How to deal with potential data falsification?
In science, a lack of reproducibility leaves you all on the hook. But, I would probably recommend getting a third expert in Monte Carlo to review the code. I'll assume this is you.
First, it can be the case that a small change in code makes big differences, permutation testing for instance can do this. But, you can run the simulation lots of times, look at the results, and find what quintile the original results are in. This corresponds to a p value for falsification, or as I will call it: a possible mistake.
Nonetheless, Monte Carlo is not very complicated, and in the paper regardless you will have to explain how the answers were obtained. If you cannot do this, you cannot push paper into community. So, inspect, conclude, rework. 
For their sake, I hope falsification is not the case. That's a very very ugly way to go about research, and it will crop up.