A Critical Study on Financial Performance of Insurance Industry In India

Existence of entry barriers for new insurance companies meant that competition was restricted to existing public insurers. In case of life segment of insurance, Life Insurance Corporation of India (LIC) had a dominant role, while in non-life business segment, New India, United India, National and Oriental General Insurance Corporations were having monopoly. These companies were operating as cartel, even in areas where the freedom to price their products existed. With the liberalisation of insurance sector, the paradigm for Indian insurance industry has witnessed a sea change during the last decade. The emerging scenario has infused greater competitive volatility in the system, because the insurance sector has now entered into a competitive phase due to entry of more players in the insurance field. As a result there has been expansion and growth of insurance both in the life and non-life business. Hence, the larger cake is now being shared by the existing and new players. Further industry will become more professional and lowering the entry barriers and growing sophistication of customers will make insurance market oligopolistic. It is generally believed that insurance industry will never be same again and turbulent times are ahead for insurers. Therefore, paradigm for regulatory framework for future will have to be one in which insurance companies and other entities are motivated so that they give improved performance and at the same time be sensitive to the needs of their policy holders. Hence regulations should not be water tight compartments but should be flexible. Any regulation issued today should have enough scope for change with growth and maturity of the insurance market. In this context, the Insurance Regulatory and Development Authority Bill (IRDA) which was approved by both houses of parliament in December, 1999 paved the way for opening of insurance sector to private players in the country. The IRDA which was statutorily constituted on April 19, 2000 quickly organized itself to accomplish its primary task of maintaining and developing efficient, fair, safe and stable insurance market for the benefit and protection of policyholders. The authority has so far adopted a clear, transparent and consistent regulatory and supervisory process, which has brought credit to the nation and has received accolade from the International Association of Insurance Supervision

OBJECTIVES OF THE STUDY

The specific objectives of this study are: 1. To analyse the financial performance of public and private sector non-life insurers on the basis of CARAMEL parameters. 2. To make comparative statistical analysis of public and private non-life insurance companies. 3. To gauge the impact of liberalisation on the financial performance of insurance industry in India. 4. To examine impact of liberalisation on security analysis of state owned and private sector companies in the light of ISI standards. 5. To examine impact of various factors on the solvency of non-life insurers.

Beenstock et al., (1998) and Outreville studied by considering property-liability premium, but ignored other parts of insurance industry (such as long term insurance, motor insurance and etc). On other hand, Ward and Zurbruegg (2000) use aggregate variable of total insurance premium in their study. Although Ward and Zurbruegg (2000) acknowledged Brown and Kim (1993) suggestion that total premium fail to account for different market forces in various countries and make comparisons difficult and fail for account for regulatory effects on pricing, but availability of data for longer period was stated as a reason for using total premium. In addition authors claimed: “If one views the key economic benefits of insurance as risk transfer, indemnification and financial intermediation, then the benefits of risk transfer and indemnification are likely to be the major characteristics of non-life and health insurance, while financial intermediation is a part of life insurance. Thus an aggregate approach will embrace all of these ideas within the same analysis.” (Ward and Zurbruegg, 2000) Although this interpretation seems correct and logical, but some studies which have been conducted in the economic literature about aggregation problem show it may cause unreliable results. An example of aggregation is cross-sectional aggregation which occurs when a number of micro variables are aggregated to get a macro variable (Maddala and Kim, 1998). Granger, (1990) showed it is possible to have co-integration at the aggregate level and not at the disaggregate level and vice versa. If it is true, one might accept finding of Ward and Zurbruegg (2000) about no long run relationship between economic growth and insurance market size in countries like Austria, Switzerland, United Kingdom and the United States. Ward and Zurbruegg (2000) note that insurance further supports the functioning of the market expensive items, such as cars, by offering risk transfer and indemnification services to risk averse individuals. This encourages such individuals to make purchases that they would not otherwise have made. Thus insurance provides positive externalities in terms of increased purchases, profits and employment both within and alongside the insurance sector. In addition, insurance facilitates innovation within an economy by offering to underwrite new risks. According to Swiss Re (2004) important factors that determine the growth of the insurance business are the distribution of wealth, legal systems and property rights, the availability of insurance products, regulation and supervision, trust and risk awareness. Other non- insurance. For non-life; regulation (e.g., compulsory insurance), claim awards, exposure to natural disasters, and the public sector’s role in health. For life; economic stability e.g., inflation, exchange rate, demography, the tax system, the savings rate, and the pension system.

RESEARCH METHODOLOGY:

Sample Size The study has covered non-life insurance business establishments from both from public and private sector. The public sector companies include United India Insurance, National Insurance Company, Oriental Insurance and New India Insurance Company. The private sector companies include Royal Sundaram, Bajaj Allianz, IFFCO Tokio, ICICI Lombard, Tata AIG, Reliance, Cholamandalam and HDFC Ergo insurance companies. The selection was for the whole non-life sector companies registered; however, as the study was going on various other players joined the sector but could not be taken due to lack of data as the study span is of five years after liberalization.

MATERIALS AND METHODS

In the study both primary and secondary data has been used. The collection of primary information has been done through personal investigation method. Secondary data constitutes the main source of information, suitable for the purpose of present research work. The sources of secondary data were Annual Reports of the companies and IRDA, Directors and Auditors report, IRDA Journals, Asia Insurance Post, The Insurance Times, Journal of Insurance Institute of India, Insurance Chronicle (ICFAI), Daily papers and government reports relating to the issues under study. Experts in the field were also approached for the purpose of discussion to understand the problem in right perspective. The work of academicians on the subject has also been consulted for the purpose analysis. The performance of insurance companies can be measured by a number of indicators. However, in present study, CARAMEL parameters are used to study the financial performance of insurance companies. For measuring the performance of insurance companies on the basis of CARAMEL parameters, the present study employs ratio analysis with the following methodology: A. The description of CARAMEL acronym and ratios calculated to test each acronym are:  Capital Adequacy: Capital Adequacy can be viewed as the key indicator of an insurer’s financial soundness. Capital is seen as a cushion to protect insured and promote the stability and efficiency of

calculation of capital adequacy of companies under study, two ratios have been used, prescribed by IMF and World Bank (IMF, 2005). First is the ratio of Net Premium to Capital and second ratio is Capital to Total Assets.

• Asset Quality: Asset quality is one of the most critical areas in determining the overall financial health of an insurance company. The primary factor effecting overall asset quality is the quality of the real estate investment and the credit administration program. Ratio of equities to total assets and ratio of Real Estate + Unquoted Equities + Debtors to Total Assets has been used, prescribed by IMF and World Bank.

• Reinsurance and Actuarial Issues: Reinsurance and Actuarial issue ratios reflect the overall underwriting strategy of the insurer and depict the proportion of risk retained and passed on to the reinsurers and indicates the risk bearing capacity of the country’s insurance sector. IMF prescribes two ratios in this standard viz. ratio of Net Premium to Gross Premium and ratio of Net Technical Reserves/ Average of Net Claims paid in last three years.

• Management efficiency: The ratio reflects the efficiency in operations, which ultimately indicates the management efficiency and soundness. The indicator prescribed is Operating Expenses to Gross Premiums.

• Earnings and Profitability: IMF prescribes five sub dimensions to this standard to limelight the earnings and profitability of the insurance companies. The standard is two tier, covering both operational and non-operational efficiency of the insurance companies.

STATISTICAL ANALYSIS:

In addition to the ratio analysis, the CARAMEL parameters have been tested statistically with the help of following statistical tools: Mean Standard Deviation and variance F-Test Regression Analysis (Growth Model). In order to have a comprehensive view, the growth of each ratio covered by CARAMEL is calculated by Annual Compound Growth Rate (ACGR) Method for the last five years. The Annual Compound Growth Y= abt Where, Y= dependent variables (Capital Adequacy, Asset quality, etc), a = Constant, b= Slope of trend lines (Growth Rate), t= time. Estimate of b (slope of trend line or rate of change) has been arrived as follows: b^ = log (1+g). In this equation g (growth rate) has been obtained by taking antilogarithm of log (1+g) and subtracting 1 from the same. The resultant value would be multiplied by 100 to express growth rate in percentage terms. The significance of the difference between the performances of the Insurers is verified with the help of F-test. The F-ratio is calculated as: F= (CESS-MESS)/2(q-1) MESS/ (n-2q) Where q = number of insurers, N = total number of observations (no of insurers x no of time series observations for each ratio) CESS = Combined sum of squared errors when both the insurers and their observations are used to estimate the regression equation above (for each ratio); MESS = sum of the two insurers sums of squared errors for each insurer estimated from the regression applied to each insurer (each ratio) separately. 2(q – 1) = Numerator degrees of freedom

LIMITATION OF THE STUDY

The study has the following limitations: 1. The study aimed at impact of liberalization on financial performance of non-life insurance sector and has concentrated mainly on what European Union called first generation reforms in insurance sector. As the study proceeded the IRDA introduced a second generation reform that is price deregulation in the non-life sector, except motor third party. Although its impact was witnessed on the profitability and other key functional areas and simultaneously were discussed briefly, however, keeping in view the second generation reforms various unexplored areas emerged which will pave way for further scope for research in the area of insurance sector. 2. The other key areas include the issues, fading away presence of public insurers, solvency norm II, have not been discussed in detail in the study.

REFERENCES

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