Stress testing is becoming increasingly important for insurers due to rising regulatory requirements, climate risk, economic volatility and digital threats.
Moody's recognises this risk landscape and wins this award for the comprehensive way it works with many insurers to support their stress testing requirements, such as for Solvency II, climate change scenarios or IFRS 17.
To achieve the best stress testing results for its clients, Moody's combines its economics team's insights with stochastic market-consistent, real-world and climate pathway scenario generation capabilities.
It then provides this in a robust, easy-to-use automation framework to support the production of stress and sensitivity calibrations.
The judging panel liked that Moody's scenario generation automation capability allows insurers to implement transparent, repeatable and auditable stress testing processes. This capability enables fast production timescales for risk-neutral stochastic scenarios with the validation reports required to support regulatory submissions.
In addition, users of a real-world stochastic scenarios can use Moody's flexible calibration tools to customise the model to replicate different stressed paths for the expected behaviour of key economic risk factors.
The fact that Moody's offers a range of climate pathway calibration services and a stress testing framework to support the use of climate change scenarios and related assumptions in real-world projections also earned praise from the judges.
Finally, in an increasingly fractious and uncertain world, the judges welcomed that Moody's real-world calibration tools allow clients to customise the path of market-risk variables to replicate desired stress levels.
The flexibility and ease of use of these tools is a key feature that enables various stressed paths to be incorporated into the real-world stochastic projections over short-, medium- and long-term horizons.
Moody's solution also supports a macroeconomic variable modelling framework to project variables such as GDP, unemployment, house price inflation and population changes at a regional or metropolitan area level.
