Best optimization method for minimizing error of estimated default probability

Question

The credit risk modelling problem can be stated as: $$ \min_{a \in \mathbb{R}^{1 \times n}} \sum_i \Big( d_i -\frac{\exp(a x_i) }{1+\exp(a x_i)}\Big)^2 $$ Where $ d_i \in \mathbb{N} \in [0,1] $ is the default indicator for customer $ i $ and $ x_i \in \mathbb{R}^{n \times 1} $ is the value of all the $ n $ information variables available for customer $ i $. Any alternatives to logistic regression?