Table 15 Descriptive statistics of LD + AP 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 |
|---|---|---|---|---|
MRE_M3 | 1017 (0.800%) | 635 (8.278%) | 432 (7.258%) | 110 (2.944%) |
MRE_M6 | 2033 (1.600%) | 1360 (17.729%) | 864 (14.516%) | 192 (5.138%) |
MRE_M9 | 3050 (2.400%) | 1994 (25.994%) | 1358 (22.816%) | 274 (7.332%) |
MRE_M12 | 3939 (3.100%) | 2538 (33.086%) | 1666 (27.991%) | 329 (8.804%) |
MRE_M15 | 4829 (3.800%) | 3173 (41.364%) | 2036 (34.207%) | 411 (10.998%) |
MRE_M18 | 5718 (4.500%) | 3807 (49.628%) | 2468 (41.465%) | 466 (12.470%) |
MRE_M21 | 6608 (5.200%) | 4442 (57.906%) | 2839 (47.698%) | 548 (14.664%) |
MRE_M24 | 7370 (5.800%) | 4895 (63.812%) | 3147 (52.873%) | 603 (16.136%) |
MRE_M27 | 8133 (6.400%) | 5348 (69.717%) | 3517 (59.089%) | 658 (17.608%) |
MRE_M30 | 8895 (7.000%) | 5892 (76.809%) | 3826 (64.281%) | 713 (19.079%) |
MRE_M33 | 9658 (7.600%) | 6436 (83.900%) | 4134 (69.456%) | 767 (20.524%) |
MRE_M36 | 10,293 (8.100%) | 6798 (88.619%) | 4381 (73.606%) | 795 (21.274%) |
MRE_M39 | 10,801 (8.500%) | 7161 (93.352%) | 4628 (77.755%) | 850 (22.746%) |
MRE_M42 | 11,183 (8.800%) | 7433 (96.897%) | 4813 (80.864%) | 850 (22.746%) |
MRE_M45 | 11,437 (9.000%) | 7614 (99.257%) | 4937 (82.947%) | 877 (23.468%) |
MRE_M48 | 11,818 (9.300%) | 7886 (102.803%) | 5060 (85.013%) | 904 (24.191%) |
MRE_M49 | 13,597 (10.700%) | 9155 (119.346%) | 5739 (96.421%) | 1014 (27.134%) |