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Table 17 Summary statistics of LD in different networks on NEEQ SMEs dataset

From: Clues from networks: quantifying relational risk for credit risk evaluation of SMEs

Risk event

MN

DN

SN

CN

LD_M3

635 (0.500%)

453 (5.905%)

247 (4.150%)

55 (1.472%)

LD_M6

1271 (1.000%)

816 (10.637%)

555 (9.325%)

137 (3.666%)

LD_M9

1779 (1.400%)

1178 (15.357%)

802 (13.474%)

164 (4.389%)

LD_M12

2287 (1.800%)

1450 (18.902%)

987 (16.583%)

192 (5.138%)

LD_M15

2669 (2.100%)

1813 (23.634%)

1172 (19.691%)

219 (5.860%)

LD_M18

3304 (2.600%)

2175 (28.354%)

1419 (23.841%)

274 (7.332%)

LD_M21

3812 (3.000%)

2447 (31.899%)

1666 (27.991%)

301 (8.055%)

LD_M24

4193 (3.300%)

2810 (36.631%)

1913 (32.140%)

329 (8.804%)

LD_M27

4702 (3.700%)

3082 (40.177%)

2098 (35.249%)

356 (9.526%)

LD_M30

5210 (4.100%)

3444 (44.896%)

2345 (39.399%)

384 (10.276%)

LD_M33

5718 (4.500%)

3807 (49.628%)

2592 (43.548%)

411 (10.998%)

LD_M36

6227 (4.900%)

4079 (53.174%)

2715 (45.615%)

439 (11.747%)

LD_M39

6608 (5.200%)

4351 (56.720%)

2900 (48.723%)

466 (12.470%)

LD_M42

6989 (5.500%)

4623 (60.266%)

3085 (51.831%)

466 (12.470%)

LD_M45

7370 (5.800%)

4895 (63.812%)

3270 (54.940%)

493 (13.192%)

LD_M48

7752 (6.100%)

5076 (66.171%)

3394 (57.023%)

521 (13.942%)

LD_M49

9912 (7.800%)

6617 (86.260%)

4196 (70.497%)

658 (17.608%)