Risk And Return Analysis In An Insurance Sector: Aviva Life Insurance Company Case Study

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Introduction of Risk And Return Analysis In An Insurance Sector: A Case Study Of Aviva Life Insurance Company Assignment

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Introduction Of Risk And Return Analysis In An Insurance Sector: Aviva Life Insurance Company Case Study

Part 1: Research Proposal

The process of the analysis of the risk in the insurance sector of a company may determine the premium amount against the claim of the insurance. The risk management in the sector of the Aviva life insurance company may affect the life, asset, and health of the business.

A. Research topic

a. Background of Research

The topic has been based on the various risks that may be rising at the time of the investment of the Aviva Life Insurance Company.  

b. Aim of research

The main goal of the research topic is to offer the proposal the ability to offer a minimum return on the investment.

c. The objective of the research

  • To analyze the various types of risk
  • To collect data and new techniques to mitigate the risk
  • To receive the recurring at the level of the investment of the risk
  • To attract the investors by using various methodologies

d. Rationale of Research

The rationale of the research is to evaluate the various types of risk and mitigate the risk at the time of the investment in the insurance sector (Aviva, 2022). The risks may be expected to understand the requirement of the changes in federal and the other stage level. It may affect the management of the company as well as the requirements of the customers. The risk may be the chance of the loss of the finance however, the return has required by the investor. Sometimes the chances may become harmful for the company. The risk management framework may provide the way of the different types of the risk that may be the company may face in the future. The rationale of the research may help to implicate the various risk policies. It may enable the risk that occurs continuously at the tie of the inherent of risk.

B. Literature review

Determination and the consequences in the sample of the international that may create Governance of the risk in the sector of insurance

The relation between the measurement of the performance, risks and governance has comes in the sample paper of the 107 of the insurance company. RGI (risk governance index) has included the various solvencies of the provisions and the risk material (Magee et al. 2019). The executive committee can be the chief risk officer, and the risk committee and the board industry. It will be found at the time of the crisis period 2008-2009 the firms may be expected lower default frequency.

The changes of the paradigm- evaluation of the risk in the management

The evaluation of the risk management has been discussing the various types coif the risks that may occur at the time of the investment in the company. Capital management has seen the solely responsibility of finance (Ozdemir, 2021). The disclosure of the finance and the regulatory capital may be the part of the sensitive risk. Therefore, the availability of the risk may intercept the performance of the risk (Ozdemir, 2021). The side of the demand is the requirement of the capital in the company, which may be indirectly proportioned to the level of the risk. These types of changes may be included at the time of the formation of the risk. It may also provide the perspective of the evaluation of the profession of the risk (Ozdemir, 2021). The many industries may cover the risk with the help of the “Audit Committee of the board” (Ozdemir, 2021). There may be various technology may b applicable for the mitigation of the risk and try to adopt the management of the “extension of the risk.”

The insurance sector of the European- a dynamic MST model of the risk systematic

The paper may cover the way of response to the “Systemic risk and macro prudential policy in insurance.” It may indicate the process of building up the risk, especially at the arrangement of the risk (Denkowska and Wanat, 2021). The MST model may be based on the analysis of the contribution to earache of the 28 largest insurance companies in Europe. Furthermore, the model had the contribution to the appearance of the G-SIIs list to find out the systemic risk of the company (Denkowska and Wanat, 2021). Moreover, the determination of the contribution of the systemic risk may be applicable for the highest between certainly at the degree the obtained by the MST.

C. Proposed data type and collection techniques

a. Type of data

Aviva has continued the development of the data of the science of the capacity to the both of the part of the information. The report has been done with the help of secondary data. The data collection has been done with a personal visit to the company and the help of the different types of journals. There is a number of websites, social media, and newspapers. 

b. Data collection method

The method may be used by the identification of the data and the measurements. There maybe the various risk reports and the scenario of the testing or the design that enable the risk of the dynamic risk. The application of the data may be based on the various types of the data may be analysed by the management.

D. Proposed methodology

The enhancement of the scenario may be based on the determination of the approaches at the appropriate level of the management in respect of the risk (Siddiqui, 2020).

Research design

The Aviva Life Insurance Company has been following the descriptive types of the design in the methodology period. The information has been collected systematically that describes the phenomenon, situations, and the number of the population engaged with the company.

Research approach

The researcher has taken the inductive method for evaluating the risk of the company. The process will be started with the observation of the hypothesis proportion about to the experiences of the management.

Research philosophy

The researcher has the philosophy of the company that may state the performs at the specific role that may be interpretivism (Hürlimann, 2019). This method may help to execute the number of the investors and the risk arises at the time of the investment in the company. It may indicate various types of the confusion to the researcher as the collection of the data there may be a number of the information.

Research method

The collection of the data may be based on both qualitative and quantitative data both. The company has the number of the insurance has been made for at the period.

Conclusion

The study of the report it may be concluded that the proposal of the company me be acceptable. The process of the mitigation of the risk and the uses of the various types of methods has been helpful for the company to attract the attention of the investors. The requirement of outsources of the function of the internal or the external part of the company may exit the terms of the plan.

Part 2: Data Analysis

This part has include the analysis of the data provided in the case study by the uses of the vicarious tools and the answers of the questions. The indexed used in the measurement based on the stock market of “Dow Jones Industrial Average (DJIA)” and “the Standard & Poor (S&P) 500.” Scatter plot, correlation, coefficient will be calculated to interpret relationship between variables.

1. Scatter diagram for the data and its interpretation

 Scatter Plot

Scatter diagram of a dataset indicted relation between variables. Variables of above diagram are Dow Jones and S&P index. Scatter plot diagram indicated that index of these two variables are low because index of Dow Jones situated above 1000 point whereas index of S&P 500 run within 0 to 2000. This plot implies that both of the indexes have no relation and they do not depend on each other.

2. Computation of correlation coefficient

Correlation Coefficient

Dow jones

S&P 500

Dow jones

1

S&P 500

0.917271449

1

Table 1: Correlation

(Source: Developed by Learner)

The correlation covariance may use for the measurement of the strength of the various relations between the movement of the two variables (Giri et al. 2018). There may be the strongest correlation may be considered above 0.4 which may be good for the company. The calculation of the correlation and the covariance may be based on the investment in DJIA and S&P 500. The above figure shows that the Dow Jones has occurred 1 and the S&P 500 has become 0.91727 It shows that it has been above 0.4, which shows the company has a better performance in the market.

3. Are they poorly correlated, or do they have a close association 

 Correlation range run between 0 to 1 and 1 indicated high relation. On other hand, value at about 0 indicted that index are poorly correlated. Correlation value of the two index are 0.91 and it is near about 1. It implies that relation between two variables is high and volatility of one stock can make impact on other stock or index.

4. Develop the least squares estimated regression equation 

Variance

Standard deviation

Date

Dow jones

S&P 500

Dow jones

S&P 500

Dow jones

S&P 500

11-Feb

10425

1387

-0.017971108

-0.027210624

0.000322961

0.000740418

18-Feb

10220

1346

-0.034213353

-0.006502438

0.001170554

4.22817E-05

25-Feb

9862

1333

0.05079986

0.057188964

0.002580626

0.003270578

31-Mar

10367

1409

-0.042025604

-0.006785842

0.001766151

4.60477E-05

10-Mar

9929

1395

0.06494744

0.050381148

0.00421817

0.00253826

17-Mar

10595

1464

0.048699676

0.044507367

0.002371658

0.001980906

24-Mar

11113

1527

-0.01540004

-0.015429119

0.000237161

0.000238058

31-Mar

10922

1499

0.01909777

0.01446372

0.000364725

0.000209199

7-Apr

11111

1516

-0.076022239

-0.113920228

0.005779381

0.012977818

14-Apr

10306

1357

1

1

1

1

Table 2: Variance and Standard Deviation

(Source: Developed by Learner)

The linear regression equation may explain the value that may be dependent or independent at the same tie of the estimation (Armstrong, 2019). At the starting date of the investment of the Dow Jones has 10425 and the S&P 500 has 1387. Therefore it may be shows that the Dow Jones -0.017971108 -0.027210624 S&P 500 of the variance. The standard deviation has been becomes 0.000322961 and 0.000740418 Dow Jones and S&P 500 respectively.

5. Computation of coefficient of Determination and Recommendation of the regression model for the purpose of estimation

Interpretation of Coefficient

The model of the coefficient covariance may be determined for the investment of the company. The uses of the linear equation has been separately analyze the

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.924357456

R Square

0.854436707

Adjusted R Square

0.833641951

Standard Error

193.5978713

Observations

9

ANOVA

df

SS

MS

F

Significance F

Regression

1

1540023.05

1540023.05

41.08904671

0.000363781

Residual

7

262360.9504

37480.13577

Total

8

1802384

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

2243.569163

1288.357062

1.741418765

0.125149684

-802.9111892

5290.049516

-802.911

5290.05

1387

5.778676439

0.901499199

6.410073846

0.000363781

3.64696957

7.910383307

3.64697

7.910383

Table 3: Regression Model

(Source: Developed by Learner)

Regression model has been calculated for coefficient correlation of the variables (Poldrack et al. 2020). Regression model that coefficient of these variables is 22243.5613. This data implies that two variables are highly correlated with each other. On the hand, both factors can be impacted by each other.

Recommendation for Regression

Company can various type of regression model for measure R square value, coefficient (Poldrack et al. 2020). They can use linear regression model for their analysis and calculation purposes it is effective method for calculate linear way. Different type of variables can be analysed through this method. S&P 500 and Dow Jones index are two important for investor and they analyse variables according to their need. This method can use several number of variables for calculation which can be effective for users.

Conclusion

The case study may be concluded that the company has may be face the various number of the profit or the loss at the different stages. The company has the investment of the various number of stocks in the share market. The share of the company may be faces the huge number of the profit by investing in the stock market of the S&P 500. Therefore, the company need to follow the required number of the methods for the fulfilment of the better performance of the company. However, the company may be the requirement of the various methods of fulfilment of the market. 

Reference list

Armstrong, R.A., 2019. 2020. Evaluating the efficiency of Indian life insurance sector. Indian Journal of Economics and Development, 16(1), pp.72-80.

Aviva.com, (2022), Annual report, 2022, Available at: https://www.aviva.com/sites/default/files/Annual_Report%20_18-19_Website.pdf [Accessed on: 06.05.2022]

Denkowska, A. and Wanat, S., 2021. A dynamic MST-deltaCoVaR model of systemic risk in the European insurance sector. Stat. Transit. New Ser, 22, pp.173-188. 

Giri, J., Pokharel, P.R., Gyawali, R., Timsina, J. and Pokhrel, K., 2018. New regression equations for mixed dentition space analysis in Nepalese mongoloids. BMC oral health, 18(1), pp.1-7.

Hürlimann, C., 2019. Research Philosophy and Ethics. In Valuation of Renewable Energy Investments (pp. 111-126). Springer Gabler, Wiesbaden.

Magee, S., Schilling, C. and Sheedy, E., 2019. Risk governance in the insurance sector—determinants and consequences in an international sample. Journal of Risk and Insurance, 86(2), pp.381-413.

Ozdemir, B., 2021. Evolution of Risk Management from Risk Compliance to Strategic Risk Management Part II Evolution of the Risk Executive and the Boards–The Changing Paradigm An analysis on the Canadian banking and insurance sectors.

Poldrack, R.A., Huckins, G. and Varoquaux, G., 2020. Establishment of best practices for evidence for prediction: a review. JAMA psychiatry, 77(5), pp.534-540.

Should Pearson's correlation coefficient be avoided?. Ophthalmic and Physiological Optics, 39(5), pp.316-327.

Siddiqui, S.A., Mishra, P., Pandey, C.M., Singh, U. and Gupta, A., 2018. Scales of measurement and presentation of statistical data. Annals of cardiac anaesthesia, 21(4), p.419.

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