Insurance Regulatory Information System – Definition

Cite this article as:"Insurance Regulatory Information System – Definition," in The Business Professor, updated March 19, 2019, last accessed October 20, 2020,


Insurance Regulatory Information System (IRIS) Definition

The Insurance Regulatory Information System (IRIS)  is a system containing databases and tools to analyze the financial statements of different insurance companies. It is primarily used by the National Association of Insurance Commissioners (NAIC) to determine the credibility of insurance companies.

The Insurance Regulatory Information System (IRIS)  is an electronic system designed to provide financial analysis for insurance companies and give reliable data on how well a company is able to meet its long-term financial obligations. IRIS is run by the National Association of Insurance Commissioners (NAIC). NAIC uses the database and tools of IRIS to weight an insurance company’s financial solvency.

A Little More on What is the Insurance Regulatory Information System

IRIS was established in 1972 and the National Association of Insurance Commissioners, NAIC has been at the helm of its affairs. A company’s ability to continue operations in the future is paramount to NAIC and for a company to last through the age, it must have the capability to attend to all financial needs. Hence, NAIC uses that database provided by IRIS to check a company’s present financial status and the likelihood to maintain the status in the nearest future or otherwise.

IRIS does not only help NAIC manage and examine insurance companies but also serve as a problem detector for the companies. That is, if IRIS notices financial challenges with a company, this is not just for NAIC to regulate the company but to also avail the company a chance to look into the financial problems and make amends.

There are defined ratios that an insurer or company must meet before it can be said to be fit for business. IRIS determine these defined ratios and point out insurance companies that are considered acceptable and those that need more examination by NAIC.

The financial ratios as calculated by IRIS are used to generate a report and categorize insurance companies on how well they have met the financial ratios. However, companies that fall short of the acceptable financial ratios are not left unattended to, rather, the are closely examined and regulated by NAIC.

Although, through the categorization, IRIS places the companies at a competitive leve andl at the same time identifies that some companies may be below the expected range due to the economic difficulties and financial in the countries in which they operate.

Hence, with IRIS at NAIC’s disposal, the examination, evaluation, regulation and monitoring of insurance companies have become easier as IRIS provide detailed information about all the insurance companies which may not even be found in the database of the states in which they operate.

References for the Insurance Regulatory Information System

Academic Research on the Insurance Regulatory Information System

  • Optimistic reporting in the property-casualty insurance industry, Petroni, K. R. (1992). Journal of Accounting and Economics, 15(4), 485-508. Property loss occur through diverse means such as fire accidents, damage and other unforeseen cases, it is however the duty of managers to respond the claims of losses. This paper focuses on how property-casualty insurance managers attend to these cases accordingly. A good knowledge of diverse property casualty insurance and their impacts will help the manager in giving response to the liability for outstanding claim losses. Although, there are laid down processes to be followed in cases like this, it is possible that the insurer or insurance company tone down the incentive for liability due to financial status. This paper further empirically examine how weak companies or insurers with low financial status underrate the claims of losses and this also reflect in how the insurers down tone these claims of losses to avoid regulatory actions form the regulatory agency. Therefore, this paper shows the interplay between the response of insurers and the financial status of the insurer.
  • Risk-based capital and solvency screening in property-liability insurance: hypotheses and empirical tests, Grace, M. F., Harrington, S. E., & Klein, R. W. (1998). Journal of Risk and Insurance, 213-243. This paper uses hypothesis and empirical test in examining the financial solvency and screening of insurance companies. Since financial solvency is a major criterion used in classifying whether an insurer is weak or strong, it is noteworthy to examine the efficacy of this financial screening. The hypothesis and empirical test questions the correctness of classifying insurance companies into either being weak or strong. This paper identifies that there is a chance of categorizing a strong insurer as a weak one and vice versa and this is regarded as Type I error. This paper however prescribes two effective methods to screen companies for financial solvency which are RBC and FAST. RBC means Risk-Based Capital while FAST refers to Financial Analysis Tracking System. These two screening methods are designed by NAIC and the hypothesis proffers them as better tools in screening insurers for financial solvency. However, while evaluating these screening methods, there is a level of inconsistency between the hypothesis and the empirical test. While the hypothesis posits that the RBC measures as much as FAST does in the identification of financially weak insurers, empirical result shows that FAST takes the lead in determining financially weak solvent insurers as RBC is regarded as less powerful in identifying financially weak property-liability insurers. Therefore, in order to have a more accurate analysis of financial solvency of insurers, both RBC and FAST must be jointly put to use. This will be a joint formidable screening method to combat financial insolvency.
  • Regulatory solvency prediction in property-liability insurance: Risk-based capital, audit ratios, and cash flow simulation, Cummins, J. D., Grace, M. F., & Phillips, R. D. (1999). Journal of Risk and Insurance, 417-458. This article draws a comparison between a seemingly new method for screening solvency and the existing models used by the US insurance regulators to screen solvency in the property-liability insurance industry. Cash flow simulation which is the new method was analysed and juxtaposed with the the RBC and FAST method as used by NAIC in 1994. The analysis however shows that both the RBC and FAST systems are rigid in nature because they are both ratio-based approaches to test solvency or insolvency in the property-liability insurance industry. However, contrary to the static nature of RBC and FAST, cash flow simulation presents a better and realistic approach to testing solvency. Logistic regression analysis is a strategy introduced by cash flow simulation and this strategy relies of logistic data and facts of previous years to determine the probability of future insolvency of an insurance company or otherwise.  The article therefore shows that the use of logistic regression analysis method will yield better and efficient results than the RBC and FACT ratio-based models.
  • Reinsurance and the management of regulatory ratios and taxes in the property—Casualty insurance industry, Adiel, R. (1996). Journal of Accounting and Economics, 22(1-3), 207-240. This paper studies and investigates how insurance companies use reinsurance to manage regulatory decisions and taxes in properties. Reinsurance may seem to be a complex term, but simply put, reinsurance refers an insurance bought by another insurance company. This is a method that insurers use in a bid to remain solvent and to also manage risk properly. Reinsurance also boost that earnings of the reinsurer. Many insurance companies embrace reinsurance as a credible method to harness financial support and gain financial stamina. Although, there are different categories of reinsurance, financial insurance is one that does not pose any threat of risk to the reinsurer. Two different analyses were conducted to know the rationale behind companies opting for reinsurance. These analyses are univariate analysis and a multiple regression. While one analysis shows that insurers engage reinsurance to reduce regulatory impacts, the other shows that the purpose of reinsurance is to cut down marginal tax rates.
  • The NAIC information system and the use of economic indicators in predicting insolvencies, Hershbarger, R. A., & Miller, R. K. (1986). The Journal of Insurance Issues and Practices, 9(2), 21-43. Despite that the issue of an insurance company’s solvency still remains priority to insurance industry regulatory bodies, insurer executives, and the people, there remains a desire for insurance policies to remain unshakeable. In the 1970’s the National Association of Insurance Commissioners (NAIC) devised new methods in solving the issue of solvency or insolvency of an insurer. The new approach required that state insurance departments and regulatory bodies offer a closer financial surveillance and supervision to the insurance companies. This approach will protect the interest of the public and as well monitor the solvency or insolvency of an insurer.
  • Insurance regulation in transition, Klein, R. W. (1995). Journal of Risk and Insurance, 363-404.In the 1980s, there was a huge record of insurance companies’ failure which affected a lot of people and this raised a concern on the ineffectiveness of the state regulatory bodies to put insurers in check. This article however highlights the drastic change in insurance policies and regulations as well as new regulatory reforms of insurers following the their failure in the 1980s. The failure of insurers and state regulatory bodies cost the society a lot as it raised severe problems. This incident therefore caused a reform in the regulatory framework for insurance companies. The new policies and regulations placed heavy demands of regulatory bodies to harness an enviable financial standards of insurers and also make proper use of monitoring tools at their disposal. A proper use of monitoring tools will the boost and expand finances of insurers and also cause a new insurance departments to emerge as part of the regulation.
  • Evaluating solvency versus efficiency performance and different forms of organization and marketing in US property––liability insurance companies, Brockett, P. L., Cooper, W. W., Golden, L. L., Rousseau, J. J., & Wang, Y. (2004). European Journal of Operational Research, 154(2), 492-514. The evaluation of solvency is crucial to the regulators US property-liability insurance companies as this aids the evaluation of the performance of the insurers. This unflinching need to evaluate solvency by regulators is hinged on some cogent factors. While regulatory bodies focused on solvency evaluation, policyholders concerned themselves with claims paying abilities of insurance companies. Investors also pay attention to what they stand to gain on their investments. Hence, the performance or efficiency of insurers is rated based on solvency results. How well an insurer gives return on investment, the claims paying ability of the insurer, and its overral financial strength are yardsticks used for solvency examination and efficiency evaluation.
  • A regression-based methodology for solvency surveillance in the property-liability insurance industry, Harrington, S. E., & Nelson, J. M. (1986). Journal of Risk and Insurance, 583-605. This paper carefully presents a practicable method for the assessment of property-liability financial strength of insurance companies. This method entails that an estimation will be carried out using regression analysis. Regression analysis will provide an insurer’s financial solvency for previous years which will serve as an insight to the expected performance of the insurer in the future. This paper suggests that regression analysis will be more effective than the Insurance Regulatory Information System IRIS, formulated by NAIC. As an improvement on the shortcomings of IRIS, regression analysis can be used to identify insurers with ratios that are substantially higher as compared to those with similar characteristics. This method requires the use of data as evidence to identify solvent and insolvent insurers.

Was this article helpful?