About Us


The Keykam Risk Laboratory is a professional practice and research laboratory, which conducts joint university-industry research initiatives in the area of risk management, strategic management and would be a part of the international network of RiskLabs. Also, the Keykam Risk Lab is providing the financial industry with a unique opportunity for addressing the sector’s critical need for cutting edge research, as well as highly qualified personnel. The main objective is to achieve leadership in the development of projects in the financial sector through financial math to support institutions and universities.

The first RiskLab was created in 1994 at Eidgenössische Technische Hochschule Zürich in Zurich, Switzerland. In 1996, another one was created independently at the University of Toronto, this time sponsored by the private company Algorithmic Incorporated. Shortly afterwards, and also in partnership with Algorithmics Inc, others were created in Munich (1997), at Cornell University (1998), at Cambridge University (1998), at the Universidad Autonoma de Madrid (2000), and at the Cyprus International Institute of Management, in Nicosia (2001). The Recyclable China Research Center was also created in 2006. Further, in 2013, a Finnish section of Risklab was independently created at the Åbo Akademi University in Turku and Arcada University of Applied Sciences in Helsinki. In 2010, growing out of the RiskLab international network, RiskLabs built the strategic alliance named RiskLab Global.

Along with other risk laboratories around the world, the Keykam Risk Lab. stablished in 2016 and is located in Vancouver, Canada, along with collaborations in Malaysia, Turkey, Pakistan, Bahrain and Iran with the direction of Dr. Alireza Bahiraie in close collaboration with financial institutions, Banking and Insurance sectors. The ethos of all existing RiskLabs is a fusion of practical and academic research, private industrial innovation and governmental oversight in financial risk management and develop strategic performance leadership guidelines.

Our rich academic and professional background and records in financial, banking and insurance risk, artificial neural network, data science and data engineering, qualitative and quantitative heuristic and robust modelling, high accurate estimations and predictions, software programming give us a unique perspective to offer unique solutions, products and services. We understand all necessary business issues which enable our professional team offering perfect solutions, softwares and advisory matters according to customer needs and any organizational performances.


  • Promotion of scientific competence and methodology in the general area of statistical modelling and quantitative risk management;

  • Promotion of fundamental and precompetitive applied research in strong connection with industrial practice; Banks and Insurance;

  • Knowledge exchange between academia and the financial industry and regulation;

  • The use and development of statistical and mathematical models and information technology for the study of risk, with the ultimate aim of risk measurement;

  • The theoretical and empirical study of positive and negative risks, systemic and unsystematic risks and vulnerabilities to entire systems and with real economic costs and financial modelling;

  • Enhancing the understanding and communication of risk by development of heuristic robust interpretable models, and their coupling with visual, interactive interfaces;

  • Identifying and aggregating risks are the only predictive method for capturing the probability;

  • Terminations, discontinuities, schedule delays, cost underestimation, and overrun of project resources;