### Most Important Contributing Factors

This is a list of factors that contribute most heavily to the final prediction in our model.

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Intervals | Points |
---|---|

0-63 | +1.799 |

64-70 | +1.017 |

71-75 | +0.269 |

76-80 | -0.326 |

81-Inf | -1.094 |

-7 | 0 |

-8 | 0 |

-9 | +1.094 |

Intervals | Points |
---|---|

0-91 | +0.549 |

92-134 | +0.292 |

135-263 | +0.086 |

264-Inf | -0.148 |

-7 | 0 |

-8 | +0.148 |

-9 | 0 |

Intervals | Points |
---|---|

0-8 | +0.083 |

9-19 | +0.083 |

20-74 | 0 |

75-81 | 0 |

82-Inf | 0 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-48 | +1.238 |

49-69 | +0.669 |

70-96 | +0.269 |

97-Inf | 0 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-2 | +1.999 |

3-5 | +1.152 |

6-12 | +0.539 |

13-21 | +0.166 |

22-Inf | -0.086 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-1 | -0.021 |

2 | +0.931 |

3-11 | +0.952 |

12 | +1.814 |

13-Inf | +2.330 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-1 | -0.021 |

2 | -0.053 |

3-7 | -0.053 |

8-9 | +0.087 |

10-Inf | +0.329 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0 | -0.198 |

1-9 | +0.535 |

10-16 | +0.116 |

17-27 | -0.097 |

28-Inf | -0.377 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-2 | -0.021 |

3 | +0.287 |

4-6 | +0.428 |

7-11 | +0.896 |

12-Inf | +2.294 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-59 | +1.567 |

59-84 | +1.012 |

84-89 | +0.601 |

89-96 | +0.366 |

96-Inf | -0.147 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-8 | -0.058 |

9-17 | -0.058 |

18-32 | -0.22 |

33-47 | -0.392 |

48-Inf | -0.482 |

-7 | +0.198 |

-8 | +0.137 |

-9 | 0 |

Intervals | Points |
---|---|

0-3 | +0.806 |

4-5 | +0.806 |

6 | +0.408 |

7-8 | -0.147 |

9-Inf | -0.147 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-2 | -0.017 |

3 | -0.147 |

4-5 | -0.147 |

6 | -0.147 |

7-Inf | -0.147 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-35 | -0.620 |

36-46 | -0.503 |

47-57 | -0.145 |

58-84 | +0.161 |

85-Inf | +1.156 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-9 | +0.001 |

10 | +0.001 |

11-35 | +0.001 |

36-70 | +0.147 |

71-Inf | +0.363 |

-7 | 0 |

-8 | +0.047 |

-9 | 0 |

Intervals | Points |
---|---|

0-2 | +0.242 |

3 | +0.229 |

4-11 | +0.313 |

12-13 | -0.830 |

14-Inf | -0.161 |

-7 | 0 |

-8 | +0.256 |

-9 | 0 |

Intervals | Points |
---|---|

0 | +1.223 |

1-2 | +0.553 |

2-8 | +0.305 |

9-22 | +0.131 |

23-Inf | -0.633 |

-7 | +1.258 |

-8 | -0.672 |

-9 | 0 |

Intervals | Points |
---|---|

0-1 | -0.047 |

2 | +0.170 |

3-4 | +0.170 |

5-8 | +0.471 |

9-Inf | +1.222 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-1 | -0.051 |

2 | -0.051 |

3-4 | +0.021 |

5-8 | +0.021 |

9-Inf | +0.021 |

-7 | 0 |

-8 | 0 |

-9 | 0 |

Intervals | Points |
---|---|

0-1 | -0.739 |

2-14 | -0.739 |

15-37 | -0.088 |

38-72 | +0.633 |

73-Inf | +1.457 |

-7 | 0 |

-8 | +0.851 |

-9 | 0 |

Intervals | Points |
---|---|

0-3 | -0.188 |

4 | -0.263 |

5-7 | -0.150 |

8-11 | +0.034 |

12-Inf | +0.165 |

-7 | 0 |

-8 | +0.512 |

-9 | 0 |

Intervals | Points |
---|---|

0-1 | -0.601 |

2 | +0.238 |

3 | +0.541 |

4-5 | +0.611 |

6-Inf | +1.039 |

-7 | 0 |

-8 | 0.601 |

-9 | 0 |

Intervals | Points |
---|---|

0-47 | -0.982 |

48-66 | -0.454 |

67-73 | -0.130 |

74-86 | +0.203 |

87-Inf | +0.772 |

-7 | 0 |

-8 | +0.794 |

-9 | 0 |

Subscales | Risk Score | Weights | Points |
---|---|---|---|

ExternalRiskEstimate | 1.593 | ||

TradeOpenTime | 2.468 | ||

NumSatisfactoryTrades | 2.273 | ||

TradeFrequency | 0.358 | ||

Delinquency | 2.470 | ||

Installment | 1.175 | ||

Inquiry | 2.994 | ||

RevolvingBalance | 1.877 | ||

Utilization | 1.119 | ||

TradeWBalance | 0.214 |

This is a list of factors that contribute most heavily to the final prediction in our model.

The system solves an optimization problem (using Gurobi(c)) to compute the smallest set of rules that guarantees identical prediction by our global model.

The table below compares the examined case with cases that share the same prediction outcome.

See documentation for more description of the global model and its local models (link is at the top of the page).