scholarly journals Application of C4.5 Algorithm for Late Payment Classification of Insurance Premiums

2021 ◽  
Vol 9 (2) ◽  
pp. 100-113
Author(s):  
Jefry Antonius Karlia ◽  
Wawan Nurmansyah
Keyword(s):  
Insurance Companies ◽  
Insurance Company ◽  
Test Results ◽  
Customer Data ◽  
Insurance Premiums ◽  
Premium Payment ◽  
C4.5 Algorithm ◽  
The Status ◽  
Number Of Customers

The problem that often arises in insurance companies is the number of customers who do not smoothly pay premiums. The procedure that applies to the insurance during the grace period is 30 days. The insured customer must follow the premium payment procedure, if the customer does not pay the premium, the insurance policy will be canceled, this is part of the company's loss. An insurance company has a lot of data and this data can be processed to produce information on how to find out potential customer delays from a pattern formed using the C4.5 method. This research was conducted by applying the C4.5 algorithm using insurance customer data. The results of this study are a classification system for late payment of insurance premiums that can classify insurance customer premium payment status as a consideration for accepting insurance customers. The system test results show that the system can classify the status of insurance customer premium payments with a classification accuracy of 88%. Keywords: Algorithm C 4.5, Insurance, Classification, Premium

scholarly journals FEATURES OF THE FORMATION AND VALUATION OF INSURANCE RESERVES

2021 ◽  
Author(s):  
Maxim Kompaniets ◽  
Inna Kysilyova
Keyword(s):  
Insurance Companies ◽  
Insurance Company ◽  
Strategic Decisions ◽  
Method Of Calculation ◽  
Loss Reserve ◽  
Management Efficiency ◽  
The Status ◽  
Conducting Research ◽  
Economic Nature ◽  
Lower Limits

The purpose of the paper is research of practice of making insurance reserves of the insurance companies in Ukraine and summarizes the ways of improvement of methods for their calculation with the purpose of increasing management efficiency of an organization. The article addresses the characteristics and economic nature of certain types of technical reserves of insurance organizations in particular the unencumbered premiums reserve, the loss reserve and the catastrophe reserve, and the characteristics of their formation. Major methods for calculating the reserve of unencumbered premiums reviewed and recommended adjustment to method 1/36 , and use of the reserve calculation method of unencumbered premiums, which takes into account inflation ratio. The method of calculation and formation of the loss reserve is considered as well as the characteristics of the reserve for past but undeclared losses and reserves for asserted but unresolved losses. The system of indicators of sufficiency of insurance reserves of insurance organizations was analyzed; the calculation formulae and recommended values are given. Insurance reserves sufficiency ratios refers to the status of insurance reserves and determine the adequacy of insurance reserves to the risks taken into insurance. Sufficiency ratio (based on premiums) and sufficiency ratio (based on payments) determine, respectively, the upper and lower limits of insurance reserves. For conducting research and substantiation of relevant conclusions, the indicators of dynamics and structure of insurance reserves of insurance company JSC IC “INGO” are analyzed. Sufficiency ratios for insurance reserves of JSC IC “INGO” are also calculated and Evaluation of the company’s insurance reserves has been performed. The results of the study can be applied by the heads of the financial divisions of insurance companies for the development of tactical and strategic decisions that allows to yield optimal condition of insurance reserves and their reliable valuation of insurance company and to perform the quick analysis of the state of insurance reserves of insurance company.

scholarly journals ANALYSIS OF COMPETITIVE POSITIONS OF INSURANCE COMPANIES IN THE NON-LIFE INSURANCE MARKET IN UKRAINE

2019 ◽  
pp. 88-94
Author(s):  
O. Pakhnenko ◽  
O. Zhuravka ◽  
V. Podhorna ◽  
A. Sukhomlyn
Keyword(s):  
Market Share ◽  
Life Insurance ◽  
Motor Vehicle ◽  
Market Concentration ◽  
Insurance Market ◽  
Insurance Companies ◽  
Insurance Company ◽  
Insurance Premiums ◽  
Property Insurance ◽  
Financial Condition

The paper explores the practical aspects of forming a competitive environment in the non-life insurance market of Ukraine and analyzes the competitiveness and financial performance of leading insurance companies. Based on the analysis of non-life insurance market concentration indicators, the authors concluded that there is no clear leader in this market, the level of market concentration is negligible. Based on the analysis of non-life insurance market leaders by volume of gross insurance premiums in the whole market and by main types of non-life insurance (CASCO, motor vehicle liability insurance, property insurance, fire and catastrophe risk insurance, CARGO, health insurance) the authors found that the leadership of insurance companies in the market does not mean their leadership in all types of non-life insurance; some insurance companies specialize in certain types of insurance and not being leaders in the insurance market at all occupy leading positions in certain segments of non-life insurance market. In order to provide a general assessment of the competitiveness of individual insurance companies in the non-life insurance market, the following indicators were selected: the volume of gross insurance premiums, gross insurance payments, insurance reserves and the amount of equity. In order to assess the size of market share of an individual insurance company in a more objective way, it is suggested to calculate the average share of the insurance company. The calculations made it possible to identify the leaders of the non-life insurance market in 2018 and to explore the dynamics of changes in their competitive position during 2016-2018. For the three insurance companies that have been identified as the leaders of the Ukrainian market non-life insurance in 2018 (“UNIKA”, “AXA Insurance” and “PZU Ukraine”), the authors analyzed the main indicators of their financial condition, namely the profitability of insurance services, profitability of sales, return on assets, return on equity, overall liquidity, absolute liquidity and autonomy. It was found that all the analyzed insurance companies are profitable, however, among the three leading Ukrainian insurance companies, the most effective in 2018 was the insurance company “PZU Ukraine” and the least profitable – “UNIKA”. Keywords: competitiveness, insurance company, market concentration, market share, competition.

scholarly journals KLASIFIKASI TINGKAT KELANCARAN NASABAH DALAM MEMBAYAR PREMI DENGAN MENGGUNAKAN METODE K-NEAREST NEIGHBOR DAN ANALISIS DISKRIMINAN FISHER (Studi kasus: Data Nasabah PT. Prudential Life Samarinda Tahun 2019)

2020 ◽  
Vol 8 (2) ◽  
pp. 88
Author(s):  
Amanah Saeroni ◽  
Memi Nor Hayati ◽  
Rito Goejantoro
Keyword(s):  
Discriminant Analysis ◽  
Nearest Neighbor ◽  
K Nearest Neighbor ◽  
Fisher Discriminant Analysis ◽  
Customer Data ◽  
Independent Variables ◽  
Premium Payment ◽  
Multivariate Technique ◽  
Fisher Discriminant

Classification is a technique to form a model of data that is already known to its classification group. The model that was formed will be used to classify new objects. The K-Nearest Neighbor (K-NN) algorithm is a method for classifying new objects based on their K nearest neighbor. Fisher discriminant analysis is a multivariate technique for separating objects in different groups to form a discriminant function for allocate new objects in groups. This research has a goal to determine the results of classifying customer premium payment status using the K-NN method and Fisher discriminant analysis and comparing the accuracy of the K-NN method classification and Fisher discriminant analysis on the insurance customer premium payment status. The data used is the insurance customer data of PT. Prudential Life Samarinda in 2019 with current premium payment status or non-current premium payment status and four independent variables are age, duration of premium payment, income and premium payment amount. The results of the comparative measurement of accuracy from the two analyzes show that the K-NN method has a higher level of accuracy than Fisher discriminant analysis for the classification of insurance customers premium payment status. The results of misclassification using the APER (Apparent Error Rate) in K-NN method is 15% while in Fisher discriminant analysis is 30%.

scholarly journals “MAQASID SHARIA INDEX”: ARAH BARU KINERJA KEUANGAN PERUSAHAAN ASURANSI SYARIAH DI INDONESIA

2019 ◽  
Vol 1 (1) ◽  
pp. 60-76
Author(s):  
Nugroho Heri Pramono
Keyword(s):  
Financial Performance ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Social Reporting ◽  
Insurance Companies ◽  
Insurance Company ◽  
Test Results ◽  
Islamic Insurance ◽  
Positive Effect ◽  
Research Show

This reseacrh is aimed to analyze the influence of Islamic social reporting index and sharia compliance disclousure to financial performance of Islamic insurance company in Indonesia which is proxied by the value of maqasid sharia. This research was conducted from 2012 to 2014. The sample were used in this reseacrh 34 observations obtained from 12 Islamic insurance company in Indonesia for three years from 2012 to 2014. The sampling technique was used simple random sampling. The results of simultaneous research show that together Islamic social reporting index and sharia compliance disclousure have a significant positive effect to the financial performance of sharia insurance companies proxied with maqasid syariah index. However, based on the partial test results of Islamic reporting index variables and sharia compliance disclosure does not affect the financial performance of sharia insurance companies proxied with the value of maqasid syariah index.

scholarly journals Measuring the effectiveness of intermediary loyalty programmes in the motor insurance industry: loyal versus non-loyal customers

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Manuel Leiria ◽  
Efigénio Rebelo ◽  
Nelson deMatos
Keyword(s):  
Insurance Industry ◽  
Binary Logistic Regression ◽  
Data Access ◽  
Insurance Companies ◽  
Insurance Company ◽  
Content Type ◽  
Customer Data ◽  
Insurance Policies ◽  
Motor Insurance ◽  
Value Propositions

PurposeThe insurance industry has not been able to effectively retain its customers and struggles to establish and maintain long-lasting relationships with them. The purpose of this paper is thus to identify the main factors that explain the cancellation of motor insurance policies by individual customers, considering the influence of intermediaries on their decisions.Design/methodology/approachThe data used in this research is based on a sample of 3,500 insurance policies that lapsed during the period of analysis between January and July 2017, against another sample of 3,500 policies that did not lapse, from a major insurance company in Portugal. Binary logistic regression was used for data analysis, using IBM SPSS software.FindingsAggressive tactics by insurance companies for customer acquisition may induce the cancellation of insurance policies. More valuable customers, the policies with higher premiums and recent claims, as well as the ancillary intermediaries and agents, are determinants of insurance cancellation. Conversely, the payment of policies by direct debit and without instalments reduces the probability of cancellations.Research limitations/implicationsThe main limitation of this study is the restriction on data access. Insurance companies are significantly resistant to sharing their customer data – including with academic researchers – even in an anonymised form.Practical implicationsThe paper highlights internal and external practices of insurance companies that should be reformulated to significantly improve their performance regarding product cancellation, related to customer information management, mistrust behaviours related to stakeholders and new value propositions that deepen the relationships with intermediaries.Originality/valueThis research developed a framework with which to identify the factors that are mainly associated with motor insurance cancellation and to predict its likelihood.

Magnetic Resonance Imaging Utilization in Iran

2021 ◽  
Author(s):  
Sajad Ramandi ◽  
Mahya Abbasi ◽  
Ali Mohammad Mosadeghrad
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Private Insurance ◽  
High Rate ◽  
Insurance Companies ◽  
Insurance Company ◽  
Resonance Imaging ◽  
Statistical Population ◽  
Study Results ◽  
The Status

Abstract Background: The increased use of diagnostic and therapeutic equipment and services increases the costs of the health system and insurance organizations. Evaluating the status of utilizing these services can provide a clear picture of the demand rate, responding process and methods of providing the relevant services. This study aimed to examine the status of using magnetic resonance imaging (MRI) services among the insured people by one of the insurance companies.Methods: This research was a descriptive and cross-sectional study. The studied statistical population included all insured persons covered by a private insurance company that had used the MRI services provided in hospitals and other diagnostic and treatment centers in 2018-2019. The data were analyzed using STATA and GIS statistical software.Results: In one contractual year, 22,738,215 medical expenses records have been filed in the entire country, out of which, 119,761 records (0.5% of all cases) were related to MRI services. The shares of the basic (main) insurer and supplemental insurance related to this service of the total MRI costs were estimated as 52,946,159,376 Rials (1,259,860.6077 USD) and 231,303,021,838 Rials (5,503,884.87252 USD), respectively. In the study, 102,024 people have used MRI at least once a year. The average cost of using MRI services at each time in the country was 2,373,470 Rials (56.47702 USD). The average number of referrals in the whole country was 0.07 times. The highest frequency of referrals was in Lorestan and Qom provinces, while Kerman and Sistan and Baluchestan provinces had the lowest frequency of referrals. The overall rate of utilization of MRI services in the country was estimated to be 6%.Conclusion: In general, the study results suggested a high rate of using MRI services in Iran, which can be due to the 100% coverage of costs by insurance companies and the increased access to health diagnostic and treatment services in the country.

scholarly journals Clustering Customer Data Using Fuzzy C-Means Algorithm

2021 ◽  
Vol 9 (1) ◽  
pp. 1-14
Author(s):  
Nurfaizah Nurfaizah ◽  
Fathuzaen Fathuzaen
Keyword(s):  
Economic Growth ◽  
Partition Coefficient ◽  
Economic Activity ◽  
Service Industry ◽  
Insurance Companies ◽  
Insurance Company ◽  
Validity Index ◽  
Customer Data ◽  
Fuzzy C Means ◽  
Fuzzy C Means Algorithm

The pattern of the service industry is influenced mostly by economic growth. When economic growth rises, the economic activity will also grow as in the case of insurance activities. One of the assets owned by an insurance company is the customer, hence the existence of a loyal or potential customer should be maintained by the insurance company. This study focuses on clustering or grouping the existing customer data in insurance companies using the Fuzzy C-Means (FCM) algorithm. This study uses data from the company for analysis and the results can be used as a basis for insurance companies in making decisions, especially those related to further insurance marketing to customers who have participated in insurance or who are still actively registered in payment insurance. Fuzzy C-Means can be used for clustering the customer datasets. It obtained 3 clustering results using Partition Coefficient (PC) in determining the validity index and the centers value was ranged from 0.5 to 1.0.  

scholarly journals A Study on Customer’s Preference for Personal Vehicle Insurance Provided by Different Insurance Companies in Bengaluru

2020 ◽  
pp. 69-79
Author(s):  
Swati Basu Ghose ◽  
Anima Akanchha
Keyword(s):  
Value Added ◽  
Third Party ◽  
Insurance Companies ◽  
Primary Data ◽  
Insurance Company ◽  
Insurance Choice ◽  
Private And Public ◽  
The Cost ◽  
Number Of Customers ◽  
Annual Premium

The primary purpose of vehicle insurance is to cover the vehicle against damage, personal injury, and third-party liability. In addition to this, some insurance companies also provide value-added services such as roadside assistance and other services in return of the amount called as premium which attracts a large number of customers. However, our study shows that vehicle owners give maximum importance to the cost of insurance in terms of the annual premium. Primary data has been collected through questionnaire and analysed to ascertain about the factors responsible for taking out vehicle insurance, choice between private and public sector insurance companies, preferred insurance companies among the major players in the field, factors that play a role in the customers’ choice of a particular insurance company, customers’ opinion about the affordability of the premium to be paid, customers’ satisfaction with their chosen company, whether customers consider fast and efficient service as a deciding factor, and whether the brand value of the company plays a role in the customers’ choice.

scholarly journals Penerapan Data Mining untuk Memprediksi Minat Nasabah Terhadap Produk Asuransi Meninggal Dunia dengan Metode Naïve Bayes (Studi Kasus : PT. BNI Life Insurance)

Respati ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. 103
Author(s):  
Ari Hidayatullah, Ena Mudiawati, Muhammad Syafrullah
Keyword(s):  
Data Mining ◽  
Life Insurance ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Insurance Companies ◽  
Insurance Company ◽  
Accuracy Rate ◽  
Customer Data ◽  
Bayes Algorithm ◽  
Business Behavior

INTISASIPendapatan untuk perusahaan asuransi ditentukan oleh jumlah premi yang dibayar oleh nasabah. faktor penting nasabah berupa premi, premi ditentukan dalam persentase atau tarif tertentu. Pada perusahaan asuransi pasti memiliki jumlah data, dan data tersebut sangat penting bagi perusahaan untuk mengetahui kriteria nasabah yang berminat pada asurnsi yang dipasarkan. Dengan adanya informasi dari  data  nasabah  yang  ada,  perusahaan  asuransi  dapat  mengambil  suatu keputusan dalam menerapkan stragi perusahaan diantarnya yaitu menjual produk- produk promo untuk meninggatkan pendapatan perusahaan. Data mining merupakan suatu teknologi yang dapat membantu perusahaan dalam menemukan suatu yang sangat penting dari sekumpulan data. Data mining dapat membentu sautu pola atau membuat suatu sifat perilaku bisnisa yang berguna untuk pengambilan keputusan. Dengan menggunakan metode algoritma Naive Bayes diharapkan bisa membantu perusahaan dalam pengelolaan data nasabah dengan cara mengklasifikasi data nasabah untuk memprediksi minat nasabah dengan tingkat akurasi melebihi 80% dalam memilih produk asuransi meninggal dunia. Kata Kunci: asuransi, baïve bayes, prediksi, data mining.   ABSTRACTIncome for insurance companies is determined by the amount of premium paid by the customer. Important factors for customers in the form of premiums, premiums are determined in certain percentages or rates. The insurance company certainly has the amount of data, and the data is very important for companies to know the criteria of customers who are interested in the insurance marketed. With the information from existing customer data, the insurance company can make a decision in implementing the company's strategy, which is to sell promo products to increase company revenue. Data mining is a technology that can help companies find a very important set of data. Data mining can form a pattern or create a nature of business behavior that is useful for decision making. By using the Naive Bayes algorithm method, it is expected to be able to assist companies in managing customer data by classifying customer data to predict customer interest with an accuracy rate exceeding 80% in choosing a death insurance product. Keywords: insurance, baïve bayes, predictions, data mining..

scholarly journals Risks of the insurance company: classification and methods of analysis

2018 ◽  
Keyword(s):  
Financial Risk ◽  
Business Processes ◽  
Risk Identification ◽  
Insurance Companies ◽  
Modern Concept ◽  
Insurance Company ◽  
Strategic Risk ◽  
Insurance Contracts ◽  
Definition Of

The purpose of the article was to develop a risk classification of the insurance company, identify the shortcomings and advantages of existing methods of risk analysis and measures to reduce the risks of insurance companies. Group presented risk assessment methods is, according to the author, rather conditional, because risk identification can be carried out using techniques and technologies analysis and evaluation of all types of risks, and vice versa. An analysis of the studies of Ukrainian and foreign authors showed that there are a large number of classification features and types of risks and the absence of a single universally accepted classification of risks, which in our opinion, the author is associated with the unsystematic conceptual apparatus of the theory of risks and a wide variety of their manifestations in the practical activities of enterprises. Therefore, the definition of "risk" is clarified and it is emphasized that the modern concept of management of operating activities in an insurance company relies on the methodology of its operating business processes: the conclusion and maintenance of insurance contracts, underwriting, reinsurance and settlement of losses. The classification of risks of the insurance company and the logical connections of groups of general and specific risks is proposed, combining them into 4 types: risk of accidental risk (accidental and dangerous events), financial risk, operational risk - probability of occurrence of losses due to incorrect work of personnel, internal systems or under the influence of external factors and strategic risk. Considered is the estimation of the efficiency of the insurance company with the use of EVA and RAROC indicators, which allow to assess the financial position of the company and its effective management, or its subdivision. Considered is the application of stress testing and individual measures to reduce financial risk for effective insurance of risks of an insurance company.

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