The authors introduce a novel generic methodology to solve continuous finite-horizon stochastic optimal control problems (SOCPs). The authors treat controlled stochastic differential equations (SDEs) within the Wiener chaos framework by utilizing Malliavin calculus and developing innovative ideas to preserve the feedback character of optimal Markov decision rules. This allows a direct reformulation of sacps into deterministic ones. Hence, it facilitates using Bock's direct multiple shooting method for solving sacps and pioneers the extension of sophisticated methods for deterministic control to the broad context of SDEs. Numerical examples validate this new framework with huge computational advantages compared to standard ideas in SOC.