scholarly journals The theoretical surrender value in life insurance

2016 ◽  
Vol 7 (1) ◽  
pp. 31-44 ◽  
Author(s):  
Nicolino Ettore D’Ortona ◽  
Maria Sole Staffa
Keyword(s):  
Stochastic Simulation ◽  
Life Insurance ◽  
Stochastic Models ◽  
Calculation Method ◽  
Risk Model ◽  
Insurance Company ◽  
Simulation Approach ◽  
Method Of Calculation ◽  
Insurance Portfolio ◽  
Value Determination

In the context of the stochastic models for the management of life insurance portfolio, the authors explore, with simulation approach, the effects induced by the application of a particular method of calculation of the surrender value. In the life insurance, the policyholder position is, at any moment, quantified by the mathematical reserve. In case the reserve amount results are positive, the insurance company can allow the contract surrender, consisting in an amount payment, called surrender value, commensurate with the mathematical reserve. Generally, the insurance company enforces some restrictions in the surrender value determination, in order to avoid, first of all, that an amount is disbursed to the policyholder while, on the contrary, he results to be indebted to the Company. In this paper the authors will consider a surrender value calculation method based precisely on the profit recovery concept which shall be supplied by the contract in case it remains in the portfolio. Additionally, the authors shall analyze, by simulation approach, the effects caused by the enforcement of the surrender value calculation concept on a life portfolio profitability, and on the penalties extent enforced to the policyholders which cancel from the contract. Keywords: surrender value, life insurance, internal risk model, stochastic simulation

scholarly journals Collective Value-At-Risk (Colvar) In Life Insurance Collection

2018 ◽  
Vol 7 (3.7) ◽  
pp. 25
Author(s):  
Abdul Talib Bon ◽  
Muhammad Iqbal Al-Banna Ismail ◽  
Sukono . ◽  
Adhitya Ronnie Effendie
Keyword(s):  
At Risk ◽  
Standard Deviation ◽  
Life Insurance ◽  
Value At Risk ◽  
Risk Model ◽  
Risk Measures ◽  
Model Development ◽  
Insurance Company ◽  
Insurance Claims ◽  
Level Of Significance

Analysis of risk in life insurance claims is very important to do by the insurance company actuary. Risk in life insurance claims are generally measured using the standard deviation or variance. The problem is, that the standard deviation or variance which is used as a measure of the risk of a claim can not accommodate any claims of risk events. Therefore, in this study developed a model called risk measures Collective Modified Value-at-Risk. Model development is done for several models of the distribution of the number of claims and the distribution of the value of the claim. Collective results of model development Modified Value-at-Risk is expected to accommodate any claims of risk events, when given a certain level of significance  

scholarly journals PENENTUAN CADANGAN PREMI UNTUK ASURANSI JOINT LIFE

2016 ◽  
Vol 5 (1) ◽  
pp. 32
Author(s):  
NI LUH PUTU RATNA DEWI ◽  
I NYOMAN WIDANA ◽  
DESAK PUTU EKA NILAKUSMAWATI
Keyword(s):  
Interest Rates ◽  
Life Insurance ◽  
Calculation Method ◽  
First Year ◽  
Insurance Company ◽  
Premium Payment ◽  
Mortality Table ◽  
Constant Interest ◽  
Annual Premium

Premium reserve is a number of fund that need to be raised by insurance company in preparation for the payment of claims. This study aims to get the formula of premium reserve as well as the value of the premium reserve for joint life insurance by using retrospective calculation method. Joint life insurance participants in this study are limited to 2 people. Calculations in this study is using Indonesian Mortality Table (TMI) 2011, joint life mortality tables, commutation tables, value of annuities, value of single premiums and constant annual premium and using constant interest rates of 5%. The results showed that by using age of the participant insurance joint life of x = 50 and y = 45 years and the premium payment period of t = 10 years, we obtained that the value of premium reserve from the end of the first year until the  end of the 11th year has increased every year, while the value of premium reserves from the end of the 12th year and so on until a lifetime has decreased every year.

scholarly journals Geometric-Gamma Collective Modified Value-at-Risk Model in Life Insurance Risk

2018 ◽  
Vol 7 (3.20) ◽  
pp. 372
Author(s):  
Muhammad Iqbal Al-Banna Ismail ◽  
Sukono . ◽  
Abdul Talib BIN Bon ◽  
Yuyun Hidayat ◽  
Eman Lesmana ◽  
...  
Keyword(s):  
At Risk ◽  
Life Insurance ◽  
Value At Risk ◽  
Risk Model ◽  
Risk Measure ◽  
Insurance Companies ◽  
Insurance Company ◽  
Insurance Risk ◽  
Collective Risk Model ◽  
Collective Risk

Claim risk is a payment made by the insurance company to the policyholder. Actuaries in insurance companies should be able to measure and control the risk of claims, in order to avoid losses to insurance companies. In this paper we analyze the Geometric-Gamma Collective Modified Value-at-Risk model in life insurance risk. In this research, there is a development of claim risk measure called Collective Modified Value-at-Risk, which is an extension of Collective Risk model. This Collective Modified Value-at-Risk model requires estimation of the mean, variance, skewness, and kurtosis parameters. The result of this research, is that the extent of this model can be applied to the risk of claims amount of non-normal distributed. Thus, the Collective Modified Value-at-Risk model can serve as one of the statistical alternatives for measuring the risk of claims on life insurance.  

Tuesday Evening

PMLA ◽  
1935 ◽  
Vol 50 (4) ◽  
pp. 1357-1357
Keyword(s):  
Life Insurance ◽  
Insurance Company ◽  
Life Insurance Company ◽  
Local Committee ◽  
Tuesday Evening

On Tuesday evening the members of the Association, and attending members of their families, were entertained with a buffet supper at the Queen City Club at 7:30 p.m. at the invitation of Messrs. Joseph S. Graydon, John J. Rowe, and other Cincinnati friends of the Association. Following this supper an entertainment arranged by the Local Committee was presented in the Hall of the Western and Southern Life Insurance Company. Attendance: about 900.

Hr Practices And Hr Policies At Icici Prudential Life Insurance Company Ltd

Think India ◽  
2019 ◽  
Vol 22 (3) ◽  
pp. 348-354
Author(s):  
T. Krishna Veni ◽  
G. Kalyani
Keyword(s):  
Human Resources ◽  
Life Insurance ◽  
Insurance Company ◽  
Life Insurance Company ◽  
Hr Practices ◽  
Commercial Center

The job of Human Resources is changing as quick as innovation and the worldwide commercial center. Generally, the HR Department was seen as organization, kept individual documents and different records, dealt with the enlisting procedure, and gave other authoritative help to the business. Those circumstances are different. The positive consequence of these progressions is that HR experts have the chance to assume a progressively vital job in the business. The test for HR chiefs is to stay up with the latest with the most recent HR developments—mechanical, lawful, and something else.

Indian Life Insurance Market and Corporate Performances: A Study of Selected Firms

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Joy Chakraborty ◽  
Partha Pratim Sengupta
Keyword(s):  
Market Share ◽  
Life Insurance ◽  
Market Concentration ◽  
Insurance Market ◽  
Insurance Companies ◽  
Insurance Company ◽  
Life Insurance Company ◽  
Insurance Sector ◽  
Life Insurers ◽  
Company Limited

In the pre-reform era, Life Insurance Corporation of India (LICI) dominated the Indian life insurance market with a market share close to 100 percent. But the situation drastically changed since the enactment of the IRDA Act in 1999. At the end of the FY 2012-13, the market share of LICI stood at around 73 percent with the number of players having risen to 24 in the countrys life insurance sector. One of the reasons for such a decline in the market share of LICI during the post-reform period could be attributed to the increasing competition prevailing in the countrys life insurance sector. At the same time, the liberalization of the life insurance sector for private participation has eventually raised issues about ensuring sound financial performance and solvency of the life insurance companies besides protection of the interest of policyholders. The present study is an attempt to evaluate and compare the financial performances, solvency, and the market concentration of the four leading life insurers in India namely the Life Insurance Corporation of India (LICI), ICICI Prudential Life Insurance Company Limited (ICICI PruLife), HDFC Standard Life Insurance Company Limited (HDFC Standard), and SBI Life Insurance Company Limited (SBI Life), over a span of five successive FYs 2008-09 to 2012-13. In this regard, the CARAMELS model has been used to evaluate the performances of the selected life insurers, based on the Financial Soundness Indicators (FSIs) as published by IMF. In addition to this, the Solvency and the Market Concentration Analyses were also presented for the selected life insurers for the given period. The present study revealed the preexisting dominance of LICI even after 15 years since the privatization of the countrys life insurance sector.

Stochastic simulation for determining the design flood of cascade reservoir systems

2012 ◽  
Vol 43 (1-2) ◽  
pp. 54-63 ◽  
Author(s):  
Baohong Lu ◽  
Huanghe Gu ◽  
Ziyin Xie ◽  
Jiufu Liu ◽  
Lejun Ma ◽  
...  
Keyword(s):  
Simulation Model ◽  
Stochastic Simulation ◽  
Southern China ◽  
Flow Simulation ◽  
Simulation Method ◽  
Simulation Approach ◽  
Design Flood ◽  
Design Values ◽  
Stochastic Simulation Model ◽  
The Impact

Stochastic simulation is widely applied for estimating the design flood of various hydrosystems. The design flood at a reservoir site should consider the impact of upstream reservoirs, along with any development of hydropower. This paper investigates and applies a stochastic simulation approach for determining the design flood of a complex cascade of reservoirs in the Longtan watershed, southern China. The magnitude of the design flood when the impact of the upstream reservoirs is considered is less than that without considering them. In particular, the stochastic simulation model takes into account both systematic and historical flood records. As the reliability of the frequency analysis increases with more representative samples, it is desirable to incorporate historical flood records, if available, into the stochastic simulation model. This study shows that the design values from the stochastic simulation method with historical flood records are higher than those without historical flood records. The paper demonstrates the advantages of adopting a stochastic flow simulation approach to address design-flood-related issues for a complex cascade reservoir system.

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