E-ISSN:2583-1747

Research Article

Private Sector Life Insurance

Management Journal for Advanced Research

2022 Volume 2 Number 4 August
Publisherwww.singhpublication.com

Efficiency Analysis of LICI and Select Private Sector Life Insurance Companies in India - A Comparative Study

Qaiser IJ1*
DOI:10.54741/mjar.2.4.4

1* Iffat Jahan Qaiser, Research Scholar, Department of Commerce, University of Calcutta, Calcutta, India.

Insurance refers as a contract in which the insured transfers risk of potential loss to the insurer who promises to compensate the former upon suffering loss. The promise is called the insurer and the promise is called the insured. Insurance premium is the monetary consideration paid by the insured to the insurer for the cover granted by the insurance policy. The objective of the present study is to investigate the factors affecting efficiency of insurance companies operating in India. The target population of the study was 24 public and private life insurance companies and four important financial ratios. For which 10 years audited financial statements of the companies from 2009 to 2019 was studied for analysis. The secondary data were collected by reviewing of financial statements and related published and unpublished materials to achieve the objective of this study.

Keywords: insurance, life insurance corporation of india, public, private, anova

Corresponding Author How to Cite this Article To Browse
Iffat Jahan Qaiser, Research Scholar, Department of Commerce, University of Calcutta, Calcutta, , India.
Email:
Qaiser IJ, Efficiency Analysis of LICI and Select Private Sector Life Insurance Companies in India - A Comparative Study. Manag. J. Adv. Res.. 2022;2(4):22-34.
Available From
https://mjar.singhpublication.com/index.php/ojs/article/view/22

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2022-07-02 2022-07-19 2022-08-06
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 10.22

© 2022by Qaiser IJand Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

Introduction

The Indian Insurance Sector is basically divided into two categories i.e. Life Insurance and Non-Life Insurance. The Non-Life Insurance Sector is also known as General Insurance. Both the Life Insurance and the Non-Life Insurance is governed by the IRDAI.

The insurance industry of India consists of 63 insurance companies of which 24 are in life insurance business and 39 are non-life insurers. Among the life insurers, Life Insurance Corporation of India (LICI) is the sole public sector company.

The likelihood of an event or loss may be mathematically calculated or it may be based on the statistical results of experience in order to determine the amount of premiums that would be required to accumulate a common fund or pool, to meet the losses upon their arising.

The roots of the modern Indian life insurance industry originated with the incorporation of the Life Insurance Corporation of India (LICI) in 1956, consolidating together one hundred and fifty-six Indian and sixteen non-Indian insurers.

The LICI was the sole player in the market until the late 1990s when the insurance sector was reopened to the private sector. There are currently twenty-four players in the Indian Life Insurance Industry, the largest of which is the LICI, the only public sector life insurance company.

Literature Review

Ray and Pathak (2006) opined that ever since the privatization of the insurance sector in India in 2000, the industries have been witnessing the birth of numerous private players, mostly joint ventures between foreign insurance giants and Indian diversified conglomerates and each one is trying to make an inroad into the huge untapped market. Goswami (2007) examined that prior to privatization of insurance sector,

Life Insurance Corporation of India was the sole player in the life insurance industry in India. In six years since the entry of private players in the insurance market, LICI has lost 29% market share to the private players, although both, market size and the insurance premium being collected, are on the rise Bhatia and Sharma (2008) highlighted in their study that the India’s insurance sector which was a state monopoly until 1999, went a significant change in the post reform era and the business of private insurance companies increased rapidly overtime.

Bedi and Singh (2011) analysed the overall performance of life insurance industry in India between pre and post economic reform era and revealed that the life insurance industry showed a huge growth in its performance because of Liberalization, Privatization and Globalisation.

Gulhane (2013) discussed that there is significant difference in the growth rate of Fresh Business Premium between Public and Private Life Insurance Companies, there is significant difference in the growth of Number of policies issued by Public and Private Life Insurance Companies and Life Insurance Corporation of India enjoys dominance in Life Insurance Sector.

Long and Li (2017) employ a two-stage DEA model to evaluate operating performance of insurance companies, and their results indicate that proposed method is able to analyze with high accuracy. Ghosh (2020) observed that during post reform period growth of LICI business has grown significantly than private players at early period of reform but from 2014-15 business growth of LICI declines significantly compare to private life insurance companies in India.

Research Gap

After studying the several literatures, a research gap is being observed in the area of efficiency analysis of life insurance companies. In our present study, we have tried our level best to fulfill the gap.


Objective of the Study

The objective of the present study is to make a comparative study on efficiency analysis of LICI and select Private Sector Life Insurance Companies operating in India.

Research Methodology

In our present study, descriptive statistics, ANOVA is employed in SPSS 20 Software. One Public and Twenty-Three Private Life Insurance companies and four important financial ratios are considered for the study.

10 years audited financial statements of the companies from 2009 to 2019 was studied for analysis. The secondary data were collected by reviewing of financial statements and related published and unpublished materials. The performance evaluation analysis is based on the following key points.

Descriptive Statistics: Mean, Standard Deviation, Skewness and Kurtosis are being used for explaining the nature of the data.

ANOVA: ANOVA provides a statistical test of whether two or more population means are equal or not and therefore generalizes the t-test beyond two means.

Post-HocTest: To find out exactly, where the difference

Period of Study : 2009 - 2019

Data Analysis and Findings

Analysis of Earning Per Share of Public and Private Insurance Companies

Earnings per share are company's net profit divided by the number of common shares it has outstanding. EPS indicates how much money a company makes for each share of its stock and is a widely used metric for estimating corporate value.

Table 1: Descriptive Statistics of Earnings Per Share of the Companies

Name of the CompaniesMeanStd.DeviationSkewnessKurtosis
Aegon Life Insurance Company Ltd.-.3346.3012.1088-.9635
Aviva Life Insurance Co India Ltd-.37241.1534-2.15924.1977
Bajaj Allianz Life Insurance Company Limited54.044526.0823-.99421.5515
Bharti Axa Life Insurance Company Ltd.-1.57231.9466-1.84482.7037
Birla Sun Life Insurance Co. Ltd..64201.9484-1.47471.7579
Exide Life Insurance Company Ltd.-.0971.8340-1.42481.1088
Future Generali India Life Insurance Company Ltd.-.8388.9055-2.09235.1431
HDFC Life Insurance Co Ltd.2.44612.9515-.5842-.7860
ICICI Prudential Life Insurance Company Ltd.7.90925.3985-1.86053.2130
IDBI Federal Life Insurance Co Ltd.-.05301.5733-.4488-1.2606
Kotak Mahindra Life Insurance Company Ltd.4.49252.8217.4915.1844
Life Insurance Corporation of India726.4843905.39621.2240-.5494
Max Life Insurance Company Ltd.1.85871.7616-1.25072.1190
PNB Met Life India Insurance Co Ltd..2975.21381.47511.1006
Reliance Nippon Life Insurance Company Ltd.-.40013.5446-1.62293.7845
Sahara India Life Insurance Company Ltd..7256.6913-1.0210.8072
SBI Life Insurance Company Ltd.6.95233.9337-.2359-.1739
Shriram Life Insurance Company Ltd.2.56332.2020-.4138-1.0977
Star Union Dai-ichi Life Insurance Co Ltd..23881.9156.9859-.3358
TATA AIA Life Insurance Co Ltd..26361.7221-1.53392.1059

Source: Self Calculation by Author

A higher EPS indicates greater value because investors will pay more for a company's shares if they think company has higher profits relative to its share price. Hence we take this variable in our analysis as it reflects better performance efficiency of companies.

From analysis done in Table - 1, we have observed that top 3 companies (Life Insurance Corporation of India Ltd., Bajaj Allianz Life Insurance Company and ICICI Prudential Life Insurance Company) having high earning per share.


Table 2: Analysis of Variance of Earnings Per Share of the Companies

Sum of SquaresMean SquareFSig.
2009Between Groups1038349.468519174.7343.3980.059
Within Groups2444364.268152772.767
Total3482713.736
2010Between Groups1262276.600631138.3003.3690.060
Within Groups2997438.573187339.911
Total4259715.173
2011Between Groups1544530.999772265.5003.5870.050
Within Groups3660157.989215303.411
Total5204688.988
2012Between Groups4292.4272146.2142.0700.157
Within Groups17624.6721036.745
Total21917.099
2013Between Groups5165.2082582.6042.2570.135
Within Groups19453.0391144.296
Total24618.247
2014Between Groups7056.5243528.2622.7880.090
Within Groups21510.1091265.301
Total28566.633
2015Between Groups8812.4204406.2103.1070.071
Within Groups24107.4011418.082
Total32919.821
2016Between Groups17341.4598670.7303.3600.059
Within Groups43872.6602580.745
Total61214.119
2017Between Groups13607.1656803.5833.3490 .059
Within Groups34539.5412031.738
Total48146.706
2018Between Groups16676.6428338.3213.5440.050
Within Groups39999.7022352.924
Total56676.344
2019Between Groups18356.5799178.2892.1630.161
Within Groups46670.3674242.761
Total65026.946

Source: Self Calculation by Author

Table - 2 shows that ANOVA is significant for the year 2011 and 2018 hence we should go for post hoc test and homogeneity of variance test for these two years only to see where exactly the difference lies.

Table 3: Post Hoc Test of Earnings Per Share of the Companies

Dependent VariableMean DifferenceStd. ErrorSig.
2011Public Sector LICIOld Private Sector LIC781.49305.450.05
New Private Sector LIC773.5320.20.07
Old Private Sector LICPublic Sector LIC-781.49305.450.05
New Private Sector LIC-7.98228.671
New Private Sector LICPublic Sector LIC-773.5320.20.07
Old Private Sector LIC7.98228.671
2018Public Sector LICIOld Private Sector LIC82.6322671*31.930.05
New Private Sector LIC77.7833.470.08
Old Private Sector LICPublic Sector LIC-82.6322671*31.930.05
New Private Sector LIC-4.8523.90.98
New Private Sector LICPublic Sector LIC-77.7833.470.08
Old Private Sector LIC4.8523.90.98

Source: Self Calculation by Author

Table - 3 shows that in the year2011 and 2018, mean of earnings per share of Public Sector LICI is greater than the Private Sector LIC which is statistically significant at 5% level of Significance. For the year except 2011and 2018 the mean difference of earnings per share of above 3 groups are not statistically significant.

Analysis of Insurance premium of Public and Private Insurance

Insurance premiums are paid for policies that cover healthcare, auto, home and life insurance. Once earned, premium is income for insurance company. It also represents a liability, as insurer must provide coverage for claims being made against policy.


Table 4: Descriptive Statistics of Insurance Premium of the Companies

CompaniesMeanStd.DeviationSkewnessKurtosis
Ageon life412.55167.413-1.5881.952
Aviva1853.27440.654-0.074-1.654
Bajaj Allianz7822.452030.4750.647-0.9
Bharti Axa1057.36498.630.8580.358
Aditya Birla Sunlife5603.64760.4321.483.935
Canara HSBC1868.18858.6140.020.859
DHFL Pramerica664687.8180.878-0.626
Edelweiss Tokio291.73280.2161.2851.332
Exide Life1995.27442.6070.9070
Future General698.55271.7830.1142.041
HDFC14418.187242.6050.890.191
ICICI Prudential Life18598.095907.6221.1840.539
IDBI Federal1060514.460.517-0.762
India First1647.45937.68-0.314-0.442
Kotak Mahindra3956.361889.9261.5021.304
Max Life8189.453302.9260.736-0.195
PNB Met Life2876.91821.281.5351.984
Reliance Nippon4855.27960.4151.1960.08
Sahara184.2750.09-0.397-0.899
SBI life156947733.7531.3511.299
Sri Ram Life898.73409.3121.004-0.116
Star Union Dai-ichi1139.36545.006-0.4420.56
Tata AIA3358.821123.41.432.62
LIC241618.257791.2510.399-0.929

Source: Self Calculation by Author

From the analysis (Table - 4), we have seen that top 3 companies (Life Insurance Corporation Ltd, ICICI Prudential Life Insurance Company and SBI Life Insurance Company) having the highest collection of Insurance premium.

Table: 5 shows that ANOVA is insignificant for the above analysis hence we don’t go through with post hoc test.

Table 5: Analysis of Variance of Insurance Premium of the Companies

Sum of SquaresdfMean SquareFSig.
2009Between Groups5.7E+09228499285653.4210.052
Within Groups1.75E+1021833175603
Total2.32E+1023
2010Between Groups7.79E+09238950871473.3270.056
Within Groups2.458E+10211170621442
Total3.237E+1023
2011Between Groups9.318E+09246590156883.3330.055
Within Groups2.935E+10211397836730
Total3.867E+1023
2012Between Groups9.014E+09245072407583.220.06
Within Groups2.94E+10211399878383
Total3.841E+1023
2013Between Groups9.6E+09247999821983.2350.06
Within Groups3.116E+10211483663804
Total4.076E+1023
2014Between Groups1.221E+10261040572743.1730.063
Within Groups4.04E+10211923940925
Total5.261E+1023
2015Between Groups1.263E+10263141333963.2230.06
Within Groups4.114E+10211958948573
Total5.377E+1023
2016Between Groups1.583E+10279174142153.2820.057
Within Groups5.065E+10212412052469
Total6.649E+1023
2017Between Groups2.018E+102100878161853.2890.057
Within Groups6.442E+10213067534498
Total8.459E+1023
2018Between Groups2.286E+102114311181953.3370.055
Within Groups7.194E+10213425851607
Total9.481E+1023
2019Between Groups2.58E+102129014835193.3530.054
Within Groups8.079E+10213847200146
Total1.066E+1123

Source: Self Calculation by Author


Analysis of Commission of Public and Private Insurance

Table 6: Descriptive Statistic of Commission of the Companies

CompaniesMeanStd.DeviationSkewnessKurtosis
Ageon15430998690.0650.482-0.403
Aviva10458211128181.92.5427.265
Bajaj34959352485181.81.7543.125
Bharti Axa861325536851.140.903-0.305
Birla Sunlife33026061045767.70.734-0.835
Canara HSBC1123952686849.490.536-1.427
DLF Paramerica318424239565.271.2720.935
Edelweiss254996253866.81.0970.546
Future Generali800627682692.362.2675.654
HDFC77587123202299.21.3331.108
ICICI87009324067639.11.112-0.731
IDBI810044187220.79-0.479-0.105
ING1435958251650.371.086-0.12
India First574457441605.291.2130.405
Kotak25425061492663.70.805-0.836
Max New York75000341991914.5-0.132-1.207
Met Life1781782732214.420.396-1.045
Reliance31201321507917.81.0730.483
Sahara India12641579043.980.295-1.831
SBI life84038963721268.51.2960.625
Shriram655913272037.350.706-0.859
Star Union939270450529.680.157-1.829
Tata AIA28008062194968.11.5171.94
Life Insurance1.6E+08266905780.491-0.249

Source: Self Calculation by Author

The analysis done in Table – 6 shows that the top 3 companies having the highest Commission are Life Insurance Corporation of India ltd., Bajaj Allianz Life Insurance Company and Birla Sun life Insurance Company.

Table 7: Analysis of Variance of Commission of the Companies

Sum of SquaresdfMean SquareFSig.
2009Between Groups3.091E+1521.546E+153.0820.050
Within Groups1.053E+16215.014E+14
Total1.362E+1623
2010Between Groups3.652E+1521.826E+152.9740.073
Within Groups1.289E+16216.139E+14
Total1.654E+1623
2011Between Groups4.051E+1522.025E+152.9520.074
Within Groups1.441E+16216.861E+14
Total1.846E+1623
2012Between Groups4.487E+1522.244E+152.9480.074
Within Groups1.598E+16217.61E+14
Total2.047E+1623
2013Between Groups5.826E+1522.913E+153.0020.071
Within Groups2.038E+16219.703E+14
Total2.62E+1623
2014Between Groups4.79E+1522.395E+153.0290.07
Within Groups1.661E+16217.907E+14
Total2.14E+1623
2015Between Groups5.014E+1522.507E+153.0280.07
Within Groups1.739E+16218.28E+14
Total2.24E+1623
2016Between Groups5.841E+1522.92E+153.0720.068
Within Groups1.996E+16219.506E+14
Total2.58E+1623
2017Between Groups7.158E+1523.579E+153.1360.064
Within Groups2.397E+16211.141E+15
Total3.113E+1623
2018Between Groups8.103E+1524.052E+153.1820.062
Within Groups2.674E+16211.273E+15
Total3.484E+1623
2019Between Groups9.736E+1524.868E+153.2240.050
Within Groups3.171E+16211.51E+15
Total4.145E+1623

Source: Self Calculation by Author

The analysis done in Table – 7 shows that ANOVA is significant for the year 2009 and 2019 hence we should go for post hoc test and homogeneity of variance test for these two years only to see where exactly the difference lies.


Table 8: Post Hoc Test of Commission of the Companies

Dependent VariableMean Difference (I- J)Std. ErrorSig.
2009Public Sector Holding LICIOld Private Sector30573263.85132478750.077
New Private Sector30330823.15132478750.079
Old Private SectorPublic Sector Holding LIC-30573263.85132478750.077
New Private Sector-242440.7100144521
New Private SectorPublic Sector Holding LIC-30330823.15132478750.079
Old Private Sector242440.7100144521
2019Public Sector Holding LICIOld Private Sector53625045.95229898550.073
New Private Sector54443564.15229898550.068
Old Private SectorPublic Sector Holding LIC-53625045.95229898550.073
New Private Sector818518.2173786970.999
New Private SectorPublic Sector Holding LIC-54443564.15229898550.068
Old Private Sector-818518.2173786970.999

Source: Self Calculation by Author

Table - 8 shows that in the year 2009 and 2019 Public Sector LICI has more commission than Old Private Sector LIC which is statistically significant at 5% level of significance. For the year except 2009 and 2019 the commission of above 3 groups is not statistically significant.

Analysis of Return on Capital Employed of Public and Private Insurance

The analysis done in Table - 9 shows the top 3 companies which have highest are Return on Capital Employed are Life Insurance Corporation of India Ltd., ICICI Prudential Life Insurance Company and Bajaj Allianz Life Insurance Company.

Table 9: Descriptive Statistics of Return on Capital Employed of the Companies

CompaniesMeanStd.DeviationSkewnessKurtosis
Aegon Life Insurance Company Ltd.-3.32713.031490.133-0.748
Aviva Life Insurance Co India Ltd-19.22453.3365-2.0863.443
Bajaj Allianz Life Insurance Company
Limited
23.115423.15750.596-0.624
Bharti Axa Life Insurance Company Ltd.-369.57691.036-2.6677.276
Birla Sun Life Insurance Co. Ltd.-4.147470.4813-1.8272.754
Canara HSBC9.9158969.5471-1.2863.574
DHFL Pramerica5.3178541.7410.4965.124
Edelweiss Tokyo-0.604532.3240.3214.254
Exide Life Insurance Company Ltd.-47.095117.012-2.294.928
Future Generali India Life Insurance Company Ltd.-111.02127.383-1.2670.415
HDFC Life Insurance Co Ltd.10.213242.0335-1.5311.312
ICICI Prudential Life Insurance CompanyLtd.24.705535.7345-2.7398.335
IDBI Federal Life Insurance Co Ltd.-4.482825.974-0.527-1.324
India First-0.648724.5470.2360.514
Kotak Mahindra Life Insurance Company Ltd.22.64438.371220.1071.98
Life Insurance Corporation of India341.6460.24810.661-1.052
Max Life Insurance Company Ltd.14.594723.3631-2.5827.1
PNB Met Life India Insurance Co Ltd.9.9158915.47552.7518.045
Reliance Nippon Life Insurance Company
Ltd.
-28.84100.386-2.4676.857
Sahara India Life Insurance Company Ltd.5.317856.81801-0.5220.856
SBI Life Insurance Company Ltd.20.70128.50034-2.3266.64
Shriram Life Insurance Company Ltd.11.733911.6978-0.6390.522
Star Union Dai-ichi Life Insurance Co Ltd.-0.604512.80580.396-1.263
TATA AIA Life Insurance Co Ltd.-12.23773.6431-1.832.413

Source: Self Calculation by Author


Table 10: Analysis of Variance of Return on Capital Employed of the Companies

Sum of SquaresdfMean SquareFSig.
2009Between Groups472787.982236393.990.8730.435
Within Groups4601659.617270685.86
Total5074447.619
2010Between Groups180035.58290017.7911.7740.20
Within Groups862440.171750731.775
Total1042475.719
2011Between Groups95266.168247633.0843.3970.057
Within Groups238375.911714022.112
Total333642.0819
2012Between Groups42500.528221250.2644.3680.029
Within Groups82699.112174864.654
Total125199.6419
2013Between Groups26081.121213040.563.8160.043
Within Groups58096.243173417.426
Total84177.36419
2014Between Groups34335.394217167.6973.7580.045
Within Groups77653.641174567.861
Total111989.0319
2015Between Groups33001.282216500.6413.5690.051
Within Groups78586.312174622.724
Total111587.619
2016Between Groups61946.344230973.1723.9720.038
Within Groups132567.69177798.099
Total194514.0319
2017Between Groups45328.998222664.4993.9610.039
Within Groups97282.38175722.493
Total142611.3819
2018Between Groups50502.196225251.0984.0690.036
Within Groups105487.31176205.136
Total155989.5119
2019Between Groups42658.235221329.1172.3690.126
Within Groups144070.42169004.401
Total186728.6618

Source: Self Calculation by Author

Table - 10 exhibits that ANOVA is significant for the years 2012, 2013, 2014, 2016, 2017and 2018. Hence we should go for post hoc test and homogeneity of variance test for those years only to see where exactly the difference lies.


Table 11: Post Hoc Test of Return on Capital Employed of the Companies

Dependent VariableMean Difference (I-J)Std. ErrorSig.
2012Public Sector LICIOld Private Sector70.72806845.9131420.298
New Private Sector136.8901575*48.130050.029
Old Private SectorPublic Sector LIC-70.72806845.9131420.298
New Private Sector66.1620934.3717310.162
New Private SectorPublic Sector LIC-136.8901575*48.130050.029
Old Private Sector-66.1620934.3717310.162
2013Public Sector LICIOld Private Sector74.07930738.4822640.162
New Private Sector111.2870521*40.3403740.034
Old Private SectorPublic Sector LIC-74.07930738.4822640.162
New Private Sector37.20774528.8087890.419
New Private SectorPublic Sector LIC-111.2870521*40.3403740.034
Old Private Sector-37.20774528.8087890.419
2014Public Sector LICIOld Private Sector90.51463744.4905220.134
New Private Sector127.8582816*46.6387390.035
Old Private SectorPublic Sector LIC-90.51463744.4905220.134
New Private Sector37.34364433.3067220.515
New Private SectorPublic Sector LIC-127.8582816*46.6387390.035
Old Private Sector-37.34364433.3067220.515
2016Public SectorOld Private Sector145.5932458.1306830.056
LICINew Private Sector165.5072258*60.9375140.037
Old Private SectorPublic Sector LIC-145.5932458.1306830.056
New Private Sector19.91398943.518090.892
New Private SectorPublic Sector LIC-165.5072258*60.9375140.037
Old Private Sector-19.91398943.518090.892
2017Public Sector LICIOld Private Sector122.010949.7970570.063
New Private Sector142.9679290*52.20150.035
Old Private SectorPublic Sector LIC-122.010949.7970570.063
New Private Sector20.95703437.2793280.842
New Private SectorPublic Sector LIC-142.9679290*52.20150.035
Old Private Sector-20.95703437.2793280.842
2018Public Sector LICIOld Private Sector131.0079451.8545290.054
New Private Sector149.7092220*54.3583170.034
Old Private SectorPublic Sector LIC-131.0079451.8545290.054
New Private Sector18.70128438.8196030.881
New Private SectorPublic Sector LIC-149.7092220*54.3583170.034
Old Private Sector-18.70128438.8196030.881

Source: Self Calculation by Author


Table - 11 exhibits that in the year 2012, 2013, 2014, 2016, 2017 and 2018 Public Sector LICI has more Return on Capital Employed than Old Private Sector LIC which is statistically significant at 5% level of significance. For the year except 2012, 2013, 2016, 2017 and 2018 the Return on Capital Employed of above 3 groups are not statistically significant.

Conclusion

  • In the year 2011 and 2018, mean of earnings per share of Public Sector LIC is greater than the Private Sector LIC, which is statistically significant at 5% level of Significance.
  • From the analysis (Table 1), we have observed that top 3 companies (Life Insurance Corporation of India Ltd., Bajaj Allianz Life Insurance Company and ICICI Prudential Life Insurance Company) having the highest earnings per
  • From the analysis (Table - 4), we have seen that top 3 companies (Life Insurance Corporation Ltd, ICICI Prudential Life Insurance Company and SBI Life Insurance Company) having the highest collection of Insurance premium.
  • The analysis (Table - 6) shows that the top 3 companies having the highest Commission are Life Insurance Corporation of India ltd., Bajaj Allianz Life Insurance Company and Birla Sun life Insurance Company.
  • In the year 2009-2010 and 2019-2020 Public Sector LICI has more commission than Old Private Sector LIC which is statistically significant at 5% level of significance. For the year except 2009-2010 and 2019-2020 the commission of above 3 groups is not statistically significant.
  • The analysis (Table - 9) shows the top 3 companies which have highest are Return on Capital Employed are Life Insurance Corporation of India Ltd., ICICI Prudential Life Insurance Company and Bajaj Allianz Life Insurance
  • In the year 2012, 2013, 2014, 2016, 2017 and 2018, Public Sector LICI has more return on capital employed than Old Private Sector LICI which is statistically significant at 5% level of For the year except 2012, 2013, 2016, 2017 and 2018, the return on capital employed of above 3 groups are not statistically significant.

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