# Does High Information Value (IV) for a variable implies high coefficient in logistic regression?

I'm performing a Logistic regression for a binary classification task.

As a preprocessing technique I use a transformation with WOE and Information value(IV), but I found something counterintuitive since when I check the regression's coefficients there are some that have the value of zero though those variables have a "high" IV

From the table below I see that for variable CANT_ACT_ECONOMICAS has a coefficient of 0 but is has the highest IV

Model coefficients:
***** Fature Impportance *****
importance
COMPANY_DOMAIN_CLASS      0.027879
GENDER                    0.000000
CANT_ACT_ECONOMICAS       0.000000
ACT_ECONOMIC_GROUP       -0.065918
PRODUCTIVE_ZONE          -0.108427
DOMAIN                   -0.284159
COMPANY_AGE              -0.321768
WEEKDAY                  -0.474630
ACT_ECONOMIC_RISK        -0.595959
USE_OF_PROCEEDS_INTENT   -0.805546
AGE                      -0.895112
USE_OF_PROCEEDS_RISK     -0.898074
START_HOUR               -1.030490

Information Value:

AVG_IV
CANT_ACT_ECONOMICAS 0.058573
COMPANY_AGE 0.034645
PRODUCTIVE_ZONE 0.032958
ACT_ECONOMIC_RISK   0.030869
COMPANY_DOMAIN_CLASS    0.019605
AGE 0.004793
USE_OF_PROCEEDS_RISK    0.004689
USE_OF_PROCEEDS_INTENT  0.003318
START_HOUR  0.001870
WEEKDAY 0.001217
DOMAIN  0.001032
GENDER  0.000568
ACT_ECONOMIC_GROUP  NaN


My question is:

If a variable have a high information value, does it necessarily have to have high importance on logistic regression model (high coefficient)?