Research Article
Improved ML-Based Technique for Credit Card Scoring in Internet Financial Risk Control
Table 6
Variables selected into the model.
| Bank of deposit | 0.053 |
| Number of credit cards | 0.052 | Maximum credit card limit in recent 1 month | 0.084 | Maximum overdue days of short-term loans | 0.286 | The salary per month | 0.249 | The standard deviation of the number of SMS messages sent at night in the last three months | 0.072 | The standard deviation of the frequency of answering unlabeled numbers at night in recent two months | 0.075 | Debit card ratio | 0.073 | Bill number | 0.069 | Amount to be paid under credit products | 0.065 | Average consumption in recent 30 days | 0.063 | Total data months | 0.068 | The proportion of credit cards with bills in the last 60 days | 0.066 | Balance of credit products | 0.062 | Percentage standard deviation of dialing all numbers at night in recent 60 days | 0.060 | Bank of deposit | 0.061 |
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