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Stress Testing is a well established risk management tool used by financial institutions. Stress Testing is highly prioritized with respect to banks' capital due to the regulatory requirements that banks have to comply with. 

Stress Testing has applications across different asset classes and business objectives. Macro Stress testing for instance aids in exploring how past and hypothetical future shocks transmit to loss and the income conditions for portfolios. A major objective in this regards is to examine solvency and profitability in the advent of crisis. The following article provides a brief outline of historic crash events affecting Financial Markets pre 2008.

System Dynamics was developed as a method for analyzing complex dynamical systems in the context of economy and social sciences with the aim to understand how and when systems and policies produce an unexpected outcome. The approach is focusing on certain aspects of reality by identifying constraints on any targeted outcome, time and reliability. The System Dynamics method zooms into relevant aspects of systems' behaviour and is thereby providing a useful method to support decision making processes. Applications of System Dynamics exist in multiple fields, namely project, risk and policy management as well as product development. 

Enabled through advances in Information Technology (IT), Artifical Intelligence (AI) and Machine Learning (ML) finds applications across mulltiple areas of Finance. Today, the availability of machines and algorithms specialised in learning and decision making from data make applications possible that draw insight from complex and high dimensional data. The calibration of these algorithms typically takes large number of parameter and model configurations into account. This leads to the unique machine learning approach to calibrations enabling to build robust models with adaption to the most recent information and data.