  We present a new approximation to the normal distribution quantile function.
It has a similar form to the approximation of Beasley and Springer [3],
providing a maximum absolute error of less than $2.5 \cdot 10^{-5}$. This is
less accurate than [3], but still sufficient for many applications. However it
is faster than [3]. This is its primary benefit, which can be crucial to many
applications, including in financial markets.
