DYNAMIC FINANCIAL MODELS OF LIFE INSURERS

2006

The paper deals with solvency assessment for life insurance business; some methodological issues concerning the solvency of life insurance companies, particularly connected to the investment risk, are suggested. Considerations about the technical equilibrium of an insurance portfolio and the financial regulation lead to a dynamic system involving risk measure and solvency assessment. The formal model is applied to a life annuity cohort in a stochastic context in order to exemplify the potential of the model, especially referred to the need to frame solvency assessment in a dynamic perspective.

SSRN Electronic Journal, 2014

Low interest rates are becoming a threat to the stability of the life insurance industry, especially in countries such as Germany, where products with relatively high guaranteed returns sold in the past still represent a prominent share of the total portfolio. This contribution aims to assess and quantify the effects of the current low interest rate phase on the balance sheet of a representative German life insurer, given the current asset allocation and the outstanding liabilities. To do so, we generate a stochastic term structure of interest rates as well as stock market returns to simulate investment returns of a stylized life insurance business portfolio in a multi-period setting. Based on empirically calibrated parameters, we can observe the evolution of the life insurers' balance sheet over time with a special focus on their solvency situation. To account for different scenarios and in order to check the robustness of our findings, we calibrate different capital market settings and different initial situations of capital endowment. Our results suggest that a prolonged period of low interest rates would markedly affect the solvency situation of life insurers, leading to a relatively high cumulative probability of default, especially for less capitalized companies. In addition, the new reform of the German life insurance regulation has a beneficial effect on the cumulative probability of default, as a direct consequence of the reduction of the payouts to policyholders.

International Journal of Science and Research (IJSR), 2017

Financial analysis is an important tools for insurance companies to enhance the profitability. In developing country, such as Indonesia, the empirical studies of firm-specific and macroeconomic factors are not so exhaustively analyzed. Therefore, the aim of this paper is to analyze the firm-specific factors and macroeconomic determinants of life insurance companies' profitability in Indonesia using panel data during the period 2010 to 2014. The study examines the firm-specifics factors consist of size of company, equity capital, premium growth, risk based capital ratio, leverage ratio and liquidity ratio, while macroeconomic factor is inflation rate. The findings indicate negative and significant influence of premium growth and risk based capital on profitability; and significant positive influence of equity capital, liquidity ratio, leverage ratio and size of company on profitability. Additionally, results reveal that inflation rate is not significantly influence the profitability of life insurance companies. The other finding iscompanies that have good level of total assets, equity capital, leverage ratio and liquidity ratios tend to have good achievement ROA ratio. Companies should be able calculating technical reserves appropriately, construct the optimal portfolio in order to be able to generate maximum profits and streamline expenses operating expenses to maintain the achievement of good profitability.

2009

This paper aims to draw-up an analysis of the life insurance market in Romania. This survey is drawn up for the period 2003-2006 and the data used for this analysis were taken over from the Annual Reports published by the Insurance Supervision Commission. Life insurance market in Romania is a steady growing market as a result of the economic growth and the purchase power but is still far away from the development stage of the European markets.

SSRN Electronic Journal, 2000

This section describes the business of insurance. It is divided into seven subsections: the primary activities and organization of insurance companies (subsection 1.1), the products and services offered by insurance companies (1.2), distribution channels (1.3), competition (1.4), regulation (1.5), taxation (1.6), and risks and risk management (1.7). 1.1 Activities and Organization Insurance provides economic protection from identified risks occurring or discovered within a specified period. Insurance is a unique product in that the ultimate cost is often unknown until long after the coverage period, while the revenue-premium payments by policyholders-are received before or during the coverage period. Insurance contracts are classified as either property and casualty (PC) or life and health (LH) policies: PC insurance-contracts providing protection against (a) damage to or loss of property caused by various perils, such as fire, damage or theft, (b) legal liability resulting from injuries to other persons or damage to their property, (c) losses resulting from various sources of business interruption, or (d) losses due to accident or illness. LH insurance-contracts that pay off in lump sums or annuities upon the insured's death, disability, or retirement. Some insurance policies, primarily health-related policies, have both PC and LH characteristics and can therefore be classified as either PC or LH. Most insurance companies specialize in either PC or LH insurance, but some have significant operations in both segments. In addition, while many insurers underwrite reinsurance policies (insurance sold to insurers), some focus on reinsurance as their core activity. Insurers increasingly offer products and services that involve little or no insurance protection, such as investment products and fee-based services. The industry also includes companies that provide insurance brokerage services (sourcing of insurance contracts on behalf of customers). Reflecting this variation in activities, the Global Industry Classification (GIC) system classifies insurance companies as follows: Life and Health Insurers (40301020)-Companies providing primarily life, disability, indemnity or supplemental health insurance. This category excludes managed health care companies, which are included in the Health Care sector. Examples include MetLife Inc. (MET), Prudential Financial (PRU), AFLAC Inc. (AFL), Lincoln National Corp. (LNC), Unum Group (UNM), and Torchmark Corp. (TMK). Property and Casualty Insurers (40301040)-Companies providing primarily property and casualty insurance. Examples include Berkshire Hathaway Inc. (BRK-A&B), Allstate Corp. (ALL), The Travelers Companies Inc. (TRV), Ace Limited (ACE), The Chubb Corporation (CB), Progressive Corp. (PGR), and CNA Financial Corp. (CNA). Multi-line Insurers (40301030)-Companies with diversified interests in life, health, property and casualty insurance. Examples include American International Group Inc. (AIG), Hartford Financial Services Group Inc. (HIG), and Assurant Inc. (AIZ). Academic Research on Activities and Organization Numerous studies investigate various aspects of insurers' operating, investing, and financing activities. Another prolific area of research explores differences across organizational structures, primarily stock versus mutual companies. Studies have also looked at issues relevant to the insurance industry overall, including the value of and demand for insurance, the problems of adverse selection and moral hazard in insurance, and the underwriting cycle (PC insurance). I discuss these studies in separate categories by main focus. However, many of the studies provide evidence relevant to multiple categories. Efficiency and Profitability This area of research concerns the success of insurance companies in conducting their operating activities, primarily in terms of efficiency and profitability. Studies examining efficiency consider several dimensions, including cost efficiency, technical efficiency, allocative efficiency, and revenue efficiency. Cost efficiency measures the insurer's success in minimizing costs by Summary of Studies Cummins and Xie (2008a) examine efficiency, productivity and scale economies in the US PC insurance industry over the period 1993-2006. They find that the majority of firms below median size in the industry are operating with increasing returns to scale, and the majority of firms above median size are operating with decreasing returns to scale. However, a significant number of firms in each size decile have achieved constant returns to scale. Over the sample period, the industry experienced significant gains in total factor productivity, and there is an upward trend in scale and allocative efficiency. However, cost efficiency and revenue efficiency did not improve significantly over the sample period. Regression analysis shows that efficiency and productivity gains have been distributed unevenly across the industry. More diversified firms, stock insurers, and insurance groups were more likely to achieve efficiency and productivity gains than less diversified firms, mutuals, and unaffiliated single insurers. Higher technology expenditures increase the probability of achieving optimal scale for direct writing insurers but not for independent agency firms. Cummins, Weiss, Xie and Zi (2010) investigate economies of scope in the US insurance industry over the period 1993-2006. They test the conglomeration hypothesis, which holds that firms can optimize by diversifying across businesses, versus the strategic focus hypothesis, which holds that firms optimize by focusing on core businesses. Scope economies can originate from cost complementarities (including the sharing of inputs such as customer lists and managerial expertise), earnings diversification (which permits the firm to operate with higher leverage ratios), and revenue complementarities ("one-stop shopping" opportunities for consumers that reduce search costs). On the other hand, operating a conglomerate may increase management and coordination costs, exacerbate principal-agent conflicts, and create cross-subsidization among subsidiaries due to inefficient internal capital markets. The authors test for scope economies by estimating cost, revenue, and profit efficiency using data envelopment analysis (DEA), which measures efficiency by comparing each firm in an industry to a "best practice" efficient frontier formed by the most efficient firms in the industry. LH outputs are measured using real invested assets, the real value of incurred benefits, and additions to reserves for individual life, individual annuities, group life, group annuities, and accident-health insurance. PC outputs include real invested assets and the present values of real losses incurred for short and long-tail personal and commercial lines. The same inputs are used for each category of insurersadministrative labor, agent labor, materials and business services, and financial equity capital, all measured in real dollars using the Consumer Price Index. The authors regress efficiency scores on control variables and an indicator for strategic focus. They find that PC insurers realize cost scope economies, but these are more than offset by revenue scope diseconomies. LH insurers realize both cost and revenue scope diseconomies. Hence, they conclude that strategic focus is superior to conglomeration in the insurance industry. Elango, Ma, and Pope (2008) investigate the relationship between product diversification and firm performance in the US PC insurance industry using data for 1994-2002. The extent of product diversification shares a complex and nonlinear relationship with firm performance. The findings suggest that performance Summary of Studies Ke, Petroni, and Safieddine (1999) investigate the relation between CEO compensation and accounting performance measures as a function of ownership structure. Publicly-held property-liability insurers are used to consider the relation for firms with diffusely-held ownership; privately-held property-liability insurers are used to consider the relation for firms with closely-held ownership. The authors find a significant positive association between return on assets and the level of compensation for publicly-held insurers but, consistent with optimal contracting theory, no such relationship for privately-held insurers is found. Their results suggest that within closely-held firms, CEO compensation is less based on objective measures like accounting information and more on subjective measures. Ke (2001) investigates how taxes affect managerial compensation for a sample of privately held insurers whose managers own a large percentage of the firm's stock during 1989-1996. Shareholder/managers receive two types of income from the firm they own: compensation income as employees, and investment income as shareholders. Although compensation income is taxable to employees and deductible by employers, investment income is subject to double taxation. Thus, the mix of the two is an important tax-planning decision for management-owned insurers. The author finds that as individual tax rates increased relative to corporate tax rates from 1989-1992 to 1993-1996, shareholder/managers paid themselves less tax-deductible compensation relative to a control sample of non-management-owned insurers (i.e., privately held insurers with no managerial ownership). Mergers and Acquisitions Merger and acquisition activity in the insurance industry has been very significant for many years. According to the Insurance Information Institute, 3 the number of merger and acquisition transactions in the US insurance industry during the years 1999 to 2008 has ranged between 255 and 522 annually, with average total annual transactions value of about $40 billion. Similar to other industries, the motivations for M&A transactions in the insurance industry are to increase geographical reach and product range in order...

Solvency appraising is analyzed by means of an appropriate deductive methodology, pointing out the connection to the time dynamic of the business. This research line is framed into a combined approach to solvency measuring, full of suggestions from a regulatory perspective. The model is exemplified in the case of a temporary life annuity cohort.

Asian Journal of Finance & Accounting, 2016

Life insurance policies are no longer seen solely as a means of insuring life. Due to many new features introduced by life insurers, they are seen in the new light of serving savings and even investment purposes besides the basic purpose of insuring life. The present study discusses the rates of return given by different types of policies, and the effect of mortality on these rates of return across age, sum assured, and maturity period in each type of policy studied. The findings indicate that different types of policies give different rates of return and that mortality does have an effect on the rates of return. Endowment plans have higher rate of return with mortality incorporated, while for unit-linked investment plans, the rate of return is higher when it is treated purely as an investment instrument. The study also revealed that the unadjusted and mortality-adjusted rates of return follow a linear relationship that is very similar to the capital asset pricing model. The study opens a further scope of research by extending the methodology to include other relevant risk factors besides mortality, and for different types of policies across companies.

Proceedings of the Annual International Conference on Accounting Research (AICAR 2019), 2020

The objective of this research was to examine and analyse the influence of Net Premium Growth, Claim Ratio and Risk Based Capital affect the Financial Performance of Line Insurance Companies. The study population was insurance companies listed on the Indonesia Stock Exchange from 2014-2018. The sample used in this study were 17 life insurance companies. The statistical tool in this study is Eviews 11. Net Premium Growth and Claim Ratio do not significantly influence financial performance. Risk Based Capital has a negative effect on the financial performance of life insurance, namely ROA. Simultaneously the three ratios of Net Premium Growth, Claim Ratio and Risk Based Capital affect the financial performance of life insurance companies that are proxied by ROA. The implication of this research is that life insurance companies are expected to be able to maintain the stability of premium growth every year to be above the normal limit of 23%.

Journal of CENTRUM Cathedra: The Business and Economics Research Journal, 2012

The purpose of this study is to estimate and explain the performance of nonlife (i.e., property and casualty) insurers. The analysis consists of two stages. First, we propose the use of a multicriteria method to assess the condition of insurers while considering simultaneously a set of conflicting financial criteria. Then, we use regression analysis to examine the influence of firm-specific and country-specific attributes on the overall measure of performance obtained during the first stage. Macroeconomic conditions such as gross domestic product (GDP) growth, inflation, and income inequality are the most robust predictors of performance. However, other country-specific characteristics that relate to the institutional environment and financial or economic freedom do not appear to matter.

SSRN Electronic Journal, 2000

Life insurance products are priced according to two reciprocal requirements. As finacnial products, they must yield returns to investors, but decreasingly so with increased risk exposure. On the other hand, they must be priced to reflect the providers' risk exposure. Thus, the pricing and returns of life insurance products depend on the underlying risk exposure.