I'm trying to extend the birthday problem to detect collision probability in a hashing scheme. Here is my problem. I use the letters and numbers [A-Z][a-z][0-9] to make a set of keys by randomly choosing from that set 10 times and concatenating them all together. So A24cv30kf2 could be one key for example. This implies that the base set has $62^{10}$ possible keys. Next, I want to compute the probability that I would see a collision if I picked a key from that set and issued it to $n$ users. If $M$ represents the size of the set (= $62^{10}$) and $P(M,n)$ the probability then
$$P(M,n) = \frac{M!}{M^{n}(M-n)!}$$
This follows by replacing 365 in the well known birthday problem shown here
What I want to understand is the following: I want to check and see if my choice of concatenating 10 is right, when I know that my $n$ is of the order of a few millions and my $1 - P(M,n)$ needs to be less than 0.0001 or some small number. The large values of M & n make the above intractable to compute. Is there an easier way to compute this?