Ordnungspolitische Weichenstellungen für die anstehende Reform der Riester-Rente

2020 ◽  
Vol 69 (3) ◽  
pp. 239-249
Author(s):  
Axel Kleinlein

Abstract The Riester pensions today face two main problems: First, life insurance industry in Germany faces the problem of inadequate solvency. Therefore, there is a need that we take the Riester pension not as a sole part of the life insurance sector and open it to the whole sector of financial services. Second, the previous regulation of the Riester pension is causing problems. Particularly the guarantee forces mandatory retirement with a life insurance company and the requirement of capital preservation. Therefore we have to review these two guarantee aspects. It is also important to limit costs and to simplify the funding system. The concept of the “Basisdepot-Vorsorge” solves these problems while it is based on promoting precisely those who want to save up for their retirement during their active career, no matter what kind of financial service is included in the accumulation or decumulation phase. To include all different financial service providers creates the needed economical competition to ensure better products for the Riester-Rente.

2016 ◽  
Vol 4 (10(SE)) ◽  
pp. 30-36
Author(s):  
N.Senthil Kumar ◽  
K. Selvamani

The first insurer of life was the marine insurance underwriters who started issuing life insurance policies on the life of master and crew of the ship, and the merchants. The first insurance policy was issued on 18th June 1583,on the life of WILLIAM GIBBONS for the period of 12 months. The oriental life insurance company is the first insurance companies in India which is started on 1818 by Europeans at Kolkata. The Indian Life Assurance Companies Act, 1912 was the first statutory measure to regulate life business. In 1928, the Indian Insurance Companies Act was enacted to enable the Government to collect statistical information about both life and non-life business transacted in India by Indian and foreign insurers including provident insurance societies. In 1938, with a view to protecting the interest of the Insurance public, the earlier legislation was consolidated and amended by the Insurance Act, 1938 with comprehensive provisions for effective control over the activities of insurers. In 1956 the life insurance companies was nationalized. The LIC absorbed 154 Indian, 16 non-Indian insurers as also 75 provident societies—245 Indian and foreign insurers in all. The LIC had monopoly till the late 90s when the Insurance sector was reopened to the private sector.


2020 ◽  
Vol 21 (3) ◽  
pp. 681-715 ◽  
Author(s):  
MATTHEW LOWENSTEIN

This article traces the history of the first Chinese life insurance company: the China United Assurance Society. China United was founded in Shanghai in 1912 as a purely Chinese-owned enterprise and became the first Chinese life insurer to survive past its eighth year. By 1935, it boasted insurance in force of over 20 million yuan. In adapting life insurance to Republican China, China United had to contend with a number of extraordinary challenges. It had to train a corps of Chinese technical experts in a country without a single accredited actuary. It had to cultivate demand for a product that was poorly understood and often distrusted. At the same time, the Society was forced to find a way to manage a nationwide sales network that could market insurance products to a country that hitherto had little knowledge of life insurance. In doing so, it was threatened by interethnic strife sparked by racist practices of the foreign manager. Finally, China United had to overcome increasingly fierce competition, high lapse rates, and excess mortality that combined to drive underwriting profits negative. The Society was able to survive as a going concern only through its investing prowess in Chinese capital markets. Using previously unmined sources from the Shanghai Municipal Archives, this article charts China United’s turbulent process of indigenization, and explores its lasting legacies in the contemporary Chinese life insurance industry.


Author(s):  
Marc Maier ◽  
Hayley Carlotto ◽  
Freddie Sanchez ◽  
Sherriff Balogun ◽  
Sears Merritt

Life insurance provides trillions of dollars of financial security for hundreds of millions of individuals and families worldwide. Life insurance companies must accurately assess individual-level mortality risk to simultaneously maintain financial strength and price their products competitively. The traditional underwriting process used to assess this risk is based on manually examining an applicant’s health, behavioral, and financial profile. The existence of large historical data sets provides an unprecedented opportunity for artificial intelligence and machine learning to transform underwriting in the life insurance industry. We present an overview of how a rich application data set and survival modeling were combined to develop a life score that has been deployed in an algorithmic underwriting system at MassMutual, an American mutual life insurance company serving millions of clients. Through a novel evaluation framework, we show that the life score outperforms traditional underwriting by 6% on the basis of claims. We describe how engagement with actuaries, medical doctors, underwriters, and reinsurers was paramount to building an algorithmic underwriting system with a predictive model at its core. Finally, we provide details of the deployed system and highlight its value, which includes saving millions of dollars in operational efficiency while driving the decisions behind tens of billions of dollars of benefits.


2017 ◽  
Vol 5 (1) ◽  
pp. 012
Author(s):  
Aam S. Rusydiana ◽  
Taufiq Nugroho

This study aims to measure the level of efficiency of the life insurance industry in Indonesia. The calculation of the efficiency level in this study is relative, not absolute. The approach used is Data Envelopment Analysis (DEA). There are 8 research objects: Prudential, BNI Life, PaninDai-IchiLife, Asuransi Jiwasraya and Life Insurance Adisaranan Wanaartha, Takaful Takaful Insurance, Amanahjiwa Giri sharia insurance and Al-Amin sharia life insurance. This study consists of three input variables (cost of Commissive (X1), Operational Cost (X2), Total Equity (X3) and 2 output variables (Premium) (Y1) and Investment Revenue (Y2)). The results explain that there are 15 perfectly efficient DMUs (100%). And an inefficient of 24 DMU, consisting of 7 DMU conditions IRS and 17 DMU with DRS conditions. Of all the DMU observed, Prudential insurance is a life insurance company that is able to maintain its gradual efficiency level from 2013 to 2016 when compared to other life insurance in this observation. In general, the main factor inefficiency of life insurance industry in Indonesia (in observation) from 2012 to 2016 is from the output side. To be more efficient then life insurance companies should increase the value of premiums by 91% and investment income of 8%.


Author(s):  
Joy Chakraborty ◽  
Partha Pratim Sengupta

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.


2018 ◽  
Vol 7 (4.5) ◽  
pp. 159
Author(s):  
Vaibhav A. Hiwase ◽  
Dr. Avinash J Agrawa

The growth of life insurance has been mainly depending on the risk of insured people. These risks are unevenly distributed among the people which can be captured from different characteristics and lifestyle. These unknown distribution needs to be analyzed from        historical data and use for underwriting and policy-making in life insurance industry. Traditionally risk is calculated from selected     features known as risk factors but today it becomes important to know these risk factors in high dimensional feature space. Clustering in high dimensional feature is a challenging task mainly because of the curse of dimensionality and noisy features. Hence the use of data mining and machine learning techniques should experiment to see some interesting pattern and behaviour. This will help life insurance company to protect from financial loss to the insured person and company as well. This paper focuses on analyzing hidden correlation among features and use it for risk calculation of an individual customer.  


2021 ◽  
pp. 097226292110109
Author(s):  
Amarpreet Singh Ghura ◽  
Abhishek

IndiaFirst Life Insurance (IFLI) became the 23rd entrant in India’s life insurance industry by launching its operations in November 2009 (IndiaFirst Life Insurance, 2015). IFLI went on to break-even within 6 years of its inception by declaring maiden profits in FY 2015–2016 (IndiaFirst Life Insurance, 2015). The company stated its vision as—‘To become a Life Insurance and Pension business leader that provides significant value to all its stakeholders enabling a true customer delight’ (IndiaFirst Life Insurance, 2015). In order to implement its vision, IFLI worked its human resource policies and processes around the ‘Employees First’ approach (IndiaFirst Life Insurance, 2015). These processes had helped IFLI to become the fastest-growing company in the life insurance sector, and it was ranked 12th amongst the private insurers in terms of market ranking in individual annual premium equivalent for FY 2016–2017 ( Times of India, 2017). The company aimed to become a top 10 life insurance provider in the next few years in India in terms of retail premium business ( Times of India, 2017).


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