Software effort estimation and risk management, both are vital for a successful software project delivery. Much research has been done for improving the effort estimation accuracy and minimizing the cost of risk exposure of a project. This research proposes to integrate cost of risk exposure into effort estimate of a project for improving the software effort estimation accuracy. This integrated effort estimate has been optimized using three different mutation strategies of differential evolution. Proposed approach was tested on two industry datasets: waterfall model and agile model datasets. For both the datasets, MMRE of the proposed integrated effort estimate was lower than the effort estimated without including the cost of risk exposure. Application of differential evolution approach to the effort estimation techniques: CoCoMo, CoCoMo II, Ziauddin and the proposed integrated effort estimate improved the accuracy of all of them.