scholarly journals A Simulation Procedure for Comparing Different Claims Reserving Methods

1992 ◽  
Vol 22 (2) ◽  
pp. 191-216 ◽  
Author(s):  
Teivo Pentikäinen ◽  
Jukka Rantala
Keyword(s):  
Monte Carlo ◽  
Claims Data ◽  
Theoretical Models ◽  
Risk Theory ◽  
Simulation Procedure ◽  
Financial Position ◽  
Run Off ◽  
Simulated Case ◽  
Insurance Business ◽  
The Difference

AbstractThe estimation of outstanding claims is one of the important aspects in the management of the insurance business. Various methods have been widely dealt with in the actuarial literature. Exploration of the inaccuracies involved is traditionally based on a post-facto comparison of the estimates against the actual outcomes of the settled claims. However, until recent years it has not been usual to consider the inaccuracies inherent in claims reserving in the context of more comprehensive (risk theoretical) models, the purpose of which is to analyse the insurer as a whole. Important parts of the technique which will be outlined in this paper can be incorporated into over-all risk theory models to introduce the uncertainty involved with technical reserves as one of the components in solvency and other analyses (Pentikäinen et al. (1989)).The idea in this paper is to describe a procedure by which one can explore how various reserving methods react to fictitious variations, fluctuations, trends, etc. which might influence the claims process, and, what is most important, how they reflect on the variables indicating the financial position of the insurer. For this purpose, a claims process is first postulated and claims are simulated and ordered to correspond to an actual handling of the observed claims of a fictitious insurer. Next, the simulation program will ‘mime’ an actuary who is calculating the claims reserve on the basis of these ‘observed’ claims data. Finally, the simulation is further continued thus generating the settlement of the reserved claims. The difference between reserved amounts and settled amounts gives the reserving (run-off) error in this particular simulated case. By repeating the simulation numerous times (Monte Carlo method) the distribution of the error can be estimated as well as its effect on the total outcome of the insurer.

A stochastic method for claims reserving in general insurance

1990 ◽  
Vol 117 (3) ◽  
pp. 677-731 ◽  
Author(s):  
T. S. Wright
Keyword(s):  
Claims Data ◽  
Risk Theory ◽  
Stochastic Method ◽  
Error Structure ◽  
Numerical Example ◽  
General Insurance ◽  
Development Period ◽  
Run Off ◽  
Fitting Method ◽  
Paid Claims

AbstractThe paper addresses the problem of estimating future claim payments from the ‘run-off’ of past claim payments. A model of the claim payment process is postulated. Results from risk theory are applied to give a model for the incremental paid claims data by development period. A fitting method is developed which takes account of the error structure of the data implied by the underlying model of the claim payment process. The application of a similar method to incremental incurred data is considered. A numerical example is given.

scholarly journals Evaluation of the Vertical Producing Degree of Commingled Production via Waterflooding for Multilayer Offshore Heavy Oil Reservoirs

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2428 ◽  
Author(s):  
Fei Shen ◽  
Linsong Cheng ◽  
Qiang Sun ◽  
Shijun Huang
Keyword(s):  
Heavy Oil ◽  
Flow Model ◽  
Dynamic Method ◽  
Theoretical Models ◽  
Oil Reservoirs ◽  
Sweep Efficiency ◽  
One Dimensional ◽  
Heavy Oil Reservoirs ◽  
The Difference ◽  
Important Form

Recently, commingling production has been widely used for the development of offshore heavy oil reservoirs with multilayers. However, the differences between layers in terms of reservoir physical properties, oil properties and pressure have always resulted in interlayer interference, which makes it more difficult to evaluate the producing degree of commingled production. Based on the Buckley–Leverett theory, this paper presents two theoretical models, a one-dimensional linear flow model and a planar radial flow model, for water-flooded multilayer reservoirs. Through the models, this paper establishes a dynamic method to evaluate seepage resistance, sweep efficiency and recovery percent and then conducts an analysis with field data. The result indicates the following: (1) the dynamic difference in seepage resistance is an important form of interlayer interference during the commingled production of an offshore multilayer reservoir; (2) the difference between commingled production and separated production is small within a certain range of permeability ratio or viscosity ratio, but separated production should be adopted when the ratio exceeds a certain value.

Reduction of Computing Time and Improvement of Convergence Stability of the Monte Carlo Method Applied to Radiative Heat Transfer With Variable Properties

1989 ◽  
Vol 111 (1) ◽  
pp. 135-140 ◽  
Author(s):  
M. Kobiyama
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Computing Time ◽  
Energy Difference ◽  
Radiative Properties ◽  
Radiative Energy ◽  
Control Element ◽  
The Monte Carlo Method ◽  
The Difference ◽  
Convergence Stability

A modified Monte Carlo method is suggested to reduce the computing time and improve the convergence stability of iterative calculations without losing other excellent features of the conventional Monte Carlo method. In this method, two kinds of radiative bundle are used: energy correcting bundles and property correcting bundles. The energy correcting bundles are used for correcting the radiative energy difference between two successive iterative cycles, and the property correcting bundles are used for correcting the radiative properties. The number of radiative energy bundles emitted from each control element is proportional to the difference in emissive energy between two successive iterative cycles.

scholarly journals Potential of seasonal hydrological forecasting of monthly run-off volumes for the Rhone and Arve Rivers from April to July

2018 ◽  
Author(s):  
Oriane Etter ◽  
Frédéric Jordan ◽  
Anton J. Schleiss
Keyword(s):  
Confidence Interval ◽  
Seasonal Forecast ◽  
Seasonal Forecasting ◽  
Average Error ◽  
Lead Times ◽  
Streamflow Forecasting ◽  
Rhône River ◽  
Run Off ◽  
Rhone River ◽  
The Difference

Abstract. In a context where water management is becoming increasingly important, reliable seasonal forecasting of discharge in rivers is crucial for making decisions several months in advance. This paper explores the potential of seasonal forecasting of run-off volumes produced by ensemble streamflow forecasting using past climatology and comparing it to the more commonly used average of past discharge measurements. The seasonal forecast was obtained for the Arve and Rhone rivers by simulation using the Routing System model for lead times of 30, 90 and 120 days. The initialization was performed on a validated simulation of 12 and 16 years for the Arve and Rhone rivers, respectively, obtained through long-term calibration. The performance was assessed by indicators called accuracy and thinness. The normalized mean average error (NMAE) was used to compare the performance of the seasonal forecast with the average of the past measurements. After a bias correction of the seasonal forecast of the Rhone River with the observed run-off volumes during the different lead times, the correlation of the median forecast with the measurements (accuracy) was larger than 0.55 for all lead times from April to July. The Arve River's accuracy was improved by disregarding the year 2007 member, leading to the floods of the 3rd and 9th of July, for lead times of 90 and 120 days. This resulting in the period of April to July having correlation accuracies higher than 0.5. For both rivers, the 80 % confidence interval of the seasonal forecast was relatively thin compared to the measurements (thinness) for the months of April to July. The NMAE was used to validate the range of validity of the forecast. The correction of the forecast resulted in more months being favorable for seasonal forecasting for the Rhone River. The post-processing on the Arve River decreased the difference between the measurement and the forecast (NMAE). Further investigation should concentrate on dividing the meteorological datasets to produce a strong median forecast and confidence interval

scholarly journals Validation of a Monte Carlo Modelling Based Dosimetry of Extraoral Photobiomodulation

Diagnostics ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2207
Author(s):  
Anna N. Yaroslavsky ◽  
Amy F. Juliano ◽  
Ather Adnan ◽  
Wayne J. Selting ◽  
Tyler W. Iorizzo ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Light Emitting Diode ◽  
Morphological Data ◽  
Transmitted Power ◽  
Light Dosimetry ◽  
Mean Values ◽  
Mri Scans ◽  
The Difference

An in vivo validation study was performed to confirm the accuracy of extraoral photobiomodulation therapy (PBMT) dosimetry determined by modelling. The Monte Carlo technique was utilized to calculate the fluence rate and absorbed power of light delivered through multi-layered tissue. Optical properties used during Monte Carlo simulations were taken from the literature. Morphological data of four study volunteers were acquired using magnetic resonance imaging (MRI) scans. Light emitting diode (LED) coupled to a power meter were utilized to measure transmitted power through each volunteer’s cheek, in vivo. The transmitted power determined by Monte Carlo modelling was compared to the in vivo measurements to determine the accuracy of the simulations. Experimental and simulation results were in good agreement for all four subjects. The difference between the mean values of the measured transmission was within 12% from the respective transmission obtained using Monte Carlo simulations. The results of the study indicate that Monte Carlo modelling is a robust and reliable method for light dosimetry.

Construction and Experimental Study of an Elevation Linear Fresnel Reflector

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
J. D. Nixon ◽  
P. A. Davies
Keyword(s):  
Heat Loss ◽  
Thermal Efficiency ◽  
Theoretical Models ◽  
Loss Coefficient ◽  
Heat Transfer Fluid ◽  
Stagnation Temperature ◽  
Model Predictions ◽  
The Difference ◽  
Predicted Values ◽  
Linear Fresnel Reflector

This paper outlines a novel elevation linear Fresnel reflector (ELFR) and presents and validates theoretical models defining its thermal performance. To validate the models, a series of experiments were carried out for receiver temperatures in the range of 30–100 °C to measure the heat loss coefficient, gain in heat transfer fluid (HTF) temperature, thermal efficiency, and stagnation temperature. The heat loss coefficient was underestimated due to the model exclusion of collector end heat losses. The measured HTF temperature gains were found to have a good correlation to the model predictions—less than a 5% difference. In comparison to model predictions for the thermal efficiency and stagnation temperature, measured values had a difference of −39% to +31% and 22–38%, respectively. The difference between the measured and predicted values was attributed to the low-temperature region for the experiments. It was concluded that the theoretical models are suitable for examining linear Fresnel reflector (LFR) systems and can be adopted by other researchers.

Assessing Wear Evolutions in Railway Wheelsets Using a Survival Modeling Approach

2021 ◽  
Author(s):  
Guilerme A. C. Caldeira ◽  
JoaquimAP Braga ◽  
António R. Andrade
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Life Cycle ◽  
Condition Based Maintenance ◽  
Monitoring Systems ◽  
Simulation Procedure ◽  
Condition Monitoring Systems ◽  
Survival Modeling ◽  
Wheel Profile ◽  
Independence Of Events

Abstract The present paper provides a method to predict maintenance needs for the railway wheelsets by modeling the wear out affecting the wheelsets during its life cycle using survival analysis. Wear variations of wheel profiles are discretized and modelled through a censored survival approach, which is appropriate for modeling wheel profile degradation using real operation data from the condition monitoring systems that currently exist in railway companies. Several parametric distributions for the wear variations are modeled and the behavior of the selected ones is analyzed and compared with wear trajectories computed by a Monte Carlo simulation procedure. This procedure aims to test the independence of events by adding small fractions of wear to reach larger wear values. The results show that the independence of wear events is not true for all the established events, but it is confirmed for small wear values. Overall, the proposed framework is developed in such a way that the outputs can be used to support predictions in condition-based maintenance models and to optimize the maintenance of wheelsets.

CONCEPTUAL AND OPERATIONAL DIFFERENCES BETWEEN GENERAL TAKAFUL AND CONVENTIONAL INSURANCE

2012 ◽  
Vol 01 (08) ◽  
pp. 23-28
Author(s):  
Mher Mushtaq Hussain ◽  
Ahmad Tisman Pasha
Keyword(s):  
Present Article ◽  
Conventional System ◽  
Mutual Help ◽  
Insurance Business ◽  
The Difference ◽  
Islamic Insurance ◽  
Islamic Society

Insurance in Islam is essentially a concept of mutual help. Insurance business under conventional system is based on uncertainty, which is prohibited in Islamic society under Islamic principles. So there is need to clear the difference between the conventional insurance and the Islamic insurance. A rich literature also describes such differences but the present article addresses the differences based on conceptual and operational framework.

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