Banks increasingly rely on complex AI models, but explainability has limits. This analysis examines model risk, regulatory ...

Risk models at Credit Suisse had flagged the dangers before their $5.5 billion Archegos loss. Silicon Valley Bank's risk metrics showed clear warnings before their collapse. In both cases, ...

Risk engineering applies quantitative and qualitative methods to identify, analyse and mitigate hazards across technical and socio-technical systems. Core approaches include probabilistic risk ...

Model-based systems engineering is quietly, but consistently, becoming an important part of the design, maintenance, and cybersecurity of the federal government’s most complex IT platforms. MBSE ...

Traditional cybersecurity measures are increasingly inadequate against sophisticated threats in the rapidly evolving digital security landscape. Artificial intelligence (AI) has emerged as a ...

Data analysis is enabling teams to make better decisions, and systems engineering is no different. Digital solutions have emerged to help engineers gather and analyze data from modeling, simulation, ...

Why engineers are turning to system-level models. How high-fidelity digital twins help expose system-level issues. Where MBSE is experiencing the fastest adoption. The roles of AI and data science in ...

Today’s electronic systems are an increasingly complex combination of hardware and software components. They contain an ever-expanding range of functions, require more computing power, have to operate ...