scholarly journals Penerapan Metode Limited-Fluctuation Credibility dalam Menentukan Premi Murni pada Asuransi Kendaraan Bermotor di PT XYZ

2021 ◽  
Vol 4 (2) ◽  
pp. 126
Author(s):  
Mira Zakiah Rahmah ◽  
Aceng Komarudin Mutaqin
Keyword(s):  
Motor Vehicle ◽  
Secondary Data ◽  
Past Experience ◽  
Credibility Theory ◽  
Partial Loss ◽  
Pure Premium ◽  
Premium Rates ◽  
Motor Vehicle Insurance ◽  
Insurance Data

<p><strong>Abstract. </strong>This paper discusses the method of limited-fluctuation credibility, also known as classic credibility. Credibility theory is a technique for predicting future premium rates based on past experience data. Limited fluctuation credibility consists of two credibility, namely full credibility if Z = 1 and partial credibility if Z &lt;1. Full credibility is achieved if the amount of recent data is sufficient for prediction, whereas if the latest data is insufficient then the partial credibility approach is used. Calculations for full and partial credibility standards are used for loss measures such as frequency of claims, size of claims, aggregate losses and net premiums. The data used in this paper is secondary data recorded by the company PT. XYZ in 2014. This data contains data on the frequency of claims and the size of the policyholder's partial loss claims for motor vehicle insurance products category 4 areas 1. Based on the results of the application, the prediction of pure premiums for 2015 cannot be fully based on insurance data for 2014 because the credibility factor value is less than 1. So based on the limited-fluctuation credibility method, the prediction of pure premiums for 2015 must be based on manual values for pure premiums as well as insurance data for 2014. If manual values for pure premium is 2,000,000 rupiah, then the prediction of pure premium for 2015 is 1,849,342 rupiah.</p><p><strong>Keywords</strong><strong>: </strong>limited fluctuation credibility, full credibility, partial credibility and partial loss</p>

scholarly journals Directions in the Development of Commercial Insurance in Poland and Lithuania

2014 ◽  
Vol 17 (1) ◽  
pp. 145-165
Author(s):  
Justyna Witkowska ◽  
Aušrinė Lakštutienė
Keyword(s):  
Life Insurance ◽  
Motor Vehicle ◽  
Third Party ◽  
Liability Insurance ◽  
Insurance Market ◽  
Commercial Insurance ◽  
Property Insurance ◽  
Group 3 ◽  
Motor Vehicle Insurance ◽  
Insurance Data

This article analyses trends in the development of the commercial insurance market in Poland and in Lithuania over the last decade. The insurance market changed in the 2002-2011 period. Those changes can be seen in various fields of commercial insurance. Data on the number of insurers, total premiums written, and the trends in claim payments and claim ratios were used to perform a market trend analysis. It should be emphasized that Poland experienced the results of the financial crisis in the insurance market later than Lithuania, which is visible in specific ratios under analysis. In Lithuania, in terms of insurance expenditures, non-life insurance products are definitely more popular, while in Poland life insurance plays the most important role. Poles buy most life insurance from group 1, and Lithuanians from group 3. In the case of non-life insurance, motor vehicle insurance (third-party liability insurance and casco (collision/personal liability insurance)) and property insurance are the leading forms of insurance purchased by both Poles and Lithuanians, as well as other Europeans.

scholarly journals IMPLEMENTASI METODE BAYES PADA PENGHITUNGAN PREMI ASURANSI KENDARAAN BERMOTOR

2020 ◽  
Vol 3 (2) ◽  
pp. 112-123
Author(s):  
Rika Fitriani ◽  
Gunardi Gunardi
Keyword(s):  
Historical Data ◽  
Motor Vehicle ◽  
Insurance Premium ◽  
Insurance Companies ◽  
Bayes Method ◽  
General Insurance ◽  
Pure Premium ◽  
Historical Data Analysis ◽  
Claim Frequency ◽  
Motor Vehicle Insurance

One type of general insurance is motor vehicle insurance. Premium pricing of general insurance can be calculated by some methods. In this study, Bayes method will be used. The distribution of claim frequency is Poisson distribution and the distribution of claim severity is Exponential distribution. The premium is calculated by multiplying the expectation of claim frequency and the expectation of claim severity. Based on the historical data analysis using the Bayes method, the highest pure premium of motor vehicle insurance in Indonesia is Hino brand and the lowest pure premium is Honda brand. The result of this premium pricing can be used as a reference for the insurance companies to manage their motor vehicle insurance reserves.

scholarly journals PERHITUNGAN PREMI MURNI PADA SISTEM BONUS MALUS UNTUK FREKUENSI KLAIM BERDISTRIBUSI BINOMIAL NEGATIF DAN BESAR KLAIM BERDISTRIBUSI WEIBULL PADA DATA ASURANSI KENDARAAN BERMOTOR DI INDONESIA

2021 ◽  
Vol 10 (2) ◽  
pp. 170-179
Author(s):  
Rillifa Iris Adisti ◽  
Aceng Komarudin Mutaqin
Keyword(s):  
Weibull Distribution ◽  
Risk Premium ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Motor Vehicle ◽  
Secondary Data ◽  
Insurance Company ◽  
Partial Loss ◽  
Premium Calculation

System bonus malus is one of the systems offered by an insurance company where the risk premium calculation is based on the claim history of each policyholder. In study will be discussed premium calculation in system, bonus malus  where the frequency of claims has a negative binomial distribution and the size of claims is Weibull distribution on motor vehicle insurance data in Indonesia. This method will producesystem an bonus malus optimal by finding the posterior distribution using Bayes analysis. As the application material used secondary data from the recording results obtained from the general insurance company PT. XYZ in 2014, data contains data on the frequency of claims and the amount ofclaims partial loss of policyholders forinsurance products for comprehensivemotor vehicle insurance category 8 regions 3.The results of the implementation show that the premiums with the system are bonus malus optimalconsidered fair enough because the premiums paid by policyholders insurance that extends the policy in the following year is proportional to the risk it faces, where the premium to be paid by each policyholder is based on past claims history. Keywords: system bonus malus, negative binomial distribution, Weibull distribution, comprehensive,  partial loss.

PROSES PEMBAYARAN KLAIM ASURANSI KENDARAAN BERMOTOR BAGI TERTANGGUNG (Studi di Brins General Insurance Cabang Yogyakarta)

2019 ◽  
Vol 7 (1) ◽  
pp. 130
Author(s):  
Atyanta Nanda Dhanistha , ◽  
Djuwityastuti ,
Keyword(s):  
Motor Vehicle ◽  
Secondary Data ◽  
Motor Vehicles ◽  
Data Types ◽  
Literature Study ◽  
Insurance Claim ◽  
Commercial Law ◽  
General Insurance ◽  
Analysis Technique ◽  
Motor Vehicle Insurance

<p>Abstract<br />This article aims to explaining completion of the insurance claim payment motorized vehicles for insured in <br />BRINS General Insurance Branch Yogyakarta. This study examines the problems, firstly how the rejection <br />of motor vehicle insurance claims and settlement of payments for the insured at BRINS General Insurance <br />Branch Yogyakarta. Secondly, does the rejection of claims occurring at BRINS General Insurance Branch <br />Yogyakarta is in accordance with the laws and regulations. This research is an empirical normative legal <br />research that is descriptive. Secondary data types include primary and secondary legal materials. Data <br />collection techniques used are literature study and interview, then the analysis technique used is qualitative <br />method. The results showed that the call to pay motor vehicle insurance at BRINS Branch Yogyakarta <br />General Insurance is done through the stages, also using Article 31 paragraph (3) of Law Number 40 <br />Year 2014 as a guidance that is handling risk quickly, easily, easily accessed and fair. The settlement <br />of insurance claim payment at BRINS Branch Yogyakarta Public Insurance is based on the existing <br />provisions of Law Number 40 Year 2014 regarding the rules of implementation in the OJK Regulations, <br />the Book of Commercial Law, the Civil Code and the Standard of Motor Vehicle Insurance Indonesia. It <br />can be proved by Article 29 paragraph (2) and paragraph (3) of OJK Regulation No. 69/POJK.05/2016 <br />that the premium payment has been made which resulted in the responsibility of the Insurer.<br />Keywords: Payments; claims; agreements; motor vehicles</p><p>Abstrak<br />Artikel ini bertujuan untuk menjelaskan penyelesaian pembayaran klaim asuransi kendaraan bermotor di <br />BRINS General Insurance Cabang Yogyakarta. Penelitian ini mengkaji permasalahan, pertama bagaimana <br />penolakan klaim asuransi kendaraan bermotor dan penyelesaian pembayarannya bagi tertanggung di <br />BRINS General Insurance Cabang Yogyakarta. Kedua, apakah penolakan klaim yang terjadi di BRINS <br />General Insurance Cabang Yogyakarta sudah sesuai dengan peraturan perundang-undangan. Penelitian <br />ini adalah penelitian hukum normatif empiris yang bersifat deskriptif. Jenis data sekunder meliputi bahan <br />hukum  primer  dan  sekunder.  Teknik  pengumpulan  data  yang  digunakan  adalah  studi  kepustakaan <br />dan wawancara, selanjutnya teknik analisis yang digunakan adalah metode kualitatif. Hasil penelitian <br />menunjukkan bahwa penyelesaian pembayaran klaim asuransi kendaraan bermotor di BRINS General <br />Insurance  Cabang Yogyakarta  dilakukan  melalui  tahapan  yang  telah  ditentukan,  serta  menjadikan <br />Pasal 31 ayat (3) Undang-Undang Nomor 40 Tahun 2014 sebagai pedoman yaitu penanganan klaim <br />secara cepat, sederhana, mudah diakses, dan adil. Penyelesaian pembayaran klaim asuransi di BRINS <br />General Insurance Cabang Yogyakarta dilakukan berdasarkan perundang-undangan yang ada yaitu <br />Undang-Undang Nomor 40 Tahun 2014 beserta peraturan pelaksanaannya dalam Peraturan OJK, Kitab <br />Undang-Undang Hukum Dagang, Kitab Undang-Undang Hukum Perdata, serta Polis Standar Asuransi <br />Kendaraan Bermotor Indonesia.Hal ini dapat dibuktikan melalui Pasal 29 ayat (2) dan ayat (3) Peraturan <br />OJK Nomor 69/POJK.05/2016 bahwa apabila pembayaran premi telah dilakukan maka pembayaran <br />klaim asuransi yang timbul merupakan tanggung jawab Penanggung.<br />Kata Kunci : Pembayaran; klaim; perjanjian; kendaraan bermotor</p>

scholarly journals Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves

2021 ◽  
Vol 2 (1) ◽  
pp. 38-48
Author(s):  
Ria Novita Suwandani ◽  
Yogo Purwono
Keyword(s):  
Gaussian Process ◽  
Motor Vehicle ◽  
Gaussian Process Regression ◽  
Theory And Practice ◽  
Chain Ladder Method ◽  
Business Line ◽  
Chain Ladder ◽  
Motor Vehicle Insurance ◽  
Insurance Data ◽  
Process Method

This study aims to calculate the allowance for losses by applying Gaussian Process regression to estimate future claims. Modeling is done on motor vehicle insurance data. The data used in this study are historical data on PT XYZ's motor vehicle insurance business line during 2017 and 2019 (January 2017 to December 2019). Data analysis will be carried out on the 2017 - 2019 data to obtain an estimate of the claim reserves in the following year, namely 2018 - 2020. This study uses the Chain Ladder method which is the most popular loss reserving method in theory and practice. The estimation results show that the Gaussian Process Regression method is very flexible and can be applied without much adjustment. These results were also compared with the Chain Ladder method. Estimated claim reserves for PT XYZ's motor vehicle business line using the chain-ladder method, the company must provide funds for 2017 of 8,997,979,222 IDR in 2018 16,194,503,605 IDR in 2019 amounting to Rp. 1,719,764,520 for backup. Meanwhile, by using the Bayessian Gaussian Process method, the company must provide funds for 2017 of 9,060,965,077 IDR in 2018 amounting to 16,307,865,130 IDR, and in 2019 1,731,802,871 IDR for backup. The more conservative Bayessian Gaussian Process method. Motor vehicle insurance data has a short development time (claims occur) so that it is included in the short-tail type of business.

ANALISA KESEHATAN KEUANGAN PERUSAHAAN UNTUK MEMPREDIKSI KEBANGKRUTAN PERUSAHAAN DENGAN MENGGUNAKAN METODE ALTMAN (STUDI KASUS PADA PERUSAHAAN MANUFAKTUR SEKTOR KOMPONEN OTOMOTIF YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2011 – 2015)

2019 ◽  
Vol 13 (2) ◽  
pp. 55
Author(s):  
Indar Khaerunnisa ◽  
Edy Cahyadi
Keyword(s):  
Motor Vehicle ◽  
Stock Exchange ◽  
Secondary Data ◽  
Z Score ◽  
Financial Ratio ◽  
Average Value ◽  
Automotive Components ◽  
Grey Area ◽  
Financial Ratio Analysis ◽  
Year 2013

The Indonesian government has set the motor vehicle industry as one of the priority industries of the national interest, economic growth, and increased productivity. In order for the survival of a company is maintained, then the management should be able to maintain or even more spur increased performance. Various analyzes were developed to predict the beginning of the bankruptcy of the company. One analysis is widely used today is the analysis of Altman Z-Score, which this analysis refers to the financial ratios of the company. The purpose of this study was to analyze the bankruptcy of the automotive components companies that go public in Indonesia Stock Exchange year period 2011–2015. This study used a sample of four companies from the automotive components sector. Source of data is done by using secondary data. The data is processed by the method of the Z-score formula Z = 1,2X1 + 1,4X2 + 3,3X3 + 0,6X4 + 0,999X5. With the description of Z < 1,8 the company categorized into unhealthy/will be bankrupt, the value Z 1,8 < 2,99 the company is considered to be in the uncertain/grey area and the value of Z > 2,99 then the company is in a very healthy. In general, the results of these studies indicate that the four automtive components companies namely PT Astra Otoparts year 2011 value of Z = 14,67 year 2012 value of Z = 10,88 year 2013 value of Z = 13,90 year 2014 value of Z = 10,54 year 2015 value of Z = 4,94, PT Gajah Tunggal year 2011 value of Z = 5,72 year 2012 value of Z = 4,75 year 2013 value of Z = 3,10 year 2014 value of Z = 2,79 year 2015 value of Z = 1,58 and the average value of 2011-2015 periode Z = 3,59, PT Goodyear Indonesia year 2011 value of Z = 2,07 year 2012 value of Z = 2,44 year 2013 value of Z = 2,57 year 2014 value of Z = 2,02 year 2015 value of Z = 2,76, PT Indomobil Sukses Internasional year 2011 value of Z = 6,19 year 2012 value of Z = 3,99 year 2013 value of Z = 3,17 year 2014 value of Z = 2,59 year 2015 value of Z = 1,74. The average value 2011-2015 period showed 3 companies are in very healthy state and 1 company is in the uncertain/grey area. Keywords: Financial Ratio Analysis, Analysis of bankruptcy, Altman Z-Score Analysis, Automotive Components Company, Go Public.

Determining Pure Premium Rates for Hail Insurance on Kansas Wheat

1960 ◽  
Vol 15 (4) ◽  
pp. 559
Author(s):  
Max Everett Fessler
Keyword(s):  
Pure Premium ◽  
Premium Rates
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