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Testing Stochastic lnterest Rate Generators for lnsurer Risk and Capital Models

The Valuation of Stochastic Cash Flows

Martian Chronicles: Is MARS Better than Neural Networks?

Stochastic Models with Memory for Seismic Risk Evaluation

Practical Loss Reserving Method with Stochastic Development Factors

Which Stochastic Model is Underlying the Chain Ladder Method?

Examining Changes in Reserves Using Stochastic Interest Models

A Stochastic Method for Claims Reserving in General Insurance

An Introduction to Stochastic Simulation

Finite Markov Chains

A Stochastic Approach to Automobile Compensation

Minimum Bias With Generalized Linear Models

Minimum Bias with Generalized Linear Models [Discussion]

A Stochastic Approach to Trend and Credibility

Ratemaking: From Bailey and Simon (1960) to Generalized Linear Regression Models

Hospital Self-Insurance Funding: A Monte Carlo Approach

A Stochastic Model for the Analysis and Evaluation of the Claim Reserve

A Multiplicative Model of Loss Reserves: A Stochastic Approach

Stochastic Claims Reserving When Past Claim Numbers Are Known

Forecasting the Future - Stochastic Simulation and Scenario Testing

A Generalized Framework for the Stochastic Loss Reserving

The Application of Cumulative Distribution Functions in the Stochastic Chain Ladder Model

Something Old, Something New in Classification Ratemaking With a Novel Use of GLMs for Credit Insurance

Using Neural Networks to Predict Claim Duration in the Presence of Right Censoring and Covariates

Individual Claims Forecasting with Bayesian Mixture Density Networks

This paper introduces an individual claims forecasting framework utilizing Bayesian mixture density networks that can be used for claims analytics tasks such as case reserving and claims triaging. This approach produces multi-period, cash-flow forecasts. The modeling framework uses a publicly available data simulation tool.