What is the most likely reason that the model fails to converge?

An analyst fits a logistic regression model to predict whether or not a client will default on a loan. One of the predictors in the model is agent, and each agent serves 15-20 clients each. The model fails to converge. The analyst prints the summarized data, showing the number of defaulted loans per agent.

See the partial output below:

What is the most likely reason that the model fails to converge?
A . There is quasi-complete separation in the data.
B . There is collinearity among the predictors.
C . There are missing values in the data.
D . There are too many observations in the data.

Answer: A