scholarly journals Scenario Analysis Approach for Operational Risk in Insurance Companies

2020 ◽  
Vol 14 (2) ◽  
pp. 153-165
Author(s):  
Michal Vyskočil
Keyword(s):  
Monte Carlo Simulation ◽  
Operational Risk ◽  
Solvency Ii ◽  
Typical Case ◽  
Insurance Companies ◽  
Insurance Company ◽  
Worst Case ◽  
To Come ◽  
Real Scenario ◽  
The Impact

The article deals with the possibility of calculating the required capital in insurance companies allocated to operational risk under Solvency II regulation and the aim of this article is to come up with model that can be use in insurance companies for calculating operational risk required capital. In the article were discussed and compared the frequency and severity distributions where was chosen Poisson for frequency and Lognormal for severity. For the calculation, was used only the real scenario and data from small CEE insurance company to see the effect of the three main parameters (typical impact, Worst case impact and frequency) needed for building the model for calculation 99,5% VaR by using Monte Carlo simulation. Article comes up with parameter sensitivity and/or ratio sensitivity on calculating capital. From the database arose two conclusions related to sensitivity where the first is that the impact of frequency is much higher in the interval (0;1) than above the interval to calculated capital and second conclusion is Worst case and Typical Case ratio, where we saw that if the ratio is around 150 or higher the calculated capital is increasing faster that the ration increase demonstrated on the scenario calculation.

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.

scholarly journals The Models of Assessment of the Insurance Companies’ Activities

2020 ◽  
Vol 12 (515) ◽  
pp. 395-400
Author(s):  
N. М. Bakalova ◽  
Keyword(s):  
Internal Model ◽  
Solvency Ii ◽  
Internal Models ◽  
Insurance Market ◽  
Insurance Companies ◽  
Insurance Company ◽  
Insurance Risk ◽  
Supervisory Authority ◽  
The Impact ◽  
The Eu

The article is aimed at assessing the impact of the Solvency II requirements on the Ukrainian insurance market and making a forecast of possible situations after the introduction of these requirements. To achieve the aim, the following tasks were set: to describe both the quantitative and the qualitative requirements of the Solvency II in the EU and the conditions for their use in the Ukrainian insurance market; to predict a possible change in the insurance market of Ukraine under the influence of the Solvency II quantitative requirements, which was performed as a result of the presented research. It is specified that the «novelty» envisaged by the Solvency II, which is related to the use of internal models, is an important step in the different sense of the assessment of the activities of insurance companies. This assessment is dominated not only by the quantitative parameters, but also by the problem of generally recognized risk, to which company is inclined and which is ready to take over. However, a significant number of aspects of this approach still need to be closer defined. The criteria related to the use of internal models for the needs of the supervisory authority have so far had the nature of the initial assumptions, and the experience of insurance companies (using internal models for their own needs, not the needs of the supervisory authority) concerns only a small percentage of companies. The internal model allows the insurance company to independently determine the actual demand for the required amount of guarantee capital. However, internal models include certain risks. The most important types of risks to consider in the internal models are grouped as follows: technical and insurance risk; risk associated with assets; operational risk and other types of risk. It is projected that the implementation of the project is likely to face many more unexpected problems, but the idea itself is interesting and understood by both insurance companies and regulatory authorities.

scholarly journals Cyber operational risk scenarios for insurance companies

2019 ◽  
Vol 24 ◽  
Author(s):  
R. Egan ◽  
S. Cartagena ◽  
R. Mohamed ◽  
V. Gosrani ◽  
J. Grewal ◽  
...  
Keyword(s):  
Cyber Security ◽  
Operational Risk ◽  
Social Engineering ◽  
Insurance Companies ◽  
List Type ◽  
Operational Risks ◽  
Life Insurer ◽  
Cyber Risk ◽  
The Impact ◽  
Over Time

AbstractCyber Operational Risk: Cyber risk is routinely cited as one of the most important sources of operational risks facing organisations today, in various publications and surveys. Further, in recent years, cyber risk has entered the public conscience through highly publicised events involving affected UK organisations such as TalkTalk, Morrisons and the NHS. Regulators and legislators are increasing their focus on this topic, with General Data Protection Regulation (“GDPR”) a notable example of this. Risk actuaries and other risk management professionals at insurance companies therefore need to have a robust assessment of the potential losses stemming from cyber risk that their organisations may face. They should be able to do this as part of an overall risk management framework and be able to demonstrate this to stakeholders such as regulators and shareholders. Given that cyber risks are still very much new territory for insurers and there is no commonly accepted practice, this paper describes a proposed framework in which to perform such an assessment. As part of this, we leverage two existing frameworks – the Chief Risk Officer (“CRO”) Forum cyber incident taxonomy, and the National Institute of Standards and Technology (“NIST”) framework – to describe the taxonomy of a cyber incident, and the relevant cyber security and risk mitigation items for the incident in question, respectively.Summary of Results: Three detailed scenarios have been investigated by the working party:∙Employee leaks data at a general (non-life) insurer: Internal attack through social engineering, causing large compensation costs and regulatory fines, driving a 1 in 200 loss of £210.5m (c. 2% of annual revenue).∙Cyber extortion at a life insurer: External attack through social engineering, causing large business interruption and reputational damage, driving a 1 in 200 loss of £179.5m (c. 6% of annual revenue).∙Motor insurer telematics device hack: External attack through software vulnerabilities, causing large remediation / device replacement costs, driving a 1 in 200 loss of £70.0m (c. 18% of annual revenue).Limitations: The following sets out key limitations of the work set out in this paper:∙While the presented scenarios are deemed material at this point in time, the threat landscape moves fast and could render specific narratives and calibrations obsolete within a short-time frame.∙There is a lack of historical data to base certain scenarios on and therefore a high level of subjectivity is used to calibrate them.∙No attempt has been made to make an allowance for seasonality of renewals (a cyber event coinciding with peak renewal season could exacerbate cost impacts)∙No consideration has been given to the impact of the event on the share price of the company.∙Correlation with other risk types has not been explicitly considered.Conclusions: Cyber risk is a very real threat and should not be ignored or treated lightly in operational risk frameworks, as it has the potential to threaten the ongoing viability of an organisation. Risk managers and capital actuaries should be aware of the various sources of cyber risk and the potential impacts to ensure that the business is sufficiently prepared for such an event. When it comes to quantifying the impact of cyber risk on the operations of an insurer there are significant challenges. Not least that the threat landscape is ever changing and there is a lack of historical experience to base assumptions off. Given this uncertainty, this paper sets out a framework upon which readers can bring consistency to the way scenarios are developed over time. It provides a common taxonomy to ensure that key aspects of cyber risk are considered and sets out examples of how to implement the framework. It is critical that insurers endeavour to understand cyber risk better and look to refine assumptions over time as new information is received. In addition to ensuring that sufficient capital is being held for key operational risks, the investment in understanding cyber risk now will help to educate senior management and could have benefits through influencing internal cyber security capabilities.

Managing uncertainty in a general insurance company

1990 ◽  
Vol 117 (2) ◽  
pp. 173-277 ◽  
Author(s):  
C. D. Daykin ◽  
G. B. Hey
Keyword(s):  
Computer Model ◽  
Flow Model ◽  
Insurance Companies ◽  
Simulation Methods ◽  
Insurance Company ◽  
Practical Applications ◽  
General Insurance ◽  
Alternative Approaches ◽  
The Impact

AbstractA cash flow model is proposed as a way of analysing uncertainty in the future development of a general insurance company. The company is modelled alongside the market in aggregate so that the impact of changes in premium rates relative to the market can be assessed. An extensive computer model is developed along these lines, intended for use in practical applications by actuaries advising the management of genera1 insurance companies. Simulation methods are used to explore the consequences of uncertainty, particularly in regard to inflation and investments. Some comments are made on the role of actuaries in general insurance. Alternative approaches to describing the behaviour of an insurance firm in the market are considered.

scholarly journals INCREASING THE COMPETITIVENESS OF INSURANCE COMPANY PRODUCTS AND SERVICES USING ECONOMIC AND MATHEMATICAL MODELING METHODS

2021 ◽  
Author(s):  
Mykhailo Demydenko ◽  
Ihor Pistunov
Keyword(s):  
Mathematical Model ◽  
Social Activity ◽  
Insurance Companies ◽  
Comprehensive System ◽  
Insurance Company ◽  
Competitive Advantages ◽  
Insurance Policy ◽  
Insurance Policies ◽  
The Impact

The competitiveness of an insurance company depends on the competitiveness of the products and services it introduces in the market. The competitive advantages of the insurance company are expressed in the attractiveness and competitiveness of insurance policies. An economic and mathematical model of increasing the competitiveness of the insurance company is proposed, which allows to calculate the integrated indicator of competitiveness of the insurance policy based on a comprehensive system of indicators characterizing the reliability of the insurance company, quality of its services, competitiveness, social activity. To analyze the impact of these indicators on the competitiveness of the insurance policy and identify areas for improving the efficiency and competitiveness of the insurance company. The competitiveness of an insurance company depends on the competitiveness of the products and services it introduces in the market. The assessment of the quality of insurance company services is compliance with the needs, requirements, and insurance interests of customers. This assessment is performed each time an individual client chooses to cooperate with an insurance company that meets his insurance interests and wishes. Therefore, the overall competitiveness of the enterprise depends on the competitiveness of products and services offered on the market. The competitive advantages of the insurance company are expressed in the attractiveness and competitiveness of insurance policies. The insurance market in recent years has shown consistently high growth, which makes it attractive for doing business. In these conditions, the task of modeling the activities of the insurance company in a highly competitive market environment becomes relevant. A mathematical model of increasing the competitiveness of the insurance company is proposed, which allows to calculate the integrated indicator of competitiveness of the insurance policy based on a comprehensive system of indicators characterizing the reliability of the insurance company, quality of its services, competitiveness, social activity. With the proposed model, insurance companies can objectively assess their weaknesses and strengths to ensure continuous growth and decent competition in a competitive market environment. The model allows you to select performance indicators and perform modeling and determine the consequences of changes in this indicator, analyze the impact of these indicators on the competitiveness of insurance policies and identify areas for improving the efficiency and competitiveness of the insurance company. By conducting such experiments, insurance companies can make more informed choices and decisions, analyze areas of competitiveness, and more efficiently allocate resources.

scholarly journals TONUITY: A NOVEL INDIVIDUAL-ORIENTED RETIREMENT PLAN

2018 ◽  
Vol 49 (1) ◽  
pp. 5-30 ◽  
Author(s):  
An Chen ◽  
Peter Hieber ◽  
Jakob K. Klein
Keyword(s):  
Risk Aversion ◽  
Switching Time ◽  
Extreme Case ◽  
Solvency Ii ◽  
Capital Requirements ◽  
Insurance Companies ◽  
Longevity Risk ◽  
Insurance Company ◽  
Risk Capital ◽  
Medium Risk

AbstractFor insurance companies in Europe, the introduction of Solvency II leads to a tightening of rules for solvency capital provision. In life insurance, this especially affects retirement products that contain a significant portion of longevity risk (e.g., conventional annuities). Insurance companies might react by price increases for those products, and, at the same time, might think of alternatives that shift longevity risk (at least partially) to policyholders. In the extreme case, this leads to so-called tontine products where the insurance company’s role is merely administrative and longevity risk is shared within a pool of policyholders. From the policyholder’s viewpoint, such products are, however, not desirable as they lead to a high uncertainty of retirement income at old ages. In this article, we alternatively suggest a so-called tonuity that combines the appealing features of tontine and conventional annuity. Until some fixed age (the switching time), a tonuity’s payoff is tontine-like, afterwards the policyholder receives a secure payment of a (deferred) annuity. A tonuity is attractive for both the retiree (who benefits from a secure income at old ages) and the insurance company (whose capital requirements are reduced compared to conventional annuities). The tonuity is a possibility to offer tailor-made retirement products: using risk capital charges linked to Solvency II, we show that retirees with very low or very high risk aversion prefer a tontine or conventional annuity, respectively. Retirees with medium risk aversion, however, prefer a tonuity. In a utility-based framework, we therefore determine the optimal tonuity characterized by the critical switching time that maximizes the policyholder’s lifetime utility.

scholarly journals THE IMPACT OF THE INDUSTRIAL REVOLUTION 4.0 ON THE INSURANCE INDUSTRY AND WHETHER OF THE ASSETS AND INVESTMENTS PLAY A ROLE TO INVESTMENT YIELD?

2020 ◽  
Vol 8 (2) ◽  
pp. 345-351
Author(s):  
Iskandar Muda ◽  
Hafizah ◽  
Bunga Aditi ◽  
Hermansyur ◽  
Erlina
Keyword(s):  
Financial Services ◽  
Financial Stability ◽  
Industrial Revolution ◽  
Insurance Industry ◽  
Least Square Method ◽  
Partial Least Square ◽  
Least Square ◽  
Insurance Companies ◽  
Insurance Company ◽  
The Impact

Purpose of the study: This research aims to know the influence of the Industrial Revolution 4.0 era on the insurance industry on the side of assets and Investment insurance companies to Investment Yield Sharia Insurance in Indonesia. Methodology: This type of research is explanatory research. This type of research data is secondary data sourced from the Financial Services Authority (OJK) Republic of Indonesia period in 2016-2107. The tool of analysis in this research is the Partial Least Square method using Smart PLS statistics. Main Findings: The results are an influence of Assets and Investment on Investment Yield on insurance companies in the Industrial Revolution 4.0 era. In the era of the industrial revolution, 4.0 potential insurance improve economic growth through several aspects, namely promote financial stability. Facilitate trade and commercial activities. mobilize domestic savings. Offering a variety of risk management on capital. Increase more efficient allocation of capital and reduce the risk of loss and can increase Investment Yield for shareholders and stakeholders. Applications of this study: This research is the observation only on Sharia Insurance Company sample while other issuers are not observed in this study and this research implies that sharia insurance issuers are growing and contributing to their shareholders and shareholder. Novelty/Originality of this study: The first time observing the Sharia Insurance industry industrial Revolution 4.0 era and previous research to observe in Sharia banking.

scholarly journals Insurance Distribution Carried Out by Insurers in Spain

2020 ◽  
pp. 179-195
Author(s):  
Javier Vercher-Moll
Keyword(s):  
Insurance Companies ◽  
Insurance Company ◽  
Governance System ◽  
Legal Requirements ◽  
Insurance Policies ◽  
New Policies ◽  
The Impact

AbstractIn this chapter I analyze the impact that Directive 2016/97 has on insurance companies. The new requirements for employees who distribute the insurance policies of the insurance company increase the protection for customers. In addition, these new requirements lead to a reform of the governance system of the insurance company. New policies, new procedure manuals are necessary to carry out the distribution of insurance by the insurance company. Therefore, I will study the new legal requirements and their impact on the Spanish regulations.

The impact of insurance company mandated compression stocking trial on rate of intervention in patients with symptomatic venous reflux disease

2011 ◽  
Vol 26 (6) ◽  
pp. 235-236 ◽  
Author(s):  
D Calcagno ◽  
J A Rossi
Keyword(s):  
Average Length ◽  
Venous Intervention ◽  
Insurance Companies ◽  
Compression Stocking ◽  
Insurance Company ◽  
Compression Stockings ◽  
Patient Reported ◽  
Cast Doubt ◽  
The Impact

Objective Insurance companies have criteria for a venous intervention to be a covered procedure, including symptoms, vein size, and a trial of conservative therapy with compression stockings. The goal of this study was to see the impact of such mandated stocking use on ultimate intervention. Method A retrospective review was done of prospectively gathered data entered in the electronic medical record. Two-hundred consecutive new patients evaluated at our vein center were included. Results Forty-four of the 200 patients did not require any procedures and 39 patients had procedures scheduled for small or asymptomatic venous changes that did not meet insurance criteria. This left 117 patients with venous symptoms in whom evaluation concluded that a corrective procedure could be performed. These interventions included largely radiofrequency ablation and phlebectomy. Of these 117 patients, 48 had previously used compression stockings. In the remaining 69 patients, stockings were provided on the day of initial consultation and these 69 patients served as the subjects for this review. At three month follow up, one patient reported the stockings help enough that she did not want to pursue correction. Two patients had continued pain and were planning correction once other unrelated issues resolved. Three patients said they never wore the stockings. Sixty-one patients had procedures performed. The average length of stocking use in patients who chose corrective procedures was 103 days. One patient could not be reached. Conclusion Of the patients that reported they used the stockings as prescribed, one chose chronic stocking therapy and 63 patients either had procedures or were planning procedures. Use of prescription stockings was effective in avoiding intervention in one of 64 cases (2%), despite an average trial of 103 days. These results cast doubt on the merits of the use of an insurance company mandated stocking trial.

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