PhD, ETH Zürich · Financial Risk Manager · IMD Future Leaders
If it can't be reproduced, it can't be defended.
We develop and modernise risk and capital models and operational calculations for banks and insurers. In doing so, we connect regulatory methodology, quantitative modelling and numerical implementation with the required data, testing, documentation and risk reporting.
Risk and capital models turn regulatory and quantitative methods into operational calculations. In banks and insurers, methodology, data, software and documentation must therefore express the same logic. Only then can a result be reproduced, explained and traced through its calculation path.
Nuitio can develop new risk and capital models and modernise existing models or calculation environments. We turn the methodology into tested calculations, connect the required data, and check logic, convergence and edge cases. Where runtime becomes a constraint, we optimise simulations and other numerical methods. Code, tests and documentation describe the same model.
Nuitio can advance risk and capital models from different starting points: a new regulatory requirement, a method that has not yet been implemented, a calculation that is too slow, or a validation finding. Depending on the need, we develop an individual model component, modernise the existing calculation environment, or bring a complete model into operational use. Nuitio can take on part of the implementation or develop an existing solution jointly with the client team.
METHODOLOGY, SOFTWARE AND DOCUMENTATION MUST AGREE
Selected projects
Current Nuitio systems and work drawn from over a decade of our founders’ experience – built, adopted, approved or in production.
A solvency model for intragroup contagion effects
For every balance-sheet scenario produced by the group risk model, the contagion model calculates how defaults and rating migrations affect other legal entities through ownership, internal reinsurance and guarantees.
One bank-wide calculation for all three components of the standardised approach for market risk
All relevant sensitivities and position data were consolidated across the bank, assigned to the prescribed risk factors, risk classes and buckets, and calculated using the regulatory parameters.
Talk to Tobias
Send Tobias a short note about what you have in mind. In an initial conversation, we discuss the project and possible next steps.