scholarly journals OPTIMAL ASSET ALLOCATION IN LIFE INSURANCE: THE IMPACT OF REGULATION

2016 ◽  
Vol 46 (3) ◽  
pp. 605-626 ◽  
Author(s):  
An Chen ◽  
Peter Hieber
Keyword(s):  
Life Insurance ◽  
Asset Allocation ◽  
Regulatory Policy ◽  
Capital Requirements ◽  
Insurance Company ◽  
Traffic Light ◽  
Optimal Insurance ◽  
Insurance Contracts ◽  
Solvency Capital ◽  
The Impact

AbstractIn a typical equity-linked life insurance contract, the insurance company is entitled to a share of return surpluses as compensation for the return guarantee granted to the policyholders. The set of possible contract terms might, however, be restricted by a regulatory default constraint — a fact that can force the two parties to initiate sub-optimal insurance contracts. We show that this effect can be mitigated if regulatory policy is more flexible. We suggest that the regulator implement a traffic light system where companies are forced to reduce the riskiness of their asset allocation in distress. In a utility-based framework, we show that the introduction of such a system can increase the benefits of the policyholder without deteriorating the benefits of the insurance company. At the same time, default probabilities (and thus solvency capital requirements) can be reduced.

scholarly journals Stress and scenario tests in the context of a Romanian non-life insurance company

2019 ◽  
Vol 13 (1) ◽  
pp. 149-161
Author(s):  
Aurora Elena Dina Manolache
Keyword(s):  
Life Insurance ◽  
Stress Testing ◽  
Capital Requirements ◽  
Stress Factors ◽  
Insurance Company ◽  
Life Insurance Company ◽  
High Exposure ◽  
Natural Catastrophe ◽  
Best Estimate ◽  
Solvency Capital

Abstract The main aim of the article is to assess the vulnerabilities and resilience of a Romanian non-life insurance company in the context of different predefined insurance stress scenarios: natural catastrophe scenario and business scenario. The natural catastrophe scenario consists in two distinct scenarios: earthquake and flood, which were carried out separately and aggregated based on three stress factors: increasing by 15% of PML, increasing by 5% of the gross best estimate claim provisions and reinsurer’s incapacity to pay. The business stress scenario was based on four stress parameters: increasing by 3 % of the claims provisions due to the inflation impact, increasing by 10% of the gross earned premium for MTPL due to the legislative changes, increasing by 15% of the claims provisions for MTPL due to the increase of frequency and severity of the losses induced by the exposure growth as a result of the lower premiums and decreasing by 10% of the ceded best estimate. The results of the stress testing shown that the insurer is more sensitive to business scenario compared to natural catastrophe scenario due to the significant exposure on the MTPL line of business. High exposure to earthquake risk is a characteristic for Romania and the stress testing results confirm the vulnerability of the insurer to the earthquake scenario (non-compliance of the solvency capital requirements), due to the biggest impact of the factor: reinsurer’s incapacity to pay. Therefore, the quality of reinsurance is very important for Romanian insurance companies to be able to manage the risks arising from the seismic events and to be compliant with the regulatory solvency capital requirements.

The impact of time discretization on solvency measurement

2017 ◽  
Vol 18 (1) ◽  
pp. 2-20 ◽  
Author(s):  
Hato Schmeiser ◽  
Daliana Luca
Keyword(s):  
Discrete Time ◽  
Risk Measures ◽  
Time Discretization ◽  
Capital Requirements ◽  
Insurance Company ◽  
Probability Of Ruin ◽  
Content Type ◽  
The One ◽  
Discretization Interval ◽  
The Impact

Purpose The purpose of this paper is to study how the discretization interval affects the solvency measurement of a property-liability insurance company. Design/methodology/approach Starting with a basic solvency model, the authors study the impact of the discretization interval on risk measures. The analysis considers the sensitivity of the discrepancy between the risk measures in continuous and discrete time to various parameters, such as the asset-to-liability ratio, the characteristics of the asset and liability processes, as well as the correlation between assets and liabilities. Capital requirements for the one-year planning horizon in continuous vs discrete time are reported as well. The purpose is to report the degree to which the deviations in risk measures, due to the different discretization intervals, can be reduced by means of increasing the frequency with which the risk measures are assessed. Findings The simulation results suggest that the risk measures of an insurance company are consistently underestimated when assessed on an annual basis (as it is currently done under insurance regulation such as Solvency II). The authors complement the analysis with the capital requirements of an insurance company and conclude that more frequent discretization translates into higher capital requirements for the insurance company. Both the probability of ruin and the expected policyholder deficit (EPD) can be reduced through intermediate financial reports. Originality/value The results from our simulation analysis suggest that that the choice of discretization interval has an impact on the risk assessment of an insurance company which uses the probability of ruin and the EPD as risk measures. By assessing the risk measures once a year, both risk measures and the capital requirements are consistently underestimated. Therefore, the recommendation for risk managers is to complement the capital requirements in solvency regulation with sensitivity analyses of the risk measures presented with respect to time discretization. On the one hand, it seems to us that there is value in knowing about the substantial discrepancy between the focused time discrete ruin probability and EPD compared to the continuous version. On the other hand, and if there are no substantial transaction costs associated with more frequent monitoring of solvency figures, a frequent update would be helpful to increase the accuracy of the calculations and reduce the EPD.

scholarly journals Asset Allocation to Optimise Life Insurance Annuity Firm Economic Capital and Risk Adjusted Performance

2008 ◽  
Vol 3 (1-2) ◽  
pp. 187-214 ◽  
Author(s):  
Bruce T. Porteous ◽  
Pradip Tapadar
Keyword(s):  
Life Insurance ◽  
Asset Allocation ◽  
Financial Services ◽  
Stochastic Modelling ◽  
Economic Capital ◽  
Conventional Wisdom ◽  
Low Risk ◽  
Bond Type ◽  
The Impact ◽  
Modelling Approach

ABSTRACTThe impact that asset allocation has on the economic capital and the risk adjusted performance of financial services firms is considered in this article. A stochastic modelling approach is used in conjunction with a life insurance annuity firm illustrative example. It is shown that traditional solvency driven deterministic approaches to financial services firm asset allocation can yield sub optimal results in terms of minimising economic capital or maximising risk adjusted performance. Our results challenge the conventional wisdom that the assets backing life insurance annuities and financial services firm capital should be invested in low risk, bond type, assets. Implications for firms, customers, capital providers and regulators are discussed.

scholarly journals The impact of lending on bancassurance activity

2019 ◽  
Vol 13 (1) ◽  
pp. 171-181
Author(s):  
Elda Marzai Abliz
Keyword(s):  
Negative Impact ◽  
Distribution Channel ◽  
Solvency Ii ◽  
Capital Requirements ◽  
Financial Supervision ◽  
Insurance Companies ◽  
Insurance Company ◽  
Customer Base ◽  
Premium Income ◽  
The Impact

Abstract Due to financial crisis, and especially because of prudence in lending (retail, micro, and corporate), banks are looking for new sources of income, and bancasurance is clearly a potential source of revenue. Thus, in the financial market, the interests of two major components of it are met: banks maximize commission income, and insurers make access to the large customer base of banks. Bancassurance is a distribution channel of insurance products through bank branches, bringing important advantages for banks, insurance companies and customers. The main advantage for the bank is that earns fee amount from the insurance company, the insurance company increases customers data base and market share, the client satisfy his financial needs and requests in the same institution. Considering that in Romania, banks and insurers do not provide information on the number of insurances sold via the bancassurance distribution channel, as well as commissions obtained by banks for the insurance sale, to determine the development of bancassurance in Romania, we used the statistical data provided by the National Bank of Romania, on credit growth and data provided by The Financial Supervision Association, on the evolution of gross written premiums. Bancassurance is one of the most important insurance distribution channels, accounting for approximately 36% of the global insurance market, in 2016, Europe’s insurers generated total premium income of €1 189bn and had €10 112bn invested in the economy. Regarding to the risks of bancassurance business for banks and insurers, they mainly concern distinct capital requirements for the banking and insurance systems, which will be covered by the Basel III and Solvency II directives. This paper aims to analyze the influence of credit on the bancassurance activity in the last 5 years in Romania, the economic, political and legal factors that have a negative impact on the development of bancassurance, and also the calculating the correlation coefficient r (Pearson’s coefficient) and his result.

Are Risk-Based Capital Requirements Detrimental to Corporate Lending?

2018 ◽  
Author(s):  
Brunella Bruno ◽  
Giacomo Nocera ◽  
Andrea Resti
Keyword(s):  
Asset Allocation ◽  
Business Models ◽  
Capital Requirements ◽  
Financial Repression ◽  
European Banking ◽  
European Banks ◽  
Corporate Loan ◽  
Capital Regulations ◽  
Asset Allocations ◽  
The Impact

In this chapter, we summarize the main results of a recent empirical research concerning European banks. We first explore the main drivers of the differences in risk-weighted assets (RWAs) across a sample of fifty large European banking groups. We then assess the impact of RWA-based capital regulations on those banks’ asset allocations in 2008–14. We find that risk weights are affected by bank size, business models, and asset mix. We also find that the adoption of internal ratings-based (IRB) approaches is an important driver of RWAs and that national segmentations explain a significant (albeit decreasing) share of the variability in risk weights. As for the impact of internal ratings on banks’ asset allocation in 2008–14, we uncover that banks using IRB approaches more extensively have reduced more (or increased less) their corporate loan portfolio. This effect is somewhat stronger for banks located in Eurozone periphery countries during the 2010–12 sovereign crisis. We do not find evidence, however, of internal models producing a reallocation from corporate loans to government exposures, suggesting that other motives prevailed in driving banks towards sovereign bonds during the Eurozone sovereign crisis, including the so-called ‘financial repression’ channel.

ASSESSMENT OF FINANCIAL STABILITY AND PROFITABILITY OF THE INSURANCE COMPANY

2020 ◽  
Vol 2 (10) ◽  
pp. 80-86
Author(s):  
E. A. RUSETSKAYA ◽  
◽  
L. V. AGARKOVA ◽  
V. V. AGARKOV ◽  
◽  
...  
Keyword(s):  
High Risk ◽  
Financial Stability ◽  
Insurance Company ◽  
Large Share ◽  
Insurance Contracts ◽  
Financial Condition ◽  
Insurance Portfolio ◽  
Standard Values ◽  
The Impact ◽  
Authorized Capital

The study of the issues of financial stability and profitability of an insurance company showed that its financial condition is assessed as financially stable and highly profitable. Most of the calculated indicators correspond to the standard values. The company possesses a large share of highly liquid assets, is provided with its own funds, has a paid authorized capital, insurance reserves are sufficient to fulfill obligations under insurance contracts. The main directions of improving financial stability can be increasing the level of profitability and reducing the impact of risks by increasing the competitiveness of services, current forecasting of activities, optimization of the insurance portfolio, as well as reducing the share of high-risk investments.

scholarly journals The Effects of Insurances, Pensions and Mutual Funds on Economic Growth

2020 ◽  
Vol 6 (1) ◽  
pp. p17
Author(s):  
Richard S. Ramoutar
Keyword(s):  
Economic Growth ◽  
Mutual Funds ◽  
Life Insurance ◽  
Mutual Fund ◽  
Insurance Premium ◽  
Insurance Company ◽  
Market Interaction ◽  
Distributed Lag ◽  
Long Run ◽  
The Impact

Earlier studies on the impact of the insurance sectors activities on economic growth have largely failed. To examine the financial development market interaction of pensions and mutual funds linkages, through which insurance assets affects economic growth. This study re-examines the impact of life insurance premium volume, non-life insurance premium volume, insurance company assets, pension fund assets and mutual fund assets on economic growth. Using panel data of 33 countries over the period 2000-2016. The study applied the Autoregressive Distributed Lag (ARDL) model in panel setting using the PMG (Pooled Mean Group) and MG (Mean Group) estimators in this analysis. The study findings indicate that cointegration exists among all series and that insurances and mutual funds stimulate economic growth in both the short and long run.

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