scholarly journals RESPONSIVENESS OF MOTOR INSURANCE BUSINESS TO INSURANCE SECTOR DEVELOPMENT, 2005-2016. ECONOMETRIC EVIDENCE FROM NIGERIA

2019 ◽  
Vol 3 (9) ◽  
Author(s):  
EZEMA, Clifford Anene ◽  
ANI, Afamefuna Jonah
Keyword(s):  
Insurance Sector ◽  
Motor Insurance ◽  
Econometric Evidence ◽  
Insurance Business

scholarly journals Premium Rates in the German Motor Insurance Business

1963 ◽  
Vol 3 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Johannes Mehring
Keyword(s):  
Price Competition ◽  
Traffic Accidents ◽  
Transitional Period ◽  
Insurance Company ◽  
Free Competition ◽  
The Third ◽  
Third Phase ◽  
Motor Insurance ◽  
Insurance Business ◽  
Set Up

In his report to the XVIth International Congress of Actuaries in Brussels [5] in 1960 the author has given a survey of the German Motor Insurance Business and in this it was mentioned that a change might be expected from the flat-tariff prescribed by law into individual tariffs for every insurance company. The Federal Ministry of Economics decided this question at the end of 1959 by signing the price regulation PR 15/59 [I] The federal price-fixing treaty had thus come to an end after several decades.Three steps are planned for the transitional period: For the years i960 and 1961 the flat-tariff remained in existence; free competition was introduced by providing for a return of premiums from technical surplus. At the beginning of 1962 the second phase of liberalisation began: Between 1962–1965 each insurance company has to compute its own tariff which has to be approved by the Federal Ministry of Economics. No deviations are permitted from the approved tariffs. Nobody can tell yet what the third phase in 1966 will bring.At the time the price-fixing agreements were cancelled it was unanimously agreed that proper competition should be maintained and that ruinous price competition which would harm the interests of victims of traffic accidents must be avoided [4]. Trusts or tariff rings were not taken into consideration. However, some market regulations were set up by co-operation between the different parties.The benefits (insurance conditions) are the same for all insurance enterprises. Also there are only few alternatives in the tariff conditions.

scholarly journals Innovatizing the Insurance Business in the Development of Digital Economy

2021 ◽  
Vol 7 (522) ◽  
pp. 62-69
Author(s):  
O. O. Sosnovska ◽  
Keyword(s):  
Business Processes ◽  
Swot Analysis ◽  
Insurance Industry ◽  
Global Scale ◽  
Digital Economy ◽  
Insurance Companies ◽  
Insurance Sector ◽  
Insurance Business ◽  
Health Insurance Industry ◽  
The Individual

The article defines the current trends of innovatizing the insurance business in the digital economy. The stages of development of modern insurance technologies (InsurTech), which are innovative products in the insurance sector of financial infrastructure, are provided. The instruments of digitalization of business processes for sale of insurance products, settlement of insurance claims, bookkeeping and tax accounting, risk underwriting, document flow are presented. The dynamics of global investments in technological innovations of insurance companies on a global scale have been specified. The volume of global investments and concluded agreements in InsurTech sector by insurance sectors is analyzed and it is proved that 2020 is a period of awareness of the importance and role of digital technologies implementation in the insurance industry, recognition of the value of the digitalization vector of insurance business and global investments in InsurTech development with the highest recorded values. It is identified that the leader in attracting investments in the processes of innovatizing is the property insurance industry (P&C), which has compiled 53% of the total financing and 63% of the concluded agreements. The individual health insurance industry (L&H) ranks second in terms of indicators, maintaining overall investment attractiveness, high amounts of financing and the introduction of insurance technologies. The economic, technological, organizational management, and legal factors that stimulate or inhibit the innovative activity of insurance companies in Ukraine are systematized. Based on the generalization of problems and weaknesses that are relevant and impede the desired pace of innovatizing the insurance business in the digital economy, a SWOT analysis matrix of the feasibility of InsurTech implementation is proposed. It is determined that the introduction of innovations and the development of insurance on the basis of digitalization are currently a catalyst for the strategic development of the insurance business, improving the quality of insurance products and successful activities in an increasingly customer-oriented financial sector.

Impact of Foreign Direct Investment in India on Insurance Industry

2018 ◽  
Vol 6 (7) ◽  
pp. 65 ◽  
Author(s):  
Krunal Soni
Keyword(s):  
Foreign Direct Investment ◽  
Life Insurance ◽  
Direct Investment ◽  
Capital Investment ◽  
Insurance Industry ◽  
Dynamic Environment ◽  
Insurance Sector ◽  
Private Participation ◽  
Overall Performance ◽  
Insurance Business

The study concluded that increase in foreign direct investment (F.D.I.) is optimistic move for the future of Indian Life Insurance Sector, since this sector need huge amount of capital investment which can be done effectively only through increase in FDI and it enhance overall performance of insurance sector. Parliament has passed Insurance Laws (Amendment) Bill, 2015. It was first passed in LokSabha on 4 March 2015 and later in RajyaSabha on 12 March 2015, which will become an Act when the President signs it. The bill aims to bring improvements in the existing laws relating to insurance business in India. The bill also seeks to remove archaic provisions in previous laws and incorporate modern day practices of insurance business that are emerging in a changing dynamic environment, which also includes private participation. The insurance sector in India has a great potential even during the downtrend and FDI flow is expected to rise in the mere future.

Multinational Enterprises and Institutional Regulation in the Life-Insurance Market in Spain, 1880–1935

2008 ◽  
Vol 82 (1) ◽  
pp. 87-114 ◽  
Author(s):  
Jerònia Pons Pons
Keyword(s):  
World War I ◽  
International Business ◽  
Life Insurance ◽  
Multinational Enterprises ◽  
External Factors ◽  
Insurance Companies ◽  
World War ◽  
Regulatory Requirements ◽  
Insurance Sector ◽  
Insurance Business

The number of multinationals in the life-insurance sector expanded during the first era of globalization. Many of these firms gravitated to Spain, attracted by factors such as the country's small number of national companies and minimal regulatory requirements. Toward the end of the nineteenth century, however, the Spanish government began to impose more institutional regulations, increasing the guarantees, deposits, and reserves required of insurance companies. In response, American and British multinationals began to leave the Spanish market, propelled both by the new requirements and by a series of external factors that obliged American companies to reduce their international business. Finally, the economic disruption that accompanied the outbreak of World War I convinced American and British multinationals to withdraw from the Spanish insurance business.

scholarly journals Macro-Economic Determinants of Life Insurance Business – Empirical Evidence during 2000-01 to 2015-16

2019 ◽  
Vol 9 (2) ◽  
pp. 4599-4606
Keyword(s):  
Economic Growth ◽  
Life Insurance ◽  
Banking Sector ◽  
Time Series Data ◽  
Positive Impact ◽  
Insurance Industry ◽  
Series Data ◽  
Insurance Sector ◽  
Insurance Business ◽  
Enrolment Ratio

There is a strong link between an institutional framework of insurance sector and sustainable economic growth. Insurance business has a positive impact on economic development and vice versa. As a developed insurance market stimulates economic growth of a country, the level of its economic growth affects insurance business development in return. In India, regulatory changes commenced since midnineties for opening up of insurance markets to private and foreign insurers. After more than one and half decade execution of insurance sector reforms, Indian life insurance business have been witnessed the better growth. In this juncture, the present study focuses on an examination of the role of a macroeconomic environment in the development of life insurance industry in India by using time series data with regression analysis. The study finds that the savings to GDP ratio, banking sector development, expenditure on social security to GDP, gross enrolment ratio and life expectancy are most significant and positive factors in driving the life insurance business during the study period..

scholarly journals AN EFFECTIVE MACHINE LEARNING MODEL FOR CUSTOMER ATTRITION PREDICTIONIN MOTOR INSURANCE USING GWO-KELM ALGORITHM

2021 ◽  
Vol 9 (1) ◽  
pp. 91-105
Author(s):  
Deepthi Das, Raju Ramakrishna Gondkar
Keyword(s):  
Machine Learning ◽  
Missing Values ◽  
Insurance Industry ◽  
Expectation Maximization Algorithm ◽  
Insurance Sector ◽  
Industrial Sectors ◽  
Machine Learning Model ◽  
Motor Insurance ◽  
Bayes Algorithm ◽  
Customer Attrition

The prediction of customers' churn is a challenging task in different industrial sectors, in which the motor insurance industry is one of the well-known industries. Due to the incessant upgradation done in the insurance policies, the retention process of customers plays a significant role for the concern. The main objective of this study is to predict the behaviors of the customers and to classify the churners and non-churners at an earlier stage.  The Motor Insurance sector dataset consists of 20,000 records with 37 attributes collected from the machine learning industry. The missing values of the records are analyzed and explored via Expectation Maximization algorithm that categorizes the collected data based on the policy renewals. Then, the behavior of the customers are also investigated, so as to ease the construction process training classifiers. With the help of Naive bayes algorithm, the behaviors of the customers on the upgraded policies are examined. Depending on the dependency rate of each variable, a hybrid GWO-KELM algorithm is introduced to classify the churners and non-churners by exploring the optimal feature analysis. Experimental results have proved the efficiency of the hybrid algorithm in terms of 95% prediction accuracy; 97% precision; 91% recall & 94% F-score.

Life Insurance Industry Agent’s Attrition: A Game Changer for Insurance Business

2020 ◽  
pp. 097215091986145
Author(s):  
Neha Chhabra Roy ◽  
N. G. Roy
Keyword(s):  
Life Insurance ◽  
Financial Risk ◽  
Insurance Industry ◽  
Extensive Literature ◽  
Insurance Sector ◽  
Life Insurance Industry ◽  
Central Argument ◽  
Recent Trends ◽  
Insurance Business ◽  
Game Changer

Insurance industry of any country acts as the backbone of its financial risk management system. Although two-thirds of the insurance business in India is carried out through individual agents, recent trends show significant attrition among them. The central argument in this article revolves around identifying the drivers responsible for individual agent’s attrition in India. The methodology used for this factor identification was based on extensive literature review and further validation through a primary survey of the stakeholders in the insurance sector. A conceptual model is also proposed for mitigation of agent’s attrition.

Some Statistical Problems arising from the Transaction of Motor Insurance Business

1964 ◽  
Vol 17 (04) ◽  
pp. 279-313
Author(s):  
R. E. Beard
Keyword(s):  
Life Insurance ◽  
Statistical Models ◽  
Insurance Industry ◽  
Actual Situation ◽  
Reasonable Time ◽  
Numerical Examples ◽  
Motor Insurance ◽  
Insurance Business ◽  
Risk Processes ◽  
The Relationship

When the word statistics is used in connexion with non-life insurance the first reaction of most of those concerned with the day-today requirements of the business is to think in terms of the relationship between premiums and claims. In my talk tonight I shall not be concerned with this aspect but will be concerned with the structure of the risk processes underlying the business. In order to try to bring out some of the essential characteristics I have used the minimum of mathematics, using numerical examples to illustrate the points. Furthermore, in order to limit my talk to a reasonable time and to make it ‘live’ I have deliberately omitted many of the finer points which arise in practice to which regard must be had in using mathematical or statistical models to describe the actual situation.At rock bottom the insurance industry rests on the operation of laws of chance. A hazard is recognized as being liable to give rise to a potential pecuniary liability, and in no time at all someone is prepared to provide a policy against such liability. In devising the policy, and in assessing the rate of premium to be charged, it is necessary to define the event which must happen before a claim can be admitted under the policy and to be satisfied that the happening of the event is fortuitous as far as the proposer is concerned. In life insurance difficulty seldom arises under either count but in non-life insurance the position is frequently very troublesome.

Sign in / Sign up

Export Citation Format

Share Document