CT RISK endeavours to build financial risk models that are intended to help their users oversee the disposition of at-risk capital in the real world. For this purpose, the underlying modelling philosophy of CT RISK is empirically defined. Model quality can be measured in many ways: precision, accuracy, discriminatory power, robustness, stability and reliability. Indeed models are never perfect, and the appropriate metrics of quality and the efforts that should be put into improving quality, depend on the situation. The measuring stick of the model's success is whether it results in judicious decision making, not whether it is elegant, easy to compute or popular. There is typical financial reality to be considered:

• The normal distribution describes financial returns rather poorly and can cause severe underestimation of risk;
• A fixed co-movement structure between assets does not only pose risk in practice, but also render redundancy given the limited capacity; and
• Erratic, conflicting and unexpected events will continue to happen.

CT RISK’s approach to the application of multiple simulation-based analytics is directed to better equip the practitioner to deal with this reality.