Table 10 Descriptive statistics of binary features
From: A framework to improve churn prediction performance in retail banking
Feature | Average | 0 (FALSE) | 1 (TRUE) |
|---|---|---|---|
30. Whether the customer has received a salary with the bank | 0.42 | 1,892,600 | 1,390,732 |
31. Whether the customer is a civil servant | 0.16 | 2,748,934 | 534,398 |
32. Whether the customer has a dedicated account manager | 0.15 | 2,790,652 | 492,680 |
44. Credit purchase incidence | 0.83 | 570,809 | 2,712,523 |
45. Investment purchase incidence | 0.37 | 2,080,999 | 1,202,333 |
36. Purchase incidence | 0.98 | 58,702 | 3,224,630 |
46. Use of mobile channels incidence | 0.61 | 1,290,043 | 1,993,289 |
55. Whether the customer has a credit card | 0.20 | 2,635,776 | 647,556 |
53. Whether the customer has any credit taken | 0.41 | 1,922,302 | 1,361,030 |
54. Whether the customer has any overdue credit | 0.08 | 3,012,753 | 270,579 |
52. Whether the customer has done any debt renegotiation | 0.01 | 3,252,890 | 30,442 |
51. Whether the customer has used a credit card | 0.14 | 2,816,557 | 466,775 |