Lack of sufficient knowledge of the project environment can increase investment risks. Accordingly, the identification, grading, and management of risks are essential to project success. Risk identification is an accurate, detailed, and probing process that identifies risks during project life cycle by interacting with individuals and experts. Because risks constantly recur and change during project life cycle, risk identification is an essential and iterative process in all project phases. So, this study aims to identify and prioritise construction projects risks using a hybrid quantitative approach, namely, Fuzzy Decision Making and Trial Evaluation Laboratory (FDEMATEL) and Fuzzy Analytic Network Process (FANP) techniques. After review of the relevant literature and classification of the identified investment risks into three main risks, the above‐mentioned techniques were applied. Results revealed that systemic risk is the most influential factor whereas environmental risk is the most permeable factor among the main criteria. The highest weight belongs to the business risk factor whereas the lowest weight belongs to systemic risk. These were the most and least important factors of the risks involved in construction projects from the perspective of the experts.