Smart collaborations among the smart grid, electric vehicles, and aggregators will provide range of benefits to stakeholders involved in an intelligent transportation system (ITS). The EVs, nowadays, are becoming the epicenter of smart power system research towards the electrification of transport. However, massive penetration of EVs will pose management threats to the supporting smart grid in the foreseeable future. This work proposes a risk averse optimization framework for smart charging management of electric vehicles. Adopting conditional value at risk (CVaR) for estimating the risks, the work attempts to propose an optimized bidding strategy for the smart charging stations (SCS) that act on behalf of aggregators for managing the financial risk caused by the uncertainties. Finally, a fuzzified translation model is discussed along with notable methodologies as a solution strategy to the risk averse cost optimization problem.