Quantitative finance infrastructure is entering a new era as transparent algorithms, cloud-native delivery, and AI-powered interfaces converge. This paper explores how open-source risk analytics can help financial institutions build more auditable, scalable, and accessible infrastructure, while preparing for evolving regulatory and business requirements.
Readers will gain insights into:
- Why the proprietary “black box” model is losing ground, as regulatory requirements increase the need for transparent and explainable calculations.
- How the Open-Source Risk Engine, ORE, builds on QuantLib to support exposure simulation, XVA, sensitivity analysis, historical simulation VaR, stress testing, FRTB, and SA-CCR calculations.
- How Open Risk Analytics, ORA, combines open-source calculations with managed, cloud-based delivery, helping teams reduce the burden of maintaining bespoke infrastructure.
- How AI-powered conversational interfaces could make complex risk analytics more accessible, allowing users to interrogate calculations and understand results in plain language.
- Practical steps institutions can take today, including starting with focused use cases such as intraday CVA monitoring, SA-CCR capital optimisation, or FRTB sensitivity generation.
Complete the form now and access the report
Access the report
Thank you for submitting your details.