Confusion on result of K-Fold Cross Validation and Independent Test set
Absolutely, I've had this happen to me. As Ben Reiniger pointed out in the comment, check your individual scores of the folds. I'd expect you to have some folds that score worse than your reported k-fold score and some that score better, maybe even better than the independent test set.

Some things I consider when this happens:


When you test on the independent test set, have you trained on the full training set? 
What accuracy do you get if you predict on the training set after using it for training? Better or worse than the accuracy you got on the independent test set?


Lastly, consider the balance of classes in your training set, training folds, and your independent test set. Accuracy scores are sensitive to class imbalance, and may cause such a discrepancy in scores between sets if the balance shifts. If you suspect class imbalance is an issue, you could either balance it (e.g. undersample the test set) or use a different metric.