Outstanding Claims Reserve Research Articles

ESTIMASI CADANGAN KLAIM PADA ASURANSI UMUM DENGAN METODE CHAIN LADDER

Based on the 2020 Insurance Statistic Data released by OJK, the ratio of gross claims to gross premiums has increased due to the growth of gross premiums followed by increasing claims paid. Thus, the insurance company is obliged to provides claim reserve that is important to be estimated appropriately, especially outstanding claim reserves. This is because outstanding claim reserves are needed to cover underpayment on future claims. One popular method to estimate outstanding claim reserves is the Chain Ladder method. This study aims to determine the results of the estimated outstanding claim reserves on general insurance using Mack’s CL method. CL method is a method to estimate claim reserves simply without satisfying certain distribution assumptions. This study uses incremental run-off triangle data taken from Weindofer's research article (2012) with an event period of 2005-2012 and a development period of 8 years. Based on the calculations in this study, an estimated outstanding claim reserve of USD 20,109.82 was obtained, meaning the funds that must be prepared amounted to USD 20,109.82 in 2013 by the general insurance company that owns the data studied. It also serves as a benchmark in the determination of claim reserves in the 2013 financial statements

PEMODELAN KLAIM ASURANSI MENGGUNAKAN PENDEKATAN BAYESIAN DAN MARKOV CHAIN MONTE CARLO

The determination of the correct prediction of claims frequency and claims severity is very important in the insurance business to determine the outstanding claims reserve which should be prepared by an insurance company. One approach which may be used to predict a future value is the Bayesian approach. This approach combines the sample and the prior information The information is used to construct the posterior distribution and to determine the estimate of the parameters. However, in this approach, integrations of functions with high dimensions are often encountered. In this Thesis, a Markov Chain Monte Carlo (MCMC) simulation is used using the Gibbs Sampling algorithm to solve the problem. The MCMC simulation uses ergodic chain property in Markov Chain. In Ergodic Markov Chain, a stationary distribution, which is the target distribution, is obtained. The MCMC simulation is applied in Hierarchical Poisson Model. The OpenBUGS software is used to carry out the tasks. The MCMC simulation in Hierarchical Poisson Model can predict the claims frequency.

Prediction of Technical Reserves Based on Grey Model — GM(1,1): Evidence from Non-life Egyptian Insurance Market

Grey system theory is a mathematical technique used to predict data with known and unknown characteristics. The aim of our research is to forecast the future amount of technical reserves (outstanding claims reserve, loss ratio fluctuations reserve and unearned premiums reserve) up to 2029/2030. This study applies the Grey Model GM(1,1) using data obtained from the Egyptian Financial Supervisory Authority (EFSA) over the period from 2005/2006 to 2015/2016 for non-life Egyptian insurance market. We found that the predicted amounts of outstanding claims reserve and loss ratio fluctuations reserve are highly significant than the unearned premiums reserve according to the value of Posterior Error Ratio (PER).

A comparative analysis of outstanding claim reserves

A comparative analysis of outstanding claim reserves

Robustifying the multivariate chain-ladder method: A comparison of two methods

The expected result of a non-life insurance company is usually determined for its activity in different business lines as a whole. This implies that the claims reserving problem for a portfolio of several (perhaps correlated) subportfolios is to be solved. A popular technique for studying such a portfolio is the chain-ladder method. However, it is well known that the chain-ladder method is very sensitive to outlying data. For the bivariate situation, we have already developed robust solutions for the chain-ladder method by introducing two techniques for detecting and correcting outliers. In this article we focus on higher dimensions. Being subjected to multiple constraints (no graphical plots available), the goal of our research is to find solutions to detect and smooth the influence of outlying data on the outstanding claims reserve in higher dimensional data sets. The methodologies are illustrated and computed for real examples from the insurance practice.

Estimating IBNR claims reserves for general insurance using Archimedean copulas

Claims reserving for general insurance business has developed significantly over the recent past. There has always been a slight mystery in short-term insurance contracts of how to go about reserving for claims, which have not yet come in, and are still in some sense of figment of the future. Insurance claims variables are non-normally distributed and therefore a measure that will capture the dependence among the variables better than the usual correlation is employed. One such method is the use of copulas. The object of this paper, therefore, is to use the Archimedean copula, Clayton copula and Frank copula to estimate outstanding incurred but not reported (IBNR) claim reserves. A comparison of the estimates of outstanding claim reserves obtained from different Archimedean copulas is also presented.

A Stochastic Minimax Model to Calculate Outstanding Claims

Correct estimation of the Outstanding Claims Reserve, an item that includes Incurred But Not Reported Claims (IBNR) as well as Incurred But Not Enough Reserved Claims (IBNER), is one of the most important issues currently facing actuarial science, due to its effect on the technical and financial stability of insurance companies. The purpose of this paper is to calculate the reserve in a decision-making environment, so that estimates can be made according to accurately defined and previously established rational criteria. Specifically, the estimating process enables a company’s particular situation to be taken into account, by incorporating its approach to the consequences arising from estimation errors into the model. The proposed calculation method gives rise to optimum link ratio estimators that can also be interpreted from a Bayesian perspective, with the advantages associated to such methodology.

Bayesian Estimation of Outstanding Claim Reserves

This paper presents a Bayesian approach to forecasting outstanding claims, either the total number of claims or the total amount, that is used for claims reserving. The assumption is made that there is complete information for one or two past years of origin and partial information for some development years of other years of origin. It also assumes payments are made annually and that the development of partial payments follows a stable payoff pattern from one year of origin to another. Two different models are presented: one for the number of claims (intensity) and one for claim amounts (severity). The advantage of using this procedure is that actuaries can derive the complete predictive distribution of the reserve requirements, from which, in turn, it is possible to obtain point estimates as well as probability intervals and other summary measures, such as mean, variance, and quantiles.

Motor Outstanding Claims.

A Report with the above title, which forms Section B of this paper, was presented at the conference at Hythe, Kent in September 1977 of the General Insurance Study Group, which is sponsored jointly by the Institute and the Faculty. The conference was attended by about sixty people, nearly all non-life practitioners and nearly all actuaries.Previous papers on technical reserves had discussed various statistical methods of estimating outstanding claim reserves, and in some cases had included some data to provide numerical examples of the use of the methods. In our report we chose tostartwith some data and to look at the degree of stability in those data. Inspection of the data showed remarkably stable patterns and it was apparent that a simple method not previously described based on average payments was likely to be satisfactory for estimating the reserve for outstanding claims. The report then seeks to explain why the authors consider that this method has advantages over two well-known but more complicated methods.

Claim reserves in general insurance

1.1. This paper is concerned with claim reserves in general insurance. General, or non-Life, insurance may be taken to include such classes of business as Motor, Liability, Property, etc., and the claim reserves with which the paper is concerned are usually described as ‘outstanding claims reserves’ or ‘reserves for claims incurred but not reported’ (I.B.N.R.). Each of these reserves falls under the heading of ‘technical reserves’, and may be referred to as ‘provisions’ by the accountancy profession. Such reserves are intended in some sense to represent the liability of the insurer arising from events which have occurred within the scope of, and during the period of currency of, the insurance. It is implicit in the definition of such reserves that there is defined a specific date, which will be referred to in this paper as the accounting date, to which the reserves relate. The need for outstanding claim reserves arises from the separation in time of the reporting of a claim to an insurer from the subsequent settlement of that claim, whether this settlement involves the payment of a positive sum by the insurer, or whether, in the event, no payment is made.