ZIP Model returns "non-finite value supplied by optim"

Question

I'm trying to fit a ZIP (Zero inflated Regression Model) to my dataset which contains 4 predictors. The dependent variable is 60% full of zeros which fits the model assumption. 2 of my 4 predictors might be correlated (fluctuating between 0.5-0.8). I however really need to predict based on ALL 4 predictors, is there a way around this? Or might this error "non-finite value supplied by optim" not be related to the correlation? If I drop a variable, the model is running which leads me to believe it is due to correlation.

This is how my data is looking like:

head(data_new)

# A tibble: 6 × 6
         rownum          A      B       C      D      E
      <int>             <int>   <dbl>    <dbl>  <dbl>  <dbl>
1         1               266   0.766   0.0519 0.0260 0.156 
2         2                97   1       0      0      0     
3         3               508   0.675   0.214  0.0256 0.0855
4         4                 4   0.762   0.167  0      0.0714
5         5                70   0.796   0.122  0      0.0816
6         6                51   0.757   0.203  0      0.0405

I want to fit a regression based on "A", however B and C are the ones that might have correlation.

Running

zip_model <- zeroinfl(A ~ B + C + D + E, data = data_new, dist = "poisson")

returns Error in optim(fn = loglikfun, gr = gradfun, par = c(start$count, start$zero, : non-finite value supplied by optim