Stimulation

Simulation is a technique that uses mathematical models to imitate the operation of a real-world process or system over time, allowing banks to analyse risk and decision outcomes without real-world experimentation.

To model complex systems and estimate outcomes under uncertainty.

Monte Carlo simulation is a computational technique that uses random sampling and statistical modelling to estimate the probability of different outcomes, widely used in banks for risk assessment, portfolio valuation, and stress testing.

A single complete execution of the simulation model from start to finish.

A stochastic process is one that involves randomness or probability, where the outcome is not determined solely by initial conditions; it is fundamental to building realistic simulation models in banking.

Repeating a simulation multiple times with different random seeds.

Deterministic models produce the same output for a given input every time, while stochastic models incorporate randomness and produce a distribution of possible outcomes, making stochastic models more suited to real banking environments.

A simulation where system state changes only at specific event points in time.