A STUDY OF THE DETERMINANTS OF THE LEVEL OF REGULATORY COMPLIANCE OF INDIAN NON-LIFE INSURERS
Keywords:
IRDA, Regulatory compliance, non life insurers, Non-life Insurance Regulatory Compliance Index (NLIRCI)Abstract
Compliance with the law framed by the Insurance Regulatory and Development Authority of India is necessary to ensure an orderly conduct of insurance business within the country, alongwith, protection of the interests of the policyholder. But inspite of warnings issued and action taken by the Regulator, many cases of non compliance have been observed by non-life insurers. As such cases of non-compliance defeat the real purpose of regulation and prevent in achieving the desired goals of transparency, solvency and protection, the study attempts to analyse the factors that determine the level of regulatory compliance of Indian non-life insurers. The sample for the study includes all the 28 non life insurers operating in the country. Using multi regression model, the study measured the influence of company size, return on assets, solvency and liquidity on the compliance level of Indian non-life insurers for a period of 11 years from 2005-06 to 2015-16. The results showed that while solvency and return on assets had no influence on compliance level, company size and liquidity had a negative influence on the compliance level of Indian non life insurance companies.
References
‘A STUDY OF THE DETERMINANTS OF THE LEVEL OF REGULATORY COMPLIANCE OF INDIAN NON-LIFE INSURERS.’
by
Dr. Martina R. Noronha
and
Smeeta N. Khawani
Asst. Professor of Commerce and Accountancy
Sascma English Medium Commerce College
Near Lal Bhai Contractor Stadium, Opposite Govardhan Haveli, Dumas Road, Surat.
Mobile : 9879503730
Abstract
Compliance with the law framed by the Insurance Regulatory and Development Authority of India is necessary to ensure an orderly conduct of insurance business within the country, alongwith, protection of the interests of the policyholder. But inspite of warnings issued and action taken by the Regulator, many cases of non compliance have been observed by non-life insurers. As such cases of non-compliance defeat the real purpose of regulation and prevent in achieving the desired goals of transparency, solvency and protection, the study attempts to analyse the factors that determine the level of regulatory compliance of Indian non-life insurers. The sample for the study includes all the 28 non life insurers operating in the country. Using multi regression model, the study measured the influence of company size, return on assets, solvency and liquidity on the compliance level of Indian non-life insurers for a period of 11 years from 2005-06 to 2015-16. The results showed that while solvency and return on assets had no influence on compliance level, company size and liquidity had a negative influence on the compliance level of Indian non life insurance companies.
Keywords : IRDA, Regulatory compliance, non life insurers, Non-life Insurance Regulatory Compliance Index (NLIRCI)
Introduction
For the healthy growth of any economy, it is essential that its financial system, including the insurance sector, functions in a manner which not only fuels growth, but which ensures financial protection and stability. While playing the role of risk management and risk minimization, it is necessary that the insurance sector functions in an orderly manner, without prejudice to the interests of its stakeholders. Hence to achieve the above objectives, the insurance sector, which was earlier controlled and regulated by the Government, was opened for private players and foreign investors (subject to a maximum holding of 26%) and IRDA was appointed as its Regulatory body in the year 2000. Since its establishment, IRDA has issued several rules, regulations and guidelines for ensuring proper functioning of the insurance sector. The regulatory framework so designed, relates to almost all matters that concern the business of the insurer, some of which include processing of proposal form, claim settlement, grievance disposal, maintainance of proper books of accounts and required solvency margins, investment norms and compulsory public disclosures.
It has been more than 15 years since the establishment of IRDA and during this period, the insurance sector has undergone significant reforms. While there have been many positive developments, many cases of non compliance have also been observed against the insurers. IRDA, in exercise of its powers, has issued several warnings and levied penalties on such non compliant companies. With the passing of the Insurance Amendment Act 2015, IRDA has taken such matters of non compliance more seriously, and according to the new amendments, permission will be accorded for matters such as raising capital from the market and setting up new place of business, only after the Regulatory body is satisfied about the compliance level of the insurer. Thus, compliance with the law has now become mandatory, affecting the future business prospects of the insurer. Further, compliance with rural and social sector obligations by insurance companies is in national interest as it will ultimately help improve the level of insurance density and insurance penetration in the country. Hence the study attempted to analyze the factors which determine compliance. The study measured the impact of four independent variables namely size, return on assets, liquidity and solvency on the compliance level of non life insurers.
Literature Review
Klumpes, P. J. (1997) conducted a study regarding the propensity of Australian life insurers to voluntarily use jointly-developed Australian and New Zealand Life Insurance Accounting Standards (LIAS). Such propensity of life insurers was predicted to be related to the firm’s tax rate, ownership structure, size, expense ratio and solvency. Using evidence from earlier studies, it was hypothesized that firms with relatively high expense ratios and reporting higher income tax adopted AIS for eliminating the information asymmetry about their ability to generate economic income. Further, from the ownership point of view, the study hypothesized that high value share-owned life insurance firms, having access to equity markets, had more incentive to use AIS (to distinguish themselves from other firms) than high value mutual firms, who had no such access. Also, low value life insurance firms, closer to violating their minimum net worth requirements and which would therefore prefer a tax minimising policy, were hypothesized to be IAS non-users. The results of the study confirmed the hypothesis and proved that the voluntary use of AIS was done to reduce the level of information asymmetry faced by life insurance firms in reporting their profitability and to improve their informativeness.
Dumontier, P., & Raffournier, B. (1998) conducted a study using eight determinants (listing status, internationality, size, ownership structure, leverage, capital intensity, profitability and auditor’s reputation) to identify the motivations of Swiss listed companies, which voluntary complied with International Accounting Standards, though such compliance meant additional disclosures and renunciation of considerable discretion in accounting practices. The study showed a positive influence of size, internationality, listing status, auditor type and ownership diffusion on voluntary compliance, but no significant relationship was found for leverage, profitability and capital intensity. Importantly, the findings suggested that it was political costs and pressures from outside markets that prompted companies to apply IAS and not simply, to solve monitoring problems between shareholders, managers and creditors.
Malik H. (2011) conducted a study on 35 listed life and non-life insurance companies of Pakistan for the period of 2005-2009, for investigating the determinants of profitability. It examined the effects of firm specific factors (age of company, size of company, volume of capital, leverage ratio and loss ratio) on profitability proxied by ROA. Though the results showed an absence of relationship between profitability and age, a significant positive relationship was observed between profitability and two variables namely, size of the company and volume of capital. Loss ratio and leverage ratio indicated a significant negative relationship with profitability. Charumathi B. (2012) conducted a similar study to model the factors that determined profitability of life insurers operating in India. Using linear multiple regression model, the author found that profitability was positively and significantly influenced by size and liquidity, whereas it had an inverse relationship with leverage, premium growth and logarithm of equity capital. There was no evidence of any relationship between underwriting risk and profitability. Similar findings were observed in a study of 18 Indian life insurers from 2007-08 to 2011-12 by Bawa S.K. and Chattha S. (2013), except that profitability was found to have no relationship with solvency and insurance leverage.
Methodology
Data Collection : The data collected for the study is secondary in nature. It has been collected from the IRDA database. The compliance information for each variable was derived by studying the annual reports of companies.
Sample Selection
As the study was related to non life (general)insurance, all the twenty eight non life insurers operating in India as on 31-3-2016 were selected for the purpose of the study.
Time period of Analysis
The study covered a period of 11 years from 2005-06 to 2015-16 for measuring the level of regulatory compliance by Indian non life insurers. The reason for choosing this period was that IRDA made public disclosures mandatory for non life insurers during 2010. Also, there was a mandatory requirement to disclose annual data for the prior period of 5 years, starting from 2005-06 to 2009-10. Due to non availability of compliance data from 2000-01 to 2004-05, the study was confined to the period from 2005-06 to 2015-16.
Objectives of Study
To study the determinants of the level of regulatory compliance of Indian non life insurers.
Data Processing and Analysis Plan
To measure the level of regulatory compliance of non life insurance companies, an original, comprehensive, unweighted index called the Non-life Insurance Regulatory Compliance Index( NLIRCI) was constructed in the study, after studying the IRDA rules and regulations. Depending upon their relatedness, they were then divided into six groups/indices. The six groups identified were Obligation Fulfillment Index (OFI), Stakeholders Protection Index (SPI), Public Disclosure Index (PDI), Financial Stability Index (FSI), Investment Guidelines Index (IGI) and Other Guidelines Index (OGI). Thus the Non-life Insurance Regulatory Compliance Index (NLIRCI) was derived as under :
NLIRCI=OFI + SPI + PDI + FSI + IGI + OGI
Each such index consists of several variables. Each variable has dichotomous value i.e. yes or no. Every insurer scores 1 point for compliance and 0 point for non compliance/partial compliance/if the company was not in existence during that year. For other variables which were not dichotomous in nature (i.e. grievance disposal and claim settlement), the actual level of compliance was measured using the exact ratios and the ratios were converted into points in terms of 1. The following table shows the six sub-indices of NLIRCI, with their variables.
Table 1
Table showing the six sub-indices of NLIRCI and its variables
Sub indices Variables Score Total Score
Obligation Fulfillment Index(OFI)
Payment of Annual Fee 1 4
Rural obligation 1
Social obligation 1
Declined Risk Pool 1
Stakeholders Protection Index(SPI)
Advertisements and Disclosures 1 14
Processing of Proposal Forms 1
Free Look Period 1
Manner of Receipt of Premium 1
Prohibition of Rebates 1
Claims Settlement 1
Grievance Disposal 1
Maintenance of Policy & Claim Records 1
Individual agents 1
Corporate Agents 1
Brokers 1
Banks as Insurance brokers 1
Referral Partners 1
Others: 1
Third Party Administrators
Surveyors & Loss Assessors
Web Aggregators
Public Disclosure Index(PDI)
Actuarial Attribute 1 6
Investment Attribute 1
Corporate Governance Attribute 1
Policyholder’s Attribute 1
Financial Attribute 1
Insurance Agent Attribute 1
Financial Stability Index(FSI)
Accounting Practices 1 4
Solvency Margin 1
Expenses of Management 1
Prohibition of Loan 1
Investment Guidelines Index(IGI) 1) Central govt. Security 1 5
CG, SG & other Security 1
Approved Investment 1
Other than Approved Investment 1
Housing and Infrastructure 1
Other Guidelines Index(OGI) 1) Requirement as to Capital 1 11
Issuance of further Capital 1
Provision of documents during Investigation 1
Opening of New Place of Business 1
File and Use Procedure 1
Anti Money Laundering 1
Reinsurance 1
Micro-Insurance 1
Group Insurance 1
Insurance Repository 1
Reporting of Key persons 1
Non-Life Insurance Regulatory Compliance Index (NLIRCI) 44
Equal weightage was given to each sub indice. Finally the Non-Life Insurance Regulatory Compliance Index (NLIRCI) score was arrived at by totaling the scores of all sub indices, and it was then converted into percentage terms.
The following table shows the compliance level of non-life insurers for a period of 11 years from 2005-06 to 2015-16.
Table 2
Level of Regulatory Compliance of Non-Life Insurers using the Non-Life Insurance Regulatory Compliance Index (NLIRCI)
No. Names 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16
National 99 96 93 98 99 86 96 99 97 99 99
New India 95 91 92 92 85 84 95 95 98 99 99
United India 99 99 97 98 95 84 72 99 92 99 99
Oriental 99 99 97 99 99 87 99 95 99 99 99
ECGC 99 99 99 99 98 99 98 99 99 98 99
AICI 99 98 99 99 99 94 81 98 98 98 99
Royal Sundaram 99 99 99 99 99 99 90 71 99 99 99
Reliance 99 99 98 99 99 95 95 91 95 99 99
IFFCO Tokio 100 99 92 99 99 87 99 96 99 99 100
Tata AIG 100 95 99 99 99 99 100 95 100 100 99
Bajaj Allianz 99 99 99 98 99 81 99 99 98 99 98
ICICI 100 99 97 96 94 77 99 95 84 99 99
Cholamandalam 100 98 97 96 90 71 100 95 99 99 99
HDFC ERGO 100 99 95 99 100 99 99 95 99 99 99
Star Health NE 99 99 100 100 100 100 100 100 100 100
Apollo Munich NE NE 98 91 91 89 100 100 100 100 100
Future Generali NE NE 98 99 100 99 98 94 74 99 99
Universal Sompo NE NE 98 98 99 99 99 90 99 99 99
Shriram NE NE NE 99 100 100 100 98 99 99 99
Bharti AXA NE NE NE 98 92 100 100 95 99 99 100
Raheja QBE NE NE NE 98 98 98 98 98 76 98 98
SBI NE NE NE NE 98 98 99 95 99 99 99
Max Bupa NE NE NE NE 98 98 100 100 100 100 100
L&T NE NE NE NE NE 98 99 95 76 99 99
Religare Health NE NE NE NE NE NE NE 99 100 100 100
Liberty Videocon NE NE NE NE NE NE NE 98 99 100 99
Magma HDI NE NE NE NE NE NE NE 98 99 99 99
Cigna TTK NE NE NE NE NE NE NE NE 98 99 99
N 14 15 18 21 23 24 24 27 28 28 28
Mean
07
86
76
96
45
66
5
10 99.14
Std. Dev. 1.27 2.26 2.4 2.3 3.95 8.46 6.69 5.6 7.8 0.57 0.52
Note : (1) Computed on the basis of disclosures by companies and from IRDA database. (2) NE means Not in Existence.
To study the determinants of regulatory compliance of Indian non life insurers using four predictors namely Company size, return on assets, liquidity and solvency, the following hypothesis was tested :
Ho: There is no influence of company size, return on assets, liquidity and solvency on the level of overall regulatory compliance(using NLIRCI)
H1 : There is an influence of company size, return on assets, liquidity and solvency on the level of overall regulatory compliance(using NLIRCI)
The dependent variable for the hypotheses was the compliance score of the insurer obtained using NLIRCI (Non Life Insurance Regulatory Compliance Index) and the independent variables were company size, return on assets, liquidity and solvency. Company Size was measured as the sum of total admitted assets of the insurer. Return on assets was taken as Profit before interest and tax/ admitted assets. Liquidity was measured as Outstanding Claims/ Cash and Bank balance. Solvency was measured as the ratio between available solvency margin and required solvency margin of the insurer.
Findings
The following results were obtained :
Table 3 : Regression Results
Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson
.270a .073 .058 5.05184 1.614
Results computed using SPSS
ANOVAb
Model Sum of Squares Df Mean Square F Sig.
Regression 489.740 4 122.435 4.797 .001a
Residual 6227.136 244 25.521
Total 6716.876 248
Results computed using SPSS
Regression Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients T Sig. Collinearity Statistics
B Std. Error Beta Tolerance VIF
(Constant) 98.221 .626 156.790 .000
SIZE -6.833E-9 .000 -.137 -2.177 .030 .966 1.036
ROA -.080 .057 -.091 -1.402 .162 .908 1.101
LIQUIDITY -.196 .055 -.225 -3.557 .000 .946 1.057
SOLVENCY .070 .134 .034 .522 .602 .912 1.097
Results computed using SPSS
The R-square value was found to be 7.3 % and Adjusted R-square value was 5.8 %. This means that the present model is able to explain 5.8 % variance in NLIRCI. The p- value is 0.001 which means the model is significant and we reject the null hypothesis at 5% level of significance. The p-value of the independent variables, company size and liquidity is 0.03 and 0.00 respectively, hence we fail to accept the null hypothesis and conclude that there is a significant influence of company size and liquidity on NLIRCI. The p value of the independent variables namely return on assets and solvency is 0.162 and 0.602 respectively and so we accept the null hypothesis that there is no significant influence of return on assets and solvency on NLIRCI. Thus, the influence of company size and liquidity on NLIRCI can be explained by the following regression equation :
NLIRCI = 98.221 – 6.833(company size) - 0.196 (liquidity) + ei
Test for Heteroskedasticity, Multicollinearity and Autocorrelation :
To meet the assumption of homogeneity of variance of residuals, the regression model was tested for heteroskedasticity. The residual mean of zero indicated that there was no problem of heteroskedasticity. Another assumption of Ordinary Least Square regression is that there should be no auto correlation in the error terms. Autocorrelation is measured by Durbin Watson Statistic. The Durbin Watson value of 1.614 indicated that there was no problem of autocorrelation. Also, for the proper functioning of the regression model, it was necessary to ensure that one independent variable did not affect the value of other independent variable and there was no problem of multicollinearity. Multicollinearity is measured by variance inflationary factor(VIF). As the VIF value in the regression result was less than 5, no such problem existed.
Conclusion
Under the supervisory guidance of IRDA, the insurance sector has marked significant growth. Earlier there were only a few state run insurers to meet the insurance needs of a vast growing economy, but now the number of registered insurers has increased to 59 (including the national reinsurer GIC). Also, insurance penetration and density has improved. Through the issue of various Regulations, Rules, Guidelines and Circulars, IRDA has ensured that the insurance companies do not act in a way which is detrimental to the interests of the policyholders’ and the public faith in the institution of insurance is reposed. The results of the study show that the two independent variables, Return on assets and solvency have no influence on the level of regulatory compliance, whereas company size and liquidity have a negative influence on the level of compliance. This indicates that as company size increases, it becomes difficult for non-life insurers to ensure overall compliance. Similarly, as a company settles its claim liabilities, its liquidity decreases, though its compliance level increases.
References
I. Bawa, S. K., and Chattha, S. (2013) Financial Performance of Life Insurers in Indian Insurance Industry. Pacific Business Review International 6(5), 44-52. Retrieved from http://www.pbr.co.in/November2013/7.pdf
II. Dumontier, P., & Raffournier, B. (1998). Why firms comply voluntarily with IAS: An empirical analysis with Swiss data. Journal of International Financial Management and Accounting, 9(3), 216-245. Retrieved from
a. http://onlinelibrary.wiley.com/doi/10.1111/1467-646X.00038/abstract
III. Charumathi B. (2012). On the Determinants of Profitability of Indian Life Insurers – An Empirical Study. Proceedings of the World Congress on Engineering, London, U.K. Retrieved from
a. http://www.iaeng.org/publication/WCE2012/WCE2012_pp505-510.pdf
IV. Malik, H. (2011). Determinants Of Insurance Companies Profitability: An Analysis of Insurance Sector Of Pakistan. Academic Research International, 1(3), 315-321. Available at
a. http://www.savap.org.pk/journals/ARInt./Vol.1(3)/2011(1.3-32)stop.pdf
V. Klumpes, P. J. M. (1997). Determinants of voluntary accounting policy choices by Australian life insurers. Working Paper 1997/001. The Department of Accounting and Finance, Lancaster University Management School. Retrieved from http://eprints.lancs.ac.uk/48566/1/Document.pdf
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