loan_os_prcp_gt0_m3_num_pc—N0.0091PASSPASSFAIL——IV<0.02
loan_os_prcp_gt0_m12_num_pc—N0.0039PASSPASSFAIL——IV<0.02
repay_amount_m3_loan_os_prcp_pc—N0.0159PASSPASSFAIL——IV<0.02
repay_amount_m6_loan_os_prcp_pc—N0.0055PASSPASSFAIL——IV<0.02
repay_amount_all_shd_amt_pc—N0.0068PASSPASSFAIL——IV<0.02
repay_amount_m6_all_shd_amt_pc—N0.0111PASSPASSFAIL——IV<0.02
setl_rem_prcp_paym_last_month_lo—N0.0028PASSPASSFAIL——IV<0.02
setl_rem_prcp_paym_m12_loan_os_p—N0.0012PASSPASSFAIL——IV<0.02
setl_rem_prcp_paym_m3_num—N0.0110PASSPASSFAIL——IV<0.02
setl_rem_prcp_paym_m12_num—N0.0007PASSPASSFAIL——IV<0.02
loan_os_prcp_credit_amount_m3—Y0.0294PASSPASSPASSPASS0.0733
loan_os_prcp_credit_amount_m6—Y0.0239PASSPASSPASSPASS0.0433
loan_os_prcp_credit_amount_m12—N0.0153PASSPASSFAIL——IV<0.02
useratemore50maxcontimonsm12—N0.0122PASSPASSFAIL——IV<0.02
useratemore70_m6_num—N0.0128PASSPASSFAIL——IV<0.02
useratemore70monthsubcurmonth—N0.0101PASSPASSFAIL——IV<0.02
useratemore90_m3_num—N0.0084PASSPASSFAIL——IV<0.02
useratemore90maxcontimonsm12—N0.0090PASSPASSFAIL——IV<0.02
shd_max_dpd—N0.0301PASSPASSPASS—0.3133PSI>0.25
shd_min_dpd—N0.0021PASSPASSFAIL——IV<0.02
shd_pre_repay_cnt—N0.0061PASSPASSFAIL——IV<0.02
shd_perd_max—N0.0016PASSPASSFAIL——IV<0.02
shd_instm_amt_sum—N0.0045PASSPASS———唯一率过高(ID列)
shd_l30_max_dpd—N0.0247PASSPASSPASS—1.1956PSI>0.25
shd_l60_min_dpd—N0.0045PASSPASSFAIL——IV<0.02
shd_l90_ps_due_cnt—N0.0046PASSPASSFAIL——IV<0.02
shd_l180_max_dpd—N0.0021PASSPASSFAIL——IV<0.02
shd_l180_instm_amt_sum—N0.0052PASSPASS———唯一率过高(ID列)
shd_remain_actual_cnt—N0.0045PASSPASSFAIL——IV<0.02
shd_pre_repay_cnt_rate—N0.0031PASSPASSFAIL——IV<0.02
shd_pre_repay_amt_rate—N0.0132PASSPASSFAIL——IV<0.02
shd_pre_repay_30d_amt_rate—N0.0007PASSPASSFAIL——IV<0.02
shd_pre_repay_due_rate—N0.0386PASSPASSPASS—0.3521PSI>0.25
shd_l30_pre_repay_due_rate—N0.0142PASSPASSFAIL——IV<0.02
shd_remain_actual_rate—N0.0018PASSPASSFAIL——IV<0.02
cre_usedrate_u30_daydelta_min—N0.0023PASSPASSFAIL——IV<0.02
cre_usedrate_u30_daydelta_max—N0.0079PASSPASSFAIL——IV<0.02
cre_l30_limit_left_amt_min—N0.0169PASSPASSFAIL——IV<0.02
cre_l60_used_limit_rate_max—N0.0132PASSPASSFAIL——IV<0.02
cre_l60_used_limit_rate_min—Y0.0264PASSPASSPASSPASS0.0410
cre_l90_used_limit_amt_min—Y0.0232PASSPASSPASSPASS0.0680
cre_now_p1m_used_rate_d—N0.0099PASSPASSFAIL——IV<0.02
cre_now_p3m_used_rate_d—N0.0071PASSPASSFAIL——IV<0.02
cre_now_p1m_used_rate_m—N0.0089PASSPASSFAIL——IV<0.02
cre_now_p2m_used_rate_m—N0.0071PASSPASSFAIL——IV<0.02
cre_now_l30_used_amt_d_max—N0.0129PASSPASSFAIL——IV<0.02
cre_now_l30_used_amt_d_min—N0.0132PASSPASSFAIL——IV<0.02
cre_now_l30_limit_left_d_max—N0.0155PASSPASSFAIL——IV<0.02
cre_now_l30_limit_left_d_min—N0.0114PASSPASSFAIL——IV<0.02
cre_now_l60_used_amt_d_min—N0.0121PASSPASSFAIL——IV<0.02
cre_now_l60_limit_left_d_max—N0.0188PASSPASSFAIL——IV<0.02
cre_now_l60_limit_left_d_min—N0.0154PASSPASSFAIL——IV<0.02
cre_now_l60_used_amt_m_max—N0.0098PASSPASSFAIL——IV<0.02
cre_now_l60_used_amt_m_min—Y0.0256PASSPASSPASSPASS0.0815
cre_now_l60_usedrate_m_max—N0.0069PASSPASSFAIL——IV<0.02
cre_now_l90_limit_left_d_min—N0.0151PASSPASSFAIL——IV<0.02
cre_l30_l90_used_amt_d_max—N0.0332PASSPASSPASS—0.3521PSI>0.25
cre_l30_l90_used_amt_m_max—N0.0252PASSPASSPASS—0.3031PSI>0.25
cre_l30_l90_used_amt_m_min—N0.0087PASSPASSFAIL——IV<0.02
cre_l30_l90_usedrate_m_max—N0.0087PASSPASSFAIL——IV<0.02
cre_l30_l90_usedrate_m_min—N0.0015PASSPASSFAIL——IV<0.02

06 回归结果

待补充:本实验未运行 LR 路线(或未产生回归结果),无回归明细。

07 VIF

待补充:本实验未运行 LR 路线,未计算 VIF/相关系数。

08 最终评分卡

待补充:本实验未生成评分卡(未运行 LR 路线)。

09 模型表现

模型区分度评估(按样本)

模型样本KSAUCGINI
LightGBM开发样本0.44740.80180.6036
LightGBM测试样本0.29900.70380.4076
LightGBM训练+测试样本0.38560.76250.5250
LightGBM跨时间验证样本0.29480.69460.3892

LightGBM — 4 样本评估表(score_cut 粒度)

开发样本(KS 0.0299,AUC 0.5134)

cutscntbadgoodbad_ratepopulation_pctcum_bad_ratecum_good_rate
[493, 560)38091175263430.85%10.00%37.29%7.54%
[560, 569)3809637317216.72%10.00%57.51%16.62%
[569, 575)3809396341310.40%10.00%70.07%26.39%
[575, 582)380833834708.88%10.00%80.80%36.32%
[582, 589)380923335766.12%10.00%88.19%46.56%
[589, 597)380913636733.57%10.00%92.51%57.07%
[597, 605)380812336853.23%10.00%96.41%67.62%
[605, 616)38097737322.02%10.00%98.86%78.30%
[616, 633)38093137780.81%10.00%99.84%89.11%
[633, 707)3809538040.13%10.00%100.00%100.00%
2026-10-20T14:32:51.985998 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:52.111619 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

测试样本(KS 0.0225,AUC 0.5058)

cutscntbadgoodbad_ratepopulation_pctcum_bad_ratecum_good_rate
[499, 561)2540492204819.37%10.00%23.43%8.79%
[561, 569)2539368217114.49%10.00%40.95%18.11%
[569, 575)2539307223212.09%10.00%55.57%27.70%
[575, 582)253923023099.06%10.00%66.52%37.61%
[582, 590)253922523148.86%10.00%77.24%47.55%
[590, 597)253916023796.30%10.00%84.86%57.76%
[597, 606)253913324065.24%10.00%91.19%68.09%
[606, 616)25399724423.82%10.00%95.81%78.58%
[616, 633)25396524742.56%10.00%98.90%89.20%
[633, 709)25392325160.91%10.00%100.00%100.00%
2026-10-20T14:32:52.242867 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:52.365509 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

训练+测试样本(KS 0.0159,AUC 0.5080)

cutscntbadgoodbad_ratepopulation_pctcum_bad_ratecum_good_rate
[493, 560)63481665468326.23%10.00%31.71%8.04%
[560, 569)63481010533815.91%10.00%50.94%17.21%
[569, 575)6348697565110.98%10.00%64.22%26.91%
[575, 582)634856857808.95%10.00%75.03%36.84%
[582, 590)634845958897.23%10.00%83.77%46.96%
[590, 597)634729260554.60%10.00%89.34%57.35%
[597, 606)634826260864.13%10.00%94.32%67.81%
[606, 616)634817361752.73%10.00%97.62%78.41%
[616, 633)63489762511.53%10.00%99.47%89.15%
[633, 709)63482863200.44%10.00%100.00%100.00%
2026-10-20T14:32:52.486955 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:52.608740 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

跨时间验证样本(KS 0.0148,AUC 0.4980)

cutscntbadgoodbad_ratepopulation_pctcum_bad_ratecum_good_rate
[511, 561)3473586288716.87%10.00%24.10%8.94%
[561, 569)3473437303612.58%10.00%42.06%18.34%
[569, 576)347333331409.59%10.00%55.76%28.06%
[576, 584)347328031938.06%10.00%67.27%37.95%
[584, 592)347321432596.16%10.00%76.07%48.04%
[592, 599)347316433094.72%10.00%82.81%58.28%
[599, 608)347314433294.15%10.00%88.73%68.59%
[608, 620)347313333403.83%10.00%94.20%78.93%
[620, 640)34738433892.42%10.00%97.66%89.42%
[640, 710)34735734161.64%10.00%100.00%100.00%
2026-10-20T14:32:52.735629 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:52.858485 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

跨时间验证样本结论

风险高度集中在低分尾端——最低 20% 样本集中了全量 42.1% 的坏客户,策略切分空间很大。

① 样本与分箱结构:共 34,730 样本 / 2,432 坏样本,整体坏率 7.00%,好坏比约 13.3:1;10 档等频分数分栏,每箱约 10%,分箱均匀,无空箱无过厚箱。

② 排序性与单调性:逐箱 Bad Rate 16.87% → … → 1.64%(低分 → 高分),无倒挂,最低分段坏率是最高分段的 10.3 倍。

③ 区分度与坏客户捕获:最低 20% 样本捕获全量 42.1% 的坏客户,最低 50% 捕获 76.1%;最高 20% 样本仅含 5.8% 的坏客户,其中风险最高一箱单独占 24.1%。

(口径:分数 = 按基准分/优比/PDO 刻度由模型概率转换,分数越高风险越低;结论由程序按分箱数据自动生成。)

注:score_cut 表按分数等频分 10 档(低分 → 高分):分数由模型概率按基准分/优比/PDO 刻度转换,分数越高风险越低;每表附 KS/AUC(按概率计算,与分栏口径无关);训练+测试 = TRAIN 全体。旧实验无分数转换时为 PD 等频口径。

10 KS和GINI

LightGBM

样本KSGINIAUC
开发样本0.44740.60360.8018
测试样本0.29900.40760.7038
训练+测试样本0.38560.52500.7625
跨时间验证样本0.29480.38920.6946

开发样本

2026-10-20T14:32:52.946319 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:53.073094 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

测试样本

2026-10-20T14:32:53.141177 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:53.210323 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

训练+测试样本

2026-10-20T14:32:53.280752 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:53.352765 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

跨时间验证样本

2026-10-20T14:32:53.422098 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:53.491265 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

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
LightGBM0.00030.0120—0.0077

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,0.0158]10.00%13.06%0.00820.0082
(0.0158,0.0284]10.00%10.60%0.00030.0085
(0.0284,0.0397]10.00%9.31%0.00050.0090
(0.0397,0.0527]10.00%10.26%0.00010.0091
(0.0527,0.0673]10.00%9.53%0.00020.0093
(0.0673,0.0849]10.00%9.01%0.00100.0103
(0.0849,0.1063]10.00%9.26%0.00060.0109
(0.1063,0.1292]10.00%10.26%0.00010.0110
(0.1292,0.1653]10.00%9.62%0.00010.0111
(0.1653,inf]10.00%9.09%0.00090.0120

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,0.0158]10.00%11.78%0.00290.0029
(0.0158,0.0284]10.00%10.89%0.00080.0037
(0.0284,0.0397]10.00%8.86%0.00140.0051
(0.0397,0.0527]10.00%10.08%0.00000.0051
(0.0527,0.0673]10.00%10.08%0.00000.0051
(0.0673,0.0849]10.00%9.26%0.00060.0057
(0.0849,0.1063]10.00%8.65%0.00190.0076
(0.1063,0.1292]10.00%10.15%0.00000.0076
(0.1292,0.1653]10.00%10.33%0.00010.0077
(0.1653,inf]10.00%9.91%0.00000.0077
2026-10-20T14:32:53.570716 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

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]380910.00%25299.96%63389.98%453613.06%205911.78%
(0.0158, 0.0284]380910.00%259710.23%640610.09%368010.60%190310.89%
(0.0284, 0.0397]380910.00%25149.90%63239.96%32339.31%15488.86%
(0.0397, 0.0527]380810.00%262110.32%642910.13%356210.26%176210.08%
(0.0527, 0.0673]380910.00%256910.12%637810.05%33119.53%176110.08%
(0.0673, 0.0849]380910.00%24809.77%62899.91%31289.01%16189.26%
(0.0849, 0.1063]380810.00%254010.00%634810.00%32179.26%15128.65%
(0.1063, 0.1292]380910.00%25369.99%634510.00%356510.26%177310.15%
(0.1292, 0.1653]380910.00%25129.89%63219.96%33409.62%180510.33%
(0.1653, inf]380910.00%24939.82%63029.93%31589.09%17329.91%
sum38088100.00%25391100.00%63479100.00%34730100.00%17473100.00%

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
t_ps_od_days_max0.2430关注
apprv_num_m30.2416关注
s_ps_od_days_max0.1952关注
f_ps_od_days_max0.1507关注
suc_apprv_num_m10.1386关注
apprv_amt_day0.1356关注
cre_now_l60_used_amt_m_min0.0815稳定
loan_os_prcp_credit_amount_m30.0733稳定
cre_l90_used_limit_amt_min0.0680稳定
loan_os_prcp_credit_amount_m60.0433稳定
cre_l60_used_limit_rate_min0.0410稳定
available_limit_amt0.0138稳定
f_ps_od_days_max — PSI 0.1507
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 0.5]53.63%71.67%18.04%0.0523
(0.5, 1.5]22.17%15.68%-6.49%0.0225
(1.5, 2.5]8.98%5.01%-3.97%0.0232
(2.5, 4.5]9.43%4.97%-4.45%0.0285
(4.5, inf]5.80%2.67%-3.12%0.0242
t_ps_od_days_max — PSI 0.2430
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 0.5]54.18%75.91%21.72%0.0732
(0.5, 2.5]29.14%17.99%-11.15%0.0538
(2.5, 3.5]5.38%2.30%-3.08%0.0261
(3.5, 5.5]5.77%2.56%-3.21%0.0261
(5.5, inf]5.53%1.25%-4.28%0.0637
s_ps_od_days_max — PSI 0.1952
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 0.5]54.12%74.07%19.95%0.0626
(0.5, 1.5]20.88%14.30%-6.58%0.0249
(1.5, 2.5]9.10%4.84%-4.26%0.0269
(2.5, 4.5]9.18%4.50%-4.68%0.0333
(4.5, inf]6.72%2.30%-4.42%0.0474
available_limit_amt — PSI 0.0138
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 0.03499999921768904]32.52%32.39%-0.14%0.0000
(0.03499999921768904, 468.864990234375]11.88%9.29%-2.59%0.0064
(468.864990234375, 4307.300048828125]31.51%30.87%-0.64%0.0001
(4307.300048828125, 27316.265625]19.04%20.46%1.42%0.0010
(27316.265625, inf]5.05%6.99%1.94%0.0063
apprv_num_m3 — PSI 0.2416
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 0.5]52.89%29.54%-23.35%0.1360
(0.5, 1.5]17.43%30.19%12.76%0.0701
(1.5, 2.5]9.36%14.08%4.72%0.0193
(2.5, 4.5]9.48%13.21%3.73%0.0124
(4.5, inf]10.85%12.99%2.14%0.0038
loan_os_prcp_credit_amount_m3 — PSI 0.0733
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, -4999.0]9.66%6.42%-3.24%0.0133
(-4999.0, 35.125]21.85%26.69%4.85%0.0097
(35.125, 100.47500228881836]50.23%48.56%-1.67%0.0006
(100.47500228881836, 124.34499740600586]7.14%2.99%-4.15%0.0362
(124.34499740600586, inf]11.13%15.35%4.22%0.0136
suc_apprv_num_m1 — PSI 0.1386
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 0.5]79.23%62.50%-16.73%0.0397
(0.5, 1.5]12.57%22.98%10.41%0.0628
(1.5, inf]8.20%14.52%6.32%0.0361
cre_l60_used_limit_rate_min — PSI 0.0410
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 0.019700000062584877]11.67%16.73%5.06%0.0182
(0.019700000062584877, 0.09174999967217445]7.39%8.24%0.84%0.0009
(0.09174999967217445, 0.2787500023841858]19.24%18.81%-0.43%0.0001
(0.2787500023841858, 0.9161500036716461]49.65%41.27%-8.38%0.0155
(0.9161500036716461, inf]12.06%14.96%2.90%0.0063
cre_now_l60_used_amt_m_min — PSI 0.0815
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 1.7799999713897705]74.09%61.70%-12.38%0.0227
(1.7799999713897705, 869.5950012207031]6.50%8.10%1.59%0.0035
(869.5950012207031, 1999.7100219726562]5.41%7.26%1.84%0.0054
(1999.7100219726562, 6462.93505859375]8.21%11.44%3.23%0.0107
(6462.93505859375, inf]5.79%11.50%5.72%0.0393
apprv_amt_day — PSI 0.1356
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 11.0]79.68%63.48%-16.21%0.0369
(11.0, 1000.5]6.58%11.57%4.99%0.0281
(1000.5, 5995.0]8.68%14.12%5.44%0.0265
(5995.0, inf]5.06%10.84%5.78%0.0441
loan_os_prcp_credit_amount_m6 — PSI 0.0433
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 4.129999876022339]5.04%6.36%1.32%0.0031
(4.129999876022339, 33.795000076293945]16.32%23.19%6.88%0.0242
(33.795000076293945, 48.94499969482422]11.66%12.11%0.45%0.0002
(48.94499969482422, 107.59499740600586]49.22%40.80%-8.43%0.0158
(107.59499740600586, inf]17.76%17.55%-0.21%0.0000
cre_l90_used_limit_amt_min — PSI 0.0680
分栏开发基准比例PSI时点样本 比例变更贡献
(-inf, 21.640000343322754]14.76%21.47%6.71%0.0251
(21.640000343322754, 748.7099914550781]21.22%17.21%-4.01%0.0084
(748.7099914550781, 8516.22998046875]52.99%45.70%-7.30%0.0108
(8516.22998046875, 14597.384765625]5.96%6.57%0.61%0.0006
(14597.384765625, inf]5.08%9.06%3.99%0.0231

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。

f_ps_od_days_max
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 0.5]2042253.63%18144227811.15%7.96
2(0.5, 1.5]844175.80%80024395.20%18.23
3(1.5, 2.5]342084.78%32751454.24%22.59
4(2.5, 4.5]359094.20%34531373.82%25.20
5(4.5, inf]2207100.00%20561516.84%13.62
合计380803493031508.27%11.09
2026-10-20T14:32:53.682004 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(11.15% → 11.15% → 6.84%),如需严格单调可考虑调整切点或合并分箱。IV=0.0585,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 4→5 箱有局部反弹:Bad Rate 由 3.82% 回升至 6.84%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 11.15%,可作为拒绝或重点风控策略的阈值参考

t_ps_od_days_max
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 0.5]2063354.18%18517211610.26%8.75
2(0.5, 2.5]1109783.32%105245735.16%18.37
3(2.5, 3.5]204888.70%1977713.47%27.85
4(3.5, 5.5]219794.47%20751225.55%17.01
5(5.5, inf]2105100.00%183726812.73%6.85
合计380803493031508.27%11.09
2026-10-20T14:32:53.802191 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.26% → 12.73% → 12.73%),如需严格单调可考虑调整切点或合并分箱。IV=0.0423,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 1→2 箱有局部反弹:Bad Rate 由 10.26% 回落至 5.16%,如需严格单调可考虑合并这两箱

第 5 箱((5.5, inf])为坏率最高区间:坏率高达 12.73%,可作为拒绝或重点风控策略的阈值参考

s_ps_od_days_max
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 0.5]2061054.12%18430218010.58%8.45
2(0.5, 1.5]795175.00%75284235.32%17.80
3(1.5, 2.5]346584.10%33031624.68%20.39
4(2.5, 4.5]349493.28%33261684.81%19.80
5(4.5, inf]2560100.00%23432178.48%10.80
合计380803493031508.27%11.09
2026-10-20T14:32:53.921287 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.58% → 10.58% → 8.48%),如需严格单调可考虑调整切点或合并分箱。IV=0.0405,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 3→4 箱有局部反弹:Bad Rate 由 4.68% 回升至 4.81%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 10.58%,可作为拒绝或重点风控策略的阈值参考

available_limit_amt
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 0.03499999921768904]1238532.52%10918146711.85%7.44
2(0.03499999921768904, 468.864990234375]452344.40%42472766.10%15.39
3(468.864990234375, 4307.300048828125]1199875.91%111488507.08%13.12
4(4307.300048828125, 27316.265625]725094.95%67884626.37%14.69
5(27316.265625, inf]1924100.00%1829954.94%19.25
合计380803493031508.27%11.09
2026-10-20T14:32:54.043797 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(11.85% → 11.85% → 4.94%),如需严格单调可考虑调整切点或合并分箱。IV=0.0357,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 2→3 箱有局部反弹:Bad Rate 由 6.10% 回升至 7.08%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.03499999921768904])为坏率最高区间:坏率高达 11.85%,可作为拒绝或重点风控策略的阈值参考

apprv_num_m3
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 0.5]2013952.89%18040209910.42%8.59
2(0.5, 1.5]663770.32%62224156.25%14.99
3(1.5, 2.5]356379.67%33532105.89%15.97
4(2.5, 4.5]361089.15%34311794.96%19.17
5(4.5, inf]4131100.00%38842475.98%15.72
合计380803493031508.27%11.09
2026-10-20T14:32:54.164709 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.42% → 10.42% → 5.98%),如需严格单调可考虑调整切点或合并分箱。IV=0.0302,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 4→5 箱有局部反弹:Bad Rate 由 4.96% 回升至 5.98%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 10.42%,可作为拒绝或重点风控策略的阈值参考

loan_os_prcp_credit_amount_m3
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, -4999.0]36779.66%329937810.28%8.73
2(-4999.0, 35.125]831531.51%79333824.59%20.77
3(35.125, 100.47500228881836]1911681.73%1761015067.88%11.69
4(100.47500228881836, 124.34499740600586]271788.87%241230511.23%7.91
5(124.34499740600586, inf]4235100.00%365757813.65%6.33
合计380603491131498.27%11.09
2026-10-20T14:32:54.281555 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(10.28% → 13.65% → 13.65%),如需严格单调可考虑调整切点或合并分箱。IV=0.0294,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 1→2 箱有局部反弹:Bad Rate 由 10.28% 回落至 4.59%,如需严格单调可考虑合并这两箱

第 5 箱((124.34499740600586, inf])为坏率最高区间:坏率高达 13.65%,可作为拒绝或重点风控策略的阈值参考

suc_apprv_num_m1
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 0.5]3016979.23%2728728829.55%9.47
2(0.5, 1.5]478791.80%45911964.09%23.42
3(1.5, inf]3124100.00%3052722.30%42.39
合计380803493031508.27%11.09
2026-10-20T14:32:54.452520 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性良好:随分栏增大,Bad Rate 单调下降(9.55% → 2.30%),WOE 单调上升(-0.0993 → 0.1164),符合风控分箱预期。IV=0.0288,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 2 箱 WOE<0(风险高于平均)

第 1 箱((-inf, 0.5])为坏率最高区间:坏率高达 9.55%,可作为拒绝或重点风控策略的阈值参考

cre_l60_used_limit_rate_min
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 0.019700000062584877]444111.67%43061353.04%31.90
2(0.019700000062584877, 0.09174999967217445]281319.06%26561575.58%16.92
3(0.09174999967217445, 0.2787500023841858]732338.30%68075167.05%13.19
4(0.2787500023841858, 0.9161500036716461]1889987.94%1715717429.22%9.85
5(0.9161500036716461, inf]4589100.00%398960013.07%6.65
合计380653491531508.28%11.08
2026-10-20T14:32:54.567575 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性良好:随分栏增大,Bad Rate 单调上升(3.04% → 13.07%),WOE 单调下降(0.1382 → -0.1170),符合风控分箱预期。IV=0.0264,该变量区分度偏弱但可用。

WOE 在第 3、4 箱之间穿越 0 线:前 3 箱 WOE>0(客户质量优于整体),后 2 箱 WOE<0(风险高于平均)

第 5 箱((0.9161500036716461, inf])为坏率最高区间:坏率高达 13.07%,可作为拒绝或重点风控策略的阈值参考

cre_now_l60_used_amt_m_min
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 1.7799999713897705]2820174.09%2545827439.73%9.28
2(1.7799999713897705, 869.5950012207031]247680.59%23681084.36%21.93
3(869.5950012207031, 1999.7100219726562]206086.00%2009512.48%39.39
4(1999.7100219726562, 6462.93505859375]312594.21%30091163.71%25.94
5(6462.93505859375, inf]2203100.00%20711325.99%15.69
合计380653491531508.28%11.08
2026-10-20T14:32:54.707431 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(9.73% → 9.73% → 5.99%),如需严格单调可考虑调整切点或合并分箱。IV=0.0256,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 4 箱 WOE<0(风险高于平均)

第 3→4 箱有局部反弹:Bad Rate 由 2.48% 回升至 3.71%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 1.7799999713897705])为坏率最高区间:坏率高达 9.73%,可作为拒绝或重点风控策略的阈值参考

apprv_amt_day
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 11.0]3034479.68%2745228929.53%9.49
2(11.0, 1000.5]250686.27%2421853.39%28.48
3(1000.5, 5995.0]330494.94%3220842.54%38.33
4(5995.0, inf]1926100.00%1837894.62%20.64
合计380803493031508.27%11.09
2026-10-20T14:32:54.832641 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(9.53% → 9.53% → 4.62%),如需严格单调可考虑调整切点或合并分箱。IV=0.0250,该变量区分度偏弱但可用。

WOE 在第 1、2 箱之间穿越 0 线:前 1 箱 WOE>0(客户质量优于整体),后 3 箱 WOE<0(风险高于平均)

第 3→4 箱有局部反弹:Bad Rate 由 2.54% 回升至 4.62%,如需严格单调可考虑合并这两箱

第 1 箱((-inf, 11.0])为坏率最高区间:坏率高达 9.53%,可作为拒绝或重点风控策略的阈值参考

loan_os_prcp_credit_amount_m6
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 4.129999876022339]19175.04%17931246.47%14.46
2(4.129999876022339, 33.795000076293945]621021.35%59412694.33%22.09
3(33.795000076293945, 48.94499969482422]443733.01%41412966.67%13.99
4(48.94499969482422, 107.59499740600586]1873582.24%1707416618.87%10.28
5(107.59499740600586, inf]6761100.00%596279911.82%7.46
合计380603491131498.27%11.09
2026-10-20T14:32:54.954635 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性欠佳:Bad Rate 随分栏存在波动(6.47% → 11.82% → 11.82%),如需严格单调可考虑调整切点或合并分箱。IV=0.0239,该变量区分度偏弱但可用。

WOE 在第 3、4 箱之间穿越 0 线:前 3 箱 WOE>0(客户质量优于整体),后 2 箱 WOE<0(风险高于平均)

第 1→2 箱有局部反弹:Bad Rate 由 6.47% 回落至 4.33%,如需严格单调可考虑合并这两箱

第 5 箱((107.59499740600586, inf])为坏率最高区间:坏率高达 11.82%,可作为拒绝或重点风控策略的阈值参考

cre_l90_used_limit_amt_min
组号ValueTot. Records累计占比#Goods#BadsBad RateG/B Odds
1(-inf, 21.640000343322754]561814.76%54082103.74%25.75
2(21.640000343322754, 748.7099914550781]807635.98%75265506.81%13.68
3(748.7099914550781, 8516.22998046875]2017288.97%1835418189.01%10.10
4(8516.22998046875, 14597.384765625]226794.92%199027712.22%7.18
5(14597.384765625, inf]1932100.00%163729515.27%5.55
合计380653491531508.28%11.08
2026-10-20T14:32:55.081239 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

关键结论

单调性良好:随分栏增大,Bad Rate 单调上升(3.74% → 15.27%),WOE 单调下降(0.1447 → -0.0821),符合风控分箱预期。IV=0.0232,该变量区分度偏弱但可用。

WOE 在第 2、3 箱之间穿越 0 线:前 2 箱 WOE>0(客户质量优于整体),后 3 箱 WOE<0(风险高于平均)

第 5 箱((14597.384765625, inf])为坏率最高区间:坏率高达 15.27%,可作为拒绝或重点风控策略的阈值参考

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
cre_l90_used_limit_amt_min896.0000
loan_os_prcp_credit_amount_m6867.0000
cre_l60_used_limit_rate_min865.0000
loan_os_prcp_credit_amount_m3708.0000
available_limit_amt595.0000
cre_now_l60_used_amt_m_min347.0000
t_ps_od_days_max333.0000
apprv_num_m3333.0000
s_ps_od_days_max284.0000
f_ps_od_days_max267.0000

区分度验证 — LightGBM @ 跨时间样本

KS = 0.2948,GINI = 0.3892

2026-10-20T14:32:55.215232 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:55.337776 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

测试情景2:跨时间样本剔除一半好样本

指标数值
样本量34730 → 18581(剔除好样本 16149)
KS0.2971
AUC0.6967
GINI0.3934
2026-10-20T14:32:55.461418 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/ 2026-10-20T14:32:55.581571 image/svg+xml Matplotlib v3.10.9, https://matplotlib.org/

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。