Menu
Home
People
Places
Arts
History
Plants & Animals
Science
Life & Culture
Technology
Reference.org
Stochastic modelling (insurance)
open-in-new
<i>This page is concerned with the stochastic modelling as applied to the insurance industry. For other stochastic modelling applications, please see <a href="/facts/Monte_Carlo_method/AkHjY7jc">Monte Carlo method</a> and <a href="/facts/Stochastic_asset_model/yEsjknjT">Stochastic asset models</a>. For mathematical definition, please see <a href="/facts/Stochastic_process/Ng1n1dnB">Stochastic process</a>.</i> <p>"<a href="/facts/Stochastic/uMbgL94r">Stochastic</a>" means being or having a <a href="/facts/Random_variable/TwTBXnLT">random variable</a>. A stochastic model is a tool for estimating <a href="/facts/Probability_distribution/EpsKKVRu">probability distributions</a> of potential outcomes by allowing for random variation in one or more inputs over time. The random variation is usually based on fluctuations observed in historical data for a selected period using standard <a href="/facts/Time-series/fSXPR817">time-series</a> techniques. Distributions of potential outcomes are derived from a large number of <a href="/facts/Simulation/Q4QJV1oI">simulations</a> (stochastic projections) which reflect the random variation in the input(s). </p><p>Its application initially started in <a href="/facts/Physics/a7aH2y08">physics</a>. It is now being applied in <a href="/facts/Engineering/RFVg8H3I">engineering</a>, <a href="/facts/Life_sciences/9HYkCgqe">life sciences</a>, <a href="/facts/Social_science/hAbm1xtD">social sciences</a>, and <a href="/facts/Finance/fLh1GgN8">finance</a>. See also <a href="/facts/Economic_capital/25nGBnlE">Economic capital</a>. </p>