The Role of Insurance in Achieving the National Goals of Sustainable Development of Uzbekistan

The Republic of Uzbekistan, a signatory to the UN General Assembly Resolution on the Sustainable Development Goals, is taking practical measures to align its national Sustainable Development Goals (SDGs) with the global SDGs. In particular, according to Resolution of the Cabinet of Ministers №841 dated by October 20, 2018, the Road Map for organizing the implementation of National Goals and Objectives in the field of sustainable development for the period until 2030 was approved (Decree of the Cabinet of Ministers of the Republic of Uzbekistan, 2018).
These goals and targets were revised in the new version of the national SDG program, adopted by the Resolution of the Cabinet of Ministers №83 dated by February 21, 2022 “On Additional Measures to Accelerate the Implementation of National Goals and Tasks in the Field of Sustainable Development for the Period until 2030” (Resolution of the Cabinet of Ministers of the Republic of Uzbekistan, 2018). The national SDGs have 16 goals, 126 targets and 190 indicators.
In the Development Strategy of new Uzbekistan for 2022 – 2026, developed taking into account the Sustainable Development Goals, the following 7 priority areas for reforms are identified, aimed at further improving the people’s well-being, transforming economic sectors, accelerating the entrepreneurship development, ensuring human rights and interests, and the formation of an active civil society (Decree of the President of the Republic of Uzbekistan, 2022). building a humane state by elevation of the person honor and dignity and further developing a free civil society (corresponds to SDG-1, SDG-2, SDG-3, SDG-4, SDG-5, SDG-10. SDG-16);

• turning the justice principles and the rule of law into a fundamental and necessary condition for the country’s development (SDG-8, SDG-10, SDG-16, SDG-17);
• accelerated development of the national economy and ensuring high growth rates (SDG-1, SDG-2, SDG-8, SDG-9, SDG-11);
• implementation of fair social policies, development of human capital (SDG-1, SDG-2, SDG-3, SDG-4, SDG-5, SDG-8. SDG-10; SDG 13, SDG-16, SDG 17);
• ensuring spiritual development and raising this sphere to a new level (SDG-1, SDG-2, SDG-3, SDG-4, SDG-5, SDG-8);
• approaching global problems based on national interests (SDG-6, SDG-8, SDG-9, SDG-11, SDG-12, SDG-13. SDG-15; SDG-17);
• strengthening the security and defense potential of the country, maintaining open, pragmatic and active foreign policy (SDG-8, SDG-17).

According to the UNDP Rapid Integrated Assessment (RIA) conducted in October 2022 based on the assessment of 22 planning documents of the Republic of Uzbekistan, the level of alignment of global SDGs with national strategic development planning in Uzbekistan is currently at 79% (United Nations Development Programme, 2022). Full compliance is observed with Goals 1 (Poverty), Goal 2 (Hunger), Goal 3 (Health), Goal 5 (Gender), in which all global targets are reflected in assessed policy planning of the country. The least integration is found to be in Goal 10 – 50% (Inequalities between and within countries), Goal 13 – 60% (Climate change) and Goal 17 – 68% (Partnerships).

Achieving the national Sustainable Development Goals requires mobilization of a wide range of resources from the Government of the Republic of Uzbekistan and the private sector. According to the IMF, spending on national SDGs related to education, health and infrastructure amounts to 8.7% of GDP (International Monetary Fund, 2024).

According to UNDP estimates, the Government of the Republic of Uzbekistan currently allocates about 72% of the state budget for activities related to achieving the SDGs (United Nations Development Programme, 2024).

In November 2020, the Republic of Uzbekistan issued Eurobonds with a three-year, 14.5% 2 trillion Soums tranche, being the equivalent of approximately 200 million US Dollars. The proceeds from the transaction are anticipated to be used to implement national SDGs. These projects are mainly aimed at creating decent working conditions (SDG 8), ensuring economic growth and gender equality (SDG -5, SDG – 8), as well as increasing the infrastructure sustainability (SDG – 16). According to the report, the major share of the proceeds was spent on the construction and reconstruction of highways and roads (50%), loans to women entrepreneurs (18%), construction and reconstruction of schools (16%) (United Nations Development Ptogramme, 2024).

Figure 5.1. Overall alignment of key development planning documents with Global SDGs and Agenda 2030 profile in Uzbekistan

Source: United Nations Development Programme, n.d.

Also, in July 2021, Uzbekistan issued sovereign bonds for sustainable development goals in the amount of 235 million US Dollars with a maturity of 3 years. It was stated that the proceeds from the placement of these new bonds will be used to finance government projects in the following areas: education, health (SDG – 3); (SDG – 4); water resources management (SDG – 6); healthcare (SDG – 3); green energy (SDG – 7); development of environmentally friendly transport (SDG – 9; SDG – 11); combating environmental pollution (SDG – 11); natural resource management (SDG-13; SDG – 15).

We live in an era with higher frequency and scale of natural and man-made disasters. Over the past five years, insurance claims from natural disasters have increased several times. Moreover, natural disasters caused by climate change lead in damage. According to Swiss Re reinsurance company, losses from natural disasters in 2021 amounted to 270 billion US Dollars (Sigma, 2022).

The COVID-19 pandemic has shown its danger to the global economy. Its appearance in China at the end of 2019 led to global trade disruption, scale of production reduction, and change in existing consumption and management models. Subsequent logistics restrictions between countries further reduced global economic activity. Also, ongoing trade conflicts between countries and the introduction of international sanctions against individual countries have led to changes in the existing supply chains of goods and services. This, in turn, contributes to the destruction of the existing world trade system and leads to decline in the production factors mobility.

The global economy sustainability requires timely responses to these dangerous challenges which are global in nature and have a negative impact on international trade. The economic turmoil occurring throughout the world caused by climate change, sanctions wars, and the coronavirus pandemic require a thorough analysis of the scale of their consequences in order to determine the most rational solutions.

Insurance, as the main risk management method, is an essential element of the system for mitigating the consequences of the above-mentioned challenges. UN Framework Convention on Climate Change and the subsequent Kyoto Protocol emphasized the role of insurance in mitigating the natural disasters consequences. In the Hyogo Framework for Action (2005–2015, further development of the natural risk insurance and reinsurance mechanism was recognized as a priority measure to increase the world economy sustainability, primarily the economies of developing countries. The document states that “Sustainable development, poverty reduction, good governance and disaster risk reduction are mutually supportive objectives, and in order to meet the challenges ahead, accelerated efforts must be made to build the necessary capacities at the community and national levels to manage and reduce risk» (Hyogo Framework for Action, 2024.). Let us note that this approach should be recognized as an important component of achieving global SDGs.

It should also be noted that the development trends of the above-mentioned challenges for the global economy (natural and man-made disasters, sanctions wars, the COVID-19 pandemic) have a direct impact on the global insurance market and affect its financial stability. At the same time, these risks influence the insurance behavior of insurance consumers and thereby expand the capabilities of the insurance industry. The share of such insurance types as insurance against environmental risks, insurance against catastrophic risks, insurance against business interruption as a result of natural and man-made risks, comprehensive medical insurance and others is growing.

Protecting people’s lives and well-being is a key component of the concept of sustainable development. In the absence of any formal protection mechanism and in risky situations, people with low incomes usually rely on informal coping mechanisms. Therefore, without an effective risk management system, including insurance mechanism with affordable insurance rates level, achieving sustainable development is impossible.

The history of the development of scientific and applied approaches to the problem of solvency and financial stability of insurance companies is widely covered in the works of a number of academic economists (Sandström, 2010; Orlanyuk-Malitskaya, 1994; Malinovsky, 1995; Lelchuk, 2013), in documents of such international organizations as the International Association of Insurance Supervisors (IAIS, 2000), International Actuarial Association (International Actuarial Association, 2004), European Insurance and Occupational Pensions Authority (EIOPA, 2009), International Monetary Fund (International Monetary Fund, n.d.) and etc.

The history of the development of scientific approaches to the insurers solvency Professor of Stockholm University A. Sandström will divide into two periods: the period of the classical approach and the period of the economic approach. (Sandström, 2010).

Under “classical period” he means the period between World War II and the 1980s. To be solvent, insurance companies were required to maintain a reasonable margin on their insurance provisions. In order to assess the insurance companies’ solvency, the classical Cramer-Lundeberg theory of ruin was used, where, at given levels of the initial provision (initial solvency margin) and the rate of incoming premiums over a certain time horizon, the probability of the company’s ruin is assessed.

According to the classical approach, the solvency base is the available mandatory and stabilization reserves which are formed gradually and serve as an additional guarantee that the insurance organization will fulfill its obligations.

The definition of solvency given by B. Benjamin gives rise to two concepts of solvency (Benjamin, n.d.).

The insurance company is solvent if it is able to meet its obligations upon immediate liquidation, or upon transferring its obligations to its partner who agrees to assume them. In some works, such solvency is called static solvency (Campagne, 1961).

A company is solvent if it fulfills its obligations to insureds as they arise (dynamic solvency).

In the work of the Finnish actuary T. Pentikainen, the solvency concept was considered from the point of view of supervisory authorities and from the point of view of insurance company management (Pentikäinen, 1967).

• protection of the financial interests of insureds must be ensured (from the point of view of supervisory authorities);
• the normal functioning of the company must be ensured (from the point of view of the company management).

The first point of view is narrower since it does not require continuous operations of the company, but allows its liquidation. According to the author, it could be approved as the basis for legal and regulatory system.

According to the second point of view, the main purpose of solvency is to ensure the continuous sustainable functioning of the insurance company, and it can be considered as the company’s own approach to establishing its own solvency level for internal control.

The Finnish solvency assessment and control system, introduced in 1953, was based on the compensation provisions calculation and projection of total annual losses. The system included standard methods for calculating technical provisions (if the standard method did not suit the company it could use its own assumptions), two capital requirements (an absolute minimum requirement for the liquidation situation and one risk-based target level for continuous operations situation). The solvency test, with detailed instructions provided by the regulator, was based on the one-year time horizon with failure probability of 1% (Kastelijn & Remmerswaal, 1986).

The Norwegian system, developed in the early 1980s, was also based on projection of total annual losses and was based on the rules for determining technical provisions and the statistical data necessary for calculations (Norberg et al., 1985).

Special mention should be made of the work of Professor K. Campagne, “Minimum Standards of Solvency for Insurance Firms” written in 1961 by order of the Insurance Committee of the Organization for European Economic Co-operation (OEEC). This work later became the theoretical basis of the Solvency I model.

Based on a study of loss statistics of insurance companies in OEEC countries for the period 1952-1957, he calculated the operating expense ratio at 42%. To calculate the loss ratio, he assumed that the loss distribution follows a beta distribution. The value at risk (VaR), calculated by using data from OEEC countries with a probability of 99.7%, was 83%. Thus, the combined loss ratio was 42% + 83% = 125%. In other words, the company will need an extra 25% of the premium over 1 year to meet its obligations to insureds. The author argued that establishing a solvency margin of 25% of premiums collected would ensure that the insurer fulfills its obligations to insureds upon occurrence of insured events (Campagne, 1961).

Figure 5.2. Campagne’s Approach to Insurance Solvency

Source: Sandström Arne, 2010, Handbook of Solvency for Actuaries and Risk Managers: Theory and Practice.

In 1963, at a conference dedicated to the creation of a single free insurance market for the OEEC countries, an algorithm was proposed for calculating the minimum solvency margin based on the following three relative values:

• the ratio of the assets amounts free from liabilities to gross premiums written for the last calendar year;
• the ratio of the assets amounts free from liabilities to the average annual amount of claims paid for the last 3 years;
• the ratio of the assets amounts free from liabilities to the technical provisions amount at the reporting date.

During the preliminary discussion of the first non-life insurance directive in the European Union (EU), it was proposed to introduce a solvency margin of 24% of gross premiums written, 34% of incurred losses and 19% of technical provisions. The last part was deleted because it was not possible to agree on how to value technical provisions.

Some countries felt that the proposed solvency margin rates were too high. These comments were taken into account and we arrived at the following calculation formula: the minimum solvency margin must be greater than the following two indexes:

Insurance premium index:

where, SM – solvency margin, GP – gross premiums, GIC_av– gross average incurred claims (for the last 3 years, 7 years for certain catastrophic risks, such as hurricane and hail) (In the terminology of the first General Insurance Directive, a “unit” was defined as “the unit defined by paragraph 4 in the Status of the Euro-Pean Investment Bank”).

The European solvency assessment system described above was based on the assessment of two or three indicators. In 1972, the US National Association of Insurance Commissioners (NAIC) introduced a multi-dimensional early warning system called the Insurance Regulatory Information System (IRIS). The system was built on the basis of a total balance sheet approach and calculations and assessments were carried out in two stages. At the first, statistical stage, 12 different ratios such as “premiums/equity capital”, “provisions/equity capital”, and etc. were calculated. The number of ratios that were outside the predetermined ranges was then determined. Companies with the largest number of ratios outside these acceptable ranges were registered as the highest priority for the second, analytical, stage. The main purpose of these procedures was to determine which companies required regulatory attention.

In 1989, the NAIC adopted a solvency control program, which led to a number of changes in solvency regulation in the United States. A new system called Financial Analysis and Supervisory Tracking (FAST) was adopted and implemented in 1993. FAST was an information system that captured nearly all of the information in IRIS and consisted of approximately 30 ratios and corresponding assessment for those ratios.

The economic approach to assessing and monitoring solvency takes into account the impact of the risks to which the insurance company is exposed. Also, the assets and liabilities of the insurance company are valued at market prices. Sandsrem believes that from the very beginning, the application of this approach followed two trends (Sandström, 2010):

• European trend based mainly on the classical theory of risk and ruin, but also on risk management methods, and;
• North American, based mainly on the scientific achievements of financial economics.
• Actuarial solvency models, described in the works of the Finnish actuary T. Pentikainen, served as a theoretical and practical basis for applying the economic approach to assessing the solvency of insurance companies. According to the author, the solvency margin should serve two purposes (Pentikäinen, 1982):
• the solvency margin should be a guarantee for insureds;
• solvency margin must be a guarantee for the long-term operations of the insurance company.

In the work, the actual solvency margin was defined as the sum of free reserves (equity capital), hidden reserves in assets (undervalued assets) and the equalizing reserve (overestimation of liabilities).

The work of the UK General Insurance Study Group (GISG), led by K. Daikin, used the results of the work of Finnish actuaries and used market valuations of the assets and liabilities of the insurance company to calculate the solvency margin and studied capital adequacy problems in close connection with technical, investment and other risks of the insurance company, for example, risks of reinsurance operations (Daykin et al., 1984).

The calculation of the actual solvency margin in the work was carried out as follows. Let SM_P be the solvency margin published (in financial or accounting statements); А_P and L_P are the assets published and liabilities published of the insurer, respectively; А_РV and L_PV are the company’s assets and liabilities projected values, respectively.

With this definition, marginal assets М_А and marginal liabilities M_L are calculated as:

M_A = A_PV – A_P ; M_L = L_P – L_PV,

The actual solvency margin was determined as:

SM_A = A_PV-L_PV = SM_P+M_A +M_L

1. Sansdrem notes that this approach of the GISG study group to assessing the solvency margin is similar to the approach within the framework of Solvency II (Sandström, 2010).

It is worth to note the work of John Trowbridge’s research group, where the value of assets and liabilities was considered as the present value of future cash flows generated by the company’s existing assets and liabilities (Trowbridge Report, 1979).

In general, the economic approach is based on the concept of risk orientation. It was within the framework of the economic approach to assessing the insurance companies’ solvency that the foundations of the current RBC (Risk-Based Capital) solvency control system in the USA were laid.

Rene Doff’s book “Risk Management for Insurers” provides a fairly successful classification of models for determining insurers solvency (Doff, 2011).

1. Reporting-based static models (simple factor models and risk tolerance models);
2. Cash flow-based dynamic models (scenario models and principles-based models).

At the international level, working groups of the International Association of Insurance Supervisors (IAIS) are working on the creation of global standards for assessing solvency and capital adequacy (IAIS ,2024 г.)

) and the International Association of Actuaries (IAA) (МАА, IAA) (Duran & Knapman, 2019) and these standards in the insurance literature are known as insurance capital standards (ICS).

At the regional level, the European Union is currently reviewing its solvency regime which came into force in 2016 under the Solvency II name.

There are a number of capital adequacy standards operating at national levels. All these initiatives at the relevant levels influenced each other to one degree or another. Given the global nature of the insurance business and the global regulations harmonization, it is important to be aware of these interactions and view these initiatives in their broader context.

Figure 5.3. The supervisory assessment of the financial position of an insurer and the public financial reporting of an insurer

Source: Developed by the author based on data from the International Association of Insurance Supervisors

One of the initial steps taken towards developing a solvency regime at the international level was the publication in 2005 of two IAIS policy documents. The first document, called the Framework Paper, provided a comprehensive framework for the supervision of insurance activities (IAIS, 2005). The document proposed a “three-pillar” supervisory approach:

• Pillar I: Minimum Financial Requirements
• Pillar II: Supervisory Control Process
• Pillar III: Measures to strengthen market discipline.

Pillar I (minimum financial requirements) consisted of requirements for:

• technical provisions formation;
• the composition and quality of assets corresponding to assumed liabilities;
• minimal capital amount.

It was noted that these requirements should comprehensively reflect the insurer’s understanding of its own risks.

Pillar II (supervisory control process) was intended not only to ensure that there was sufficient capital to cover all of an insurer’s risks, but also to encourage them to develop and use more effective risk management practices reflecting the insurer’s risk profile, and to monitor and manage those risks. The document noted that such a review would allow supervisory intervention if the insurer’s capital does not sufficiently cover risks.

Pillar III was introduced to strengthen market discipline by introducing disclosure requirements. Through these requirements, it was expected that “best practices” in the industry would be encouraged.

The second IAIS document entitled “Towards a common structure and common standards for the assessment of insurer solvency: cornerstones for the formulation of regulatory financial requirements” identified 8 key elements (or “cornerstones”) for the development of a regulatory capital standard (Towards, 2005.). The paper noted that the application of a common set of capital requirements would lead to different views of an insurer’s financial strength due to differences in the determination of the value of liabilities and assets in the accounting and financial reporting systems of different jurisdictions. These determinations may create hidden surpluses or deficits that must be properly recognized for solvency purposes.

Based on the above documents, in 2008, IAIS working groups developed standards and recommendations for

• structure of regulatory capital requirements,
• enterprise risk management for capital adequacy and solvency purposes, and
• use of internal models for regulatory purposes (IAIS, 2008).

After several updates and revisions, these standards and guidance were eventually consolidated into the Insurance Core Principles (ICP) in 2011 (IAIS, 2011).

Global financial crisis 2008-2010 accelerated the development of a more complex global solvency regime. This was partly due to the relevance of the insurance sector during the crisis. In 2013, IAIS announced its plan to develop a global risk-based capital standard by 2016 (IAIS, 2016).

The IAIS project to create international capital standard ICS was first published for review in December 2014 (IAIS, 2014). Since then, a series of quantitative field tests have been conducted and various versions of the ICS projects have been published for reference. The latest version of ICS was released in November 2019 as “Level 1. Document: ICS Version 2.0 for monitoring period” (IAIS, 2019). As the name suggests, ICS Version 2.0 is used for the purpose of confidential reporting for the entire group of supervisory authorities over a five-year monitoring period from 2020 to 2024 (IAIS, 2019b). During this period, only explanations, clarifications and corrections of identified serious deficiencies and/or unintended consequences can be made. The IAIS has announced that the ICS will be adopted as a PCR (prescribed capital requirement) in the fourth quarter of 2024, but no implementation information has yet been provided to the public.

Much attention is paid to the capital requirements of insurers in the current solvency system of the European Union countries Solvency II, the main goal of which is to create a unified system for regulating capital adequacy and ensuring compliance with risk management standards (Solvency II Overview, 2022).

Solvency II is based on principles. The solvency assessment is carried out not on the basis of fixed ratios but on the basis of analysis of the insurance company’s own risks.

Solvency II includes qualitative and quantitative standards. According to them, the amount of equity capital of the insurance company must cover the amount of expected losses during the year with a probability of 0.995.

According to Solvency II, the capital requirement consists of two parts:

• minimum capital requirements (MCR);
• risk capital (solvency capital requirements, SCR).

The share of MCR in SCR must be at least 25% and no more than 45% (Directive 2009/138/ec, 2009).

0.25∗ 𝑆𝐶𝑅≤𝑀𝐶𝑅≤ 0.45∗ 𝑆𝐶𝑅.

According to the standard Solvency II formula, SCR can be calculated using the formula:

SCR =BSCR + Adj + SCRo_r

where BSCR is the basic solvency capital requirement; Adj – adjustment of technical provisions to absorb losses; SCRor – operation risk.

The Solvency II ratio reflects the ratio of the insurer’s equity capital to the SCR risk capital:

The risk margin establishes technical provisions in the amount of the expected amount required to fulfill insurance obligations. According to Article 37 of the Solvency II delegated regulation, the risk margin is calculated using the following formula (Commission Delegated Regulation (EU), 2015):

where T is the valid period of insurance obligations, CoC rate is the cost of capital rate; r – risk-free rate.

Figure 5.4. Capital requirement under Solvency II

Source: Valuation of non-life technical provisions under Solvency II.

The Solvency II regime provides for internal financial modeling based on the processing of a large volume of statistical information on risks accepted for insurance in order to determine capital adequacy. The modeling results can be useful in making business decisions on further development of insurance activities.

An analysis of existing solvency and capital adequacy standards at the level of individual jurisdictions shows that many models are, to one degree or another, focused on the concept of risk-based capital (RBC), developed and approved by the National Association of Insurance Commissioners (NAIC) in the USA.

The NAIC adopted the Model Risk-Based Capital Act for Insurers in 1993, which has become a key tool for monitoring the solvency of US insurers (Risk-based Capital (RBC), 2012).

Risk-based capital (RBC) is a statutory minimum capital level that depends on two factors: the size of the insurance company and the risk profile of the insurer. That is, the company must retain capital in proportion to its risk.

The RBC is intended to serve as a regulatory standard and to set the total capital amount the insurer must have to achieve its objectives.

In accordance with the RBC guidelines established by the NAIC, the so-called Authorized Control Level (ACL) is calculated. The ACL is calculated taking into account the risk profile of the insurer, the premiums volume, investments and other features of the insurer’s activities.

The following RBC levels are defined:

• If the company’s RBC falls below 200% of the ACL the company management must submit a plan to increase RBC levels.
• If the company’s RBC falls below 150% of the ACL the company is considered to have a Regulatory Action Level RBC, and the regulator can issue order prescribing the company to take specific actions to increase its RBC level.
• If the company’s RBC falls to the ACL level, the regulator has the right at his own discretion to force the company to rehabilitation or liquidation;
• If the company’s RBC falls below 70% of the ACL, then the company is considered to have a Mandatory Control Level RBC and is subject to mandatory rehabilitation or liquidation by the regulatory authority.

It is notable that the results of calculating capital at risk are used for various purposes. For example, the results of the capital at risk calculation are used to determine the minimum capital requirement (MCR).

The results of calculating capital at risk are also used in financial planning of the insurer’s activities. The purpose of calculating capital at risk in the context of financial management is to determine the optimal level of capital and its efficient allocation.

Nowadays, the solvency assessment and control system based on RBC is also used with slight modifications in various countries, such as Canada, Australia, Hong Kong, Japan, and etc. (Sankaranarayanan, 2024). In Uzbekistan, in accordance with the Regulations on the solvency of insurers and reinsurers, developed and approved in 2008, the basis of solvency is the presence of a formed authorized capital, sufficient insurance provisions, as well as the reinsurance system (Order of the Minister of Finance of the Republic of Uzbekistan, 2008).

The experience of countries whose system of assessing and monitoring solvency is based on RBC shows that the introduction of RBC into the national system of regulation of the insurance market requires large (labor, intellectual and financial) costs and these costs increase the cost of insurance services. Over time, these costs will be transferred to insurance services consumers – insureds. In addition, the RBC Solvency Assessment and Control System contains a set of regulatory measures that apply when the insurer’s equity falls below the minimum capital requirement (MCR). It can be argued that “this level of detail creates undue rigidity in the regulatory process” (Dickinson, 1997).

Factors of Financial Stability of Domestic Insurers

Pricing of insurance services takes significant place in the activities of insurance companies, since economically justified tariff rates are guarantees for ensuring their financial stability and solvency along with the formed insurance provisions, own funds, and use of reinsurance mechanism. This is understandable: if high prices lead to some clients leaving for other insurers, then low prices in case of unfavorable situations may not ensure that the insurer fulfills its obligations to insureds in case of insured events.

Issues of pricing insurance services related to insurance coverage of socio-economic projects being implemented today in the Republic of Uzbekistan put in new requirements to insurers. This is also explained by the fact that the insurance services tariffication is directly related to the problems of ensuring the financial stability and solvency of insurance companies. According to research by AM Best rating agency, conducted on the basis of data from insurance companies in the USA and Canada for the period 1969-2010, the main reasons for the bankruptcy of insurance companies were insufficient loss provisions (in 34% of cases) and the rapid growth (in 22% of cases) of these companies (Ackerman Sh. et all, 2010). It must be noted that both of these reasons are mainly the results of inadequate pricing.

The calculation of tariff rates in insurance is based on estimates of the insurance operations costs also taking into account the regulatory, financial and economic environment of insurance. According to marketers J. Gard and O. Eyal, approximately 75% of American insurers determine the insurance services cost based on risk costs (Cost-oriented pricing), 15% of insurers are guided by competitors’ prices (Competitive pricing) (A pricing method in which a seller or service provider sets a price based on competitors’ prices.), and 10% of insurers determine the insurance services price based on clients (Customer-oriented pricing) (Gard, J.-C. and O. Eyal , 2012). The insurance premium structure calculated on the basis of cost-oriented pricing analysis is presented in Figure 5.5.

In this insurance premium representation, the expected net premium is the value corresponding to the average claims payments for the insurance portfolio. In the actuarial literature regarding the expected net premium, the term “net premium” is also used and if statistics on loss ratio are available, it is calculated using the formula (Lelchuk, 2014):

Net Premium = Claim Frequency * Average Claim Value

The risk premium is additional payment for risk and is intended to provide insurance indemnities in case of loss ratio upward deviations and to reduce the insolvency risk of the insurance company. Its inclusion into the premium structure is also due to the fact that during tariffication there are two risk sources: stochastic and technical.

Stochastic risk is associated with the probabilistic insurance nature and it is assessed using probabilistic and statistical methods. Technical risk is related to inaccurate assessment of parameters used for tariffication. In relation to a fundamental equation, we can talk about the parameters used to evaluate its component parts. Typical examples: inaccurate assessment of the loss amount due to the fact that at the assessment date not all losses had been settled; inaccurate estimates of losses and costs inflation. Russian actuary A.L. Lelchuk believes that it is technical (he calls it parametric) and not stochastic risk that leads to the most serious problems.

The loading is intended to cover the costs of carrying out insurance, including loss adjustment, operational, administrative and other expenses. In addition, the loading may include the planned underwriting profit of the insurer. The inclusion of the planned profit in the insurance premium is due to the fact that, by selling insurance policies, the insurer assumes the risk that insurance premiums will not cover its costs, i.e. claims payments and expenses. If the insurance provisions formed from received premiums are insufficient, the insurer is forced to use its own capital. To cover the cost of this capital, insurers include profit load into the premium. At the same time, the founders (shareholders) of the insurance company expect profits at least exceeding profitability of diversified shares package or investments into reliable investment company.

Figure 5.5. Premium structure under cost-of-risk pricing
(Source: Kudryavtsev, 2011)

Typically, regulatory restrictions on insurance rates include (but are not limited to) the following requirements:

1. rates must not be excessive or inadequate and must not be unfairly discriminatory
2. the pricing process should be built taking into account the actual loss ratio for a number of consecutive reporting periods, assessment of the likelihood of catastrophic insurance events and reasonable rate of return on capital.

Regulatory restrictions of this type have a dual purpose. First, the first requirements group protects insurance consumers from unfair pricing schemes. Secondly, the second requirements are intended to ensure the applicability of the tariff system. They protect insurance companies from unfair government prices that do not provide a “reasonable rate of return on capital.” Without the expectation of such returns, private companies will not invest their capital or will be forced to become insolvent as their capital is depleted in unfavorable market situations. The right to a reasonable return on capital has a positive impact on the company’s performance, increases its solvency and, thus, protects consumers that their company will be able to fulfill its financial obligations to them in case of insured events.

In the US Society of Casualty Actuaries Basic Textbook (Casualty Actuarial Society) insurance premium calculation is carried out (Werner et al., 2016):

Premium = losses + loss adjustment expenses + underwriting expenses + underwriting profit

It must be noted that the basis for insurance premium assessment is often not the sum insured but the exposure unit. Under the concept of Risk Exposure lies the insurance premiums assessment. In their rate manuals, insurance companies typically set a base premium rate for the unit of risk accepted for a particular insurance line. The insurance premium basic size is calculated as the product of the basic tariff rate and the risk exposure value. For example, in auto insurance, machine-years are most often used as a unit of risk exposure, i.e. one car insured for one year. If a company insures its cars in the amount of 10 cars for a period of six months, then the risk exposure under this agreement will be 5 machine-years.

The insurance pricing process, which in the insurance and actuarial literature is called ratemaking (tariffication (French)) is based not on strict rules, but on principles and standards. For example, in the USA, these principles were developed and adopted by the Society of Casualty Actuaries in 1988 and formulated in the document “Approval of Principles for Setting Rates in Property and Casualty Insurance” (Statement of Principles Regarding Property and Casualty Insurance Ratemaking, 2021).

In accordance with this document, tariffs are based on the following principles:

Principle 1. Tariff rate is an estimate of expected future expenses. In order to ensure the sustainability of insurance activities, all expenses must be taken into account when calculating tariff rates.

Principle 2: The rate covers all costs associated with the risk transfer. When setting rates, individual risk transfer costs should be included to maintain fairness among insureds. When the individual risk statistics do not provide reliable basis for estimating those costs, it is appropriate to consider the aggregate statistics of similar risks. The rate calculated using this approach is an estimate of the cost of risk transfer for each insured.

Principle 3. The rate provides for the costs associated with the individual risk transfer.

It must be noted that tariff rates established according to principles 1-3 meet four criteria: rationality, accessibility, adequacy and non-deprivation.

The nature of the insurer’s actions within the underwriting cycle (Figure 5.6.) can be described using the following diagram:

Stage 1. The insurer has specific target rates to achieve certain corporate goals, such as target return on equity (ROE).

Stage 2. These target tariff rates are adjusted to the tariff rates of competing companies in the market.

Stage 3. The established tariff rates will determine the underwriting result for the reporting period. The underwriting result will be influenced by the actual loss ratio, which is a random (stochastic) variable and is not fully controlled by the insurer.

Stage 4. Analysis of financial (accounting) statements for the reporting period, assessment of solvency.

Stage 5. Analysis of the company’s position in the market.

Stage 6. Decision making based on the results of 3-5 stages (capitalization, decapitalization, exit from the market, and etc.).

Figure 5.6. Underwriting cycle

Source: Azimov R., 2023, “Innovative development of the insurance market in the Republic of Uzbekistan”

When studying insurance pricing, it is also necessary to pay attention to the fact that it is not an isolated function and interacts with such corporate functions as:

• business planning function, which is responsible for setting goals reflecting the company’s strategy and develops guidelines and parameters for making ratemaking decisions.
• underwriting function, which makes decision on whether or not to accept risks for insurance, in particular based on the results of the actuarial calculation of the technical premium;
• loss adjustment function, which provides information on loss ratios by insurance type and by region;
• reserving function, which provides information about loss reserves (declared but not settled losses reserve (DLR) and incurred but unreported losses reserve (IULR);
• capital structure modeling function, which provides information on compliance with capital adequacy standards, on allocation of the insurer’s own capital, and etc.;
• management function, which receives information from actuaries on technical tariff rates, changes in tariff rates, etc.
• finance, which are a source of information about the costs of the insurer’s operating, financial and investment activities;
• risk management function, which independently verifies the pricing process and pricing models;
• reinsurance function, which provides information on the cost of reinsurance, which is an integral part of the price of insurance services.
• other functions, such as marketing, regulatory compliance, which are indirectly and/or directly related to pricing issues.

Figure 5.7 presents the pricing control cycle, which is implementation of the classic project management cycle (planning – execution – monitoring) for the insurance industry.

As the diagram presented in Figure 5.7 suggests, the important component of the pricing cycle is monitoring everything relevant to the pricing: claims handling, costs, investments, etc. The most important variables that also need to be monitored when setting prices are the national currency exchange rate and the inflation rate.

Figure 5.7. Pricing control cycle

Source: Developed by the author on the basis of Kudryavtsev A.A., 2011, Basic approaches to pricing (tariffication) in insurance

According to Article 942 of the Civil Code of the Republic of Uzbekistan, the measure of risk exposure is the insured amount.

Insurance services pricing in the Republic of Uzbekistan is carried out on the basis of “Methodological guidelines for calculating insurance rates in the non-life and life insurance industry” (Ministry of Finance of the Republic of Uzbekistan, 2007), while in order to carry out calculations using this methodology, there must be data on a number of statistical risk indicators. The use of this technique assumes the absence of catastrophic risks.

The above methodology does not apply to insurance of rare and large risks, as well as insurance types for which the necessary statistics are not available.

The current methodology for calculating tariff rates does not reflect trends in the frequency and severity of losses, therefore we consider it necessary to improve the methodology for calculating tariff rates using modern scientific and methodological approaches. This issue is also very relevant due to the fact that according to the current methodology, the tariff rate is calculated for homogeneous risks, which is rarely found in insurance practice. Therefore, when calculating the tariff for insurance product, it is necessary to seek a compromise between the degree of homogeneity of the insured objects and the representativeness of the statistics used.

Our analysis of the loss ratio of the main lines of insurance business in the non-life insurance industry for the period 2016-2022 indicated its growth trend, but it is still at a fairly low level (Figure 5.8): over the years, the loss ratio in the non-life insurance industry varied from 7.2% to 24.6%, while in the EU the loss ratio in 2020 ranged from 36.6% (Romania) to 76.0% (Iceland) (Claims ratio for non-life insurance in Europe, 2020).

Figure 5.8. Loss ratio by main business lines in the non-life insurance industry

Source: Developed by the author based on data from the Ministry of Economy and Finance of the Republic of Uzbekistan

It should be noted that reducing the loss ratio of insurance operations automatically increases the net profit of the insurer. But artificially reducing the loss ratio by using various tricks to refuse insurance claim payment leads to a loss of confidence of individuals and legal entities in insurance as a mechanism for protecting their property interests.

The analysis of indicators for compulsory motor liability insurance (CML) for the period 2016-2022, carried out as part of this study, justifies the need to revise tariff rates for this type of insurance (Figure 5.9.). First of all, this is justified by the fact that during the specified period, the total liabilities of insurers under CML increased 7.1 times, the insurance premium grew only 2 times, and insurance claims payment increased 8.5 times, as a result of which the loss ratio under CML increased from 15.4% in 2016 to 67.8% in 2022. The maximum level of loss ratio for CML was observed in the city of Tashkent – 119%. The loss ratio progress, in turn, led to a decrease of the CML insurance premiums share from 17.2% in 2016 to 3.8% at the end of 2022. Thus, the legally established reduced tariffs for CML led to a decrease in the volume and efficiency of this type of compulsory insurance.

Figure 5.9. Time series of premiums, sums insured and claims payment by CML relative to the 2016 indicator (Indicators for 2016 are taken as a unit)

Source: Developed by the author based on data from the Ministry of Economy and Finance of the Republic of Uzbekistan.

The experience of Uzbekinvest insurance company (and some other insurance companies of Uzbekistan) in the field of health insurance also confirms the importance of proper organization of the pricing process. In July 2020, the company started offering insurance consumers a new insurance product, “Insurance against coronavirus disease – COVID 19.” For four months (from July 2020 to October 2020), the insurance premium of 4,631.24 million Soums was collected. Due to a sharp increase in claims in November 2020, the company’s Insurance Committee decided to stop selling this product and within 2020-2021 insurance claims were paid in the amount of 19,242.75 million Soums and the loss ratio composed 415.5%.

In our opinion, during the development and implementation of this product we did not take into account anti-selection factor, which is inherent in health insurance. Setting the base rate for this product at 0.7% was the main mistake in the implementation of this product. This violated the basic principle of insurance –equivalence principle, which expresses the condition for insurance activities breakeven.

Table 5.1. Tariff structure

Source: Compiled by author

Tariffication problems are given much attention in the current international financial reporting standard IFRS 17 Insurance Contracts, which provides for the assessment of insurance obligations at the current cost of execution and offers a more unified approach to the assessment and presentation of all insurance contracts (IFRS 17, 2023) (see Table 5.1).

In the context of economic modernization, the relevance of insurance pricing issues increases many times over, because:

• price and cost transparency increase. Insurance activities digitalization provides insurance consumers the opportunity to compare hundreds of insurance products by price, value and benefits. These sites also educate consumers on how to more effectively match product choices to their unique needs and willingness to pay, as do insurance brokers;
• Consumers are more informed and sophisticated. As prices have become more transparent, consumers are increasingly open to new offers based on different variables such as security, mobility and different coverage types, and these offers require new, dynamic pricing structures;
• Control by insurance supervisory authorities is being strengthened. New rules, including Solvency II, require insurers to maintain higher capital levels without reducing overall profitability, and to do this, insurers must either reduce costs or increase prices;
• New financial products (for example, insurance ecosystems) and new technologies (for example, Insurtech) enter the market. The insurance industry diversifies with e-commerce, bancassurance, retailers and other non-traditional players offering new innovative business models and products;

New revolutionary technologies open up new pricing models. Big data, machine learning, and applied data analytical tools give insurance companies advanced and powerful options to develop pricing models based on using other innovative models; extract data from new external sources and more accurately assess the risk or willingness of consumers to pay, buy or refuse services (Azimov, 2022).

Factors of Solvency and Profitability of Insurance Companies’ Activities in Uzbekistan

Insurance reserves occupy a special place among the financial indicators characterizing the profitability of insurance activities. Insurance provisions are estimates of the insurer’s financial obligations to the insureds and, depending on the growth or decline in the insurer’s liability, the size of insurance provisions changes adequately.

The insurance reserves size affects the financial results of the insurance company. Insufficient formation of insurance reserves (under-reserving) in case of unfavorable situations can lead to the impossibility to fulfill obligations only at the expense of insurance reserves and requires using the own capital of the insurance organization, which negatively affects the solvency of the insurer. On the other hand, artificially increasing the insurance reserves amount (over-reserving) is also undesirable, since this brings to implementation of compliance risk and the application of penalties by insurance supervisory authorities. These are the reasons for the interest in the problems of formation and placement of insurance reserves from the insurers, shareholders of insurance companies and insurance supervisory authorities.

The Roadmap for the accelerated development of the insurance market in Uzbekistan provides for the implementation of measures to improve methods for calculating and placing insurance provisions, taking into account the basic insurance principles developed by the International Association of Insurance Supervisors (IAIS) (Resolution of the President of the Republic of Uzbekistan, 2019). The IAIS document entitled “Principles on Capital Adequacy and Solvency” presents 14 principles and the first principle concerns the formation of technical provisions and states the following: “… the insurer’s technical provisions must be adequate, reliable, objective; the technical provisions of various insurers must allow comparison with each other” (IAIS, 2002). It is noted that the technical provisions adequacy is the cornerstone for assessing capital adequacy and solvency. According to the 6^th principle of the document, the technical provisions assessment, along with the assessment of assets and solvency margin and the determination of suitable capital forms, is an element of the capital adequacy and solvency regime.

The role of insurance, including technical, reserves in ensuring the solvency of the insurer is especially emphasized in other IAIS documents. To support this, we provide the following quote from the “Insurance Core Principles and Common Framework for the Supervision of Internationally Active Insurance Groups” document: “The technical provisions of the insurer must be sufficient to cover all expected and some unexpected losses in accordance with valuation standards. The extent to which technical provisions cover unexpected losses will vary across jurisdictions, depending on the local regulatory structure and philosophy applied.” ((IAIS, 2019).

In our opinion, when implementing measures to improve the methods of formation and placement of insurance reserves provided for in Clause 9 of the Roadmap, great attention must be paid to the implementation of the 14^th insurance core principle (ICP 14) of the IAIS. This principle, called “Valuation”, is devoted to the issues of valuation of assets and liabilities of insurers for solvency purposes (Insurance Core Principles and Common Framework for the Supervision of Internationally Active Insurance Groups, 2019, pp.156-171).

As noted in item 14.0.9 of this document, “Technical provisions are a significant component of valuation for solvency purposes. They include a margin for risk appropriate for solvency purposes. Regulatory capital requirements are another component of the solvency assessment, and they include further allowance for risk so that when taken together, they are sufficient to ensure that policy obligations are satisfied with the probability of sufficiency required by the supervisor.”

According to ICP 14, the valuation of technical provisions exceeds the current estimate by a so-called margin “Margin over the Current Estimate” (MOCE). The current estimate of technical provisions represents the discounted value of the cash flows associated with their satisfaction of the insurer’s financial obligations. That is, the current estimate of technical provisions is a statistical average of liabilities, weighted by probability and its calculation is carried out using actuarial and statistical methods.

The introduction of the MOCE concept is due to the fact that the amount of insurance compensation is a random variable and the width of the range of its possible values depends on the nature of the risks accepted for insurance with many random factors. Insurers are required to maintain the amount in such a way as to meet their obligations to insureds.

Currently, there are many regulatory approaches to the technical provisions’ formation. In some jurisdictions, regulators base their technical provisions calculation on national accounting standards, perhaps with some minor modifications, to assess the solvency of insurers.

In other jurisdictions, regulators specify measurement basis that may differ significantly from accounting standards. Insurers in these jurisdictions may take simpler approaches to technical provisioning if they meet certain criteria regarding the nature of their risk profiles and the composition of their insurance portfolios. For example, in the Netherlands the insured type is taken into account. In South Africa, the use of a particular reservation method depends on the type of insurer. For example, insurers engaged in microinsurance are subject to simplified requirements for technical provisions.

Under Solvency II, insurers must use methods to calculate technical provisions that are proportionate to the nature, scale and complexity of the risks their insurance liabilities based on. In determining whether the method of calculating technical provisions is proportionate, insurers must make an assessment. This assessment must include all risks that affect the amount, timing or value of cash inflows and outflows required to settle insurance claims during their term.

From a practical point of view, the recommendations for the technical provisions assessment developed by the European Insurance and Occupational Pensions Authority (EIOPA) are of great interest, where simplified formulas are proposed for the technical provisions’ assessment according to Solvency II standards (Guidelines on the valuation of technical provisions, 2014). For a better assessment of premiums, the following calculation formula is proposed:

BE = CR * VM + (CR-1)*PVFP + AER * PVFP

Where,

• BE-best estimate of premium provision;
• CR – estimate of combined ratio;
• VM – volume measure for unearned premium;
• PVFP is the present value of future premiums;
• AER – estimate of acquisition expenses ratio.

Formation of insurance provisions by domestic insurance companies is regulated by the Law of the Republic of Uzbekistan “On Insurance Activities” №358-II dated by April 05, 2002 (Law of the Republic of Uzbekistan, 2002).

The structure and procedure for calculating insurance reserves, as well as the conditions for their placement, are established by the Regulations of the Ministry of Finance of the Republic of Uzbekistan №107 dated by November 20, 2008 “On Insurance Reserves of Insurers” (hereinafter referred to as the Regulations) (Regulations of the Ministry of Finance of the Republic of Uzbekistan, 2008). The Regulations define insurance reserves as “funds generated by the insurer from insurance premiums paid by the insured both in Soums and in foreign currency and accounted for as assets or liabilities on the insurer’s balance sheet, necessary to fulfill financial obligations for insurance claims, for loss settlement expenses and of preventive measures financing” (Regulations of the Ministry of Finance of the Republic of Uzbekistan, 2008).

According to this regulatory act, insurance organizations must form on reporting dates:

• unearned premium reserve (UPR);
• insurance reserve (IR);
• loss reserve:
• reported but not settled (RBNS);
• incurred but not reported losses reserve (IBNR);
• stabilization reserves for compulsory motor liability insurance (CML), compulsory employer’s civil liability insurance (CECL) and compulsory carrier’s civil liability insurance (CCCL).

The insurer may additionally form the following types of reserves: preventive measures reserve (PMR), catastrophes reserve (CR), loss fluctuations reserve (LFR), assets non-compliance reserve (ANR); other types of reserves related to insurance activities.

Another legal act where the concepts of “insurance reserves” and “insurance company solvency” are described in close interconnection is the Regulation on the Solvency of Insurers and Reinsurers of the Ministry of Finance of the Republic of Uzbekistan dated by April 22, 2008 №41 which notes that “the solvency basis is the presence of the formed authorized capital, sufficient insurance reserves, as well as reinsurance system” (Regulations on the solvency of insurers and reinsurers, 2008).

In international practice, in order to increase the level of compliance of insurers’ assets to liabilities, so-called audits of the adequacy and sufficiency of liabilities, including insurance reserves, are carried out. For example, IFRS 4 Insurance Contracts require the adequacy of liabilities at each reporting date: “The insurer must assess as at the end of each reporting period” (IFRS 4, 2004.).

In accordance with IFRS standards, based on the results of checking the adequacy of the unearned premium reserve (UPR), it may be necessary to create unexpired risk reserve (URR) which is intended “to cover the insurer’s obligations related to future losses payments, costs of settling these losses and future costs of servicing existing insurance contracts in excess of the UPR.” The URR is not formed if testing at the reporting date confirms the sufficiency of the unearned premium reserve.

With regard to the loss reserves, the national accounting system does not require testing of their adequacy. However, when reporting in accordance with IFRS, it is recommended that the insurer regularly monitors changes in loss reserves.

This form of checking the reserve adequacy is carried out on the basis of the insurer’s own statistics on the actual payment of losses in the past and current estimates of the loss reserves and therefore in the insurance literature is called a “run-off analysis of the adequacy” of the loss reserve.

To briefly describe the algorithm for conducting a run-off analysis of the adequacy of the loss reserve, it represents a comparison of the initially formed loss reserve as of the date of the initial assessment with an adjusted (according to recent statistical data) assessment of these liabilities. In this case, the updated assessment of liabilities should take into account information both on the paid losses after the date of the initial assessment and on the current assessment of unsettled losses.

The ratio of the difference between the initially formed loss reserve as of the date of the initial assessment and the adjusted assessment of these obligations to the initially formed loss reserve is an indicator that assesses the adequacy of loss reserves as of the current reporting date.

According to Clause 23 of the Regulations on Insurance Reserves of Insurers, the reserve for incurred but not reported losses reserve (IBNR) is calculated for each insurance type separately, taking into account the accumulated statistics of the insurer on the insurance claims payments for this insurance type. Total IBNR is determined by summing IBNR calculated for each insurance type. However, this amount in proportion to total insurance (reinsurance) should not in any case be less than 10% of the amount of the base insurance premium under non-life insurance (reinsurance) agreements for the period of twelve months before the reporting date. That is, the base for calculating IBNR is the value of the basic insurance premium.

With this approach to calculating the size of IBNR, the adequacy of the reserve depends on the structure of the insurance portfolio and the value of insurance tariffs. Calculation of IBNR as a share of the basic insurance premium for all insurance types, regardless of the risk profile, leads to a violation of the principle of reserves adequacy for accepted liabilities.

We consider it advisable to take as the basis for calculating IBNR not the basic insurance premium, but the basic insurance premium – net of reinsurance. This is especially important for smaller insurance companies. Practice shows that taking the base insurance premium as a basis for small insurance companies can make problems related to compliance with the regulatory requirement that “the insurer is obliged to allocate assets in the amount equivalent to the value of insurance reserves,” threatening them with penalties from ASB.

In this regard, we consider it appropriate to use a proportional approach to calculating IBNR, as it is practiced in the jurisdictions of countries such as France, Great Britain and Sweden.

In paragraph 3.1. issues of financial stability and solvency were studied in close connection with macroeconomic, financial and institutional factors. From a practical point of view, research works studying the influence of internal factors specific to insurance companies on the financial stability and solvency of the company are of great interest. For example, Yu. Kim and others, based on the analysis of financial statements of US insurance companies, came to the conclusion that to predict the bankruptcy of insurers engaged in the non-life insurance industry, important variables include the company age, the premiums growth rate, the rate of return on investments, underwriting profit, operating expenses, loss reserves, equity capital growth rate and financial result from risk transfer to reinsurance (Kim,Yong-Duck et al., 1995).

1. Adams and M. Buckle studied the factors that influence the insurance activities profitability using the example of 47 insurance companies in Bermuda (Adams & Buckle, 2003). As independent variables (influencing factors), they took the amount of the company’s assets, the financial leverage ratio (the ratio of insurance reserves to equity capital), the liquidity of the company’s assets, the type of company and the volume of insurance liabilities. According to the results, financial performance is positively influenced by financial leverage ratio, company type and underwriting risk. On the contrary, liquidity has a significant negative impact on the company’s solvency. The authors argue that company’s size and insurance volumes do not have a significant correlation with financial performance.
2. Burca and G. Batrincea studied the problems of financial sustainability based on statistical data of Romanian insurance companies for the period 2008-2012. The factors taken into account were the financial leverage ratio, the company size, the age of the company, the growth rate of gross premiums written, equity capital, the company’s market share, the degree of portfolio diversification (Herfindahl-Hirschman index), underwriting risk, the share of investments in assets, the share of reinsurers in premiums, retention rate (ratio of retained earnings to net income), solvency margin and per capita GDP growth rate. The authors came to the conclusion that the determining factors for the financial stability of Romanian insurers are the financial leverage ratio, company size, growth rate of gross premiums written, underwriting risk, retention rate and solvency margin (Burca & Batrinca, 2014).

In the work of D. Jadi, based on statistical data from 57 UK companies for the period 2006-2010. the financial stability of the insurer was studied depending on the following 8 variables (factors): financial leverage ratio, return on investment, asset liquidity, company size, reinsurers’ share in premiums, growth rate of equity capital, type of business and organizational form of the company. It has been established that return on investment, assets liquidity, size and organizational form are statistically significant factors in the financial stability of the insurer (Jadi, n.d.).

Professor of Gazi University (Turkey) U. Kaya, based on statistical data from 24 insurance companies in Turkey in the non-life insurance industry, studied the financial stability of insurance company as a function of the following variables: the amount of assets of the company, the age of the company, the loss ratio, the current liquidity ratio, the financial leverage, the share of auto insurance in the company’s portfolio, the growth rate of premiums and the insurance premium retention rate (Öner, 2015). According to the study, the factors affecting the profitability of Turkish insurance companies in the non-life insurance industry are the company’s total assets, company age, loss ratio, current ratio and premium growth rate. This brief review of research shows that there are a large number of potentially useful financial reporting indicators for assessing the financial strength and solvency of insurers. This, in turn, requires data structuring and prioritization.

In our opinion, the structuring criteria are:

–    analytical significance of indicators;

–    minimization of the number of indicators with the most useful information;

–    availability;

Of great interest is the model for assessing the financial stability of insurance company, developed by the International Monetary Fund for insurers (Davies et al., 2003). In the model, indicators are conditionally divided into two groups:

• a “core set” for which indicators are publicly available and relevant for analytical purposes in almost all countries, and
• a “recommended set” for which data are not readily available and the relevance of which may vary between countries.

The International Monetary Fund model uses two new indicators. The first indicator is an indicator of the reliability of management and actuarial function. Indeed, rational management of the insurance company is crucial for the financial stability of insurers and quantifying the quality of management is quite a difficult task.

The second indicator is the so-called “survival rate” – the ratio of net technical provisions to the average annual net losses paid over the last 3 years. This indicator measures the extent to which the company adequately assesses the cost of the loss reserves (RBNS and IBNR). One of the important indicators of financial stability is the profitability of the insurer’s insurance activities. In order to assess financial stability, we used a regression model, which is based on statistical data from 24 insurance companies in the non-life insurance industry for the period 2018-2020. The following indicators were taken as independent variables (influence factors):

X_1tк –gross premiums written in year t (t=1,2,3) for company k (k=1,2,…, 24);

X_2tк – premiums transferred to reinsurance in year t for company k;

X_3tк – insurance reserves as of December 31 of year t for company k;

X_4tк – equity capital of company k as of December 31 of year t;

X_5tк – assets of company k as of December 31 of year t;

X_6tк – age of company k in year t;

X_7tк – number of full-time employees of company k as of December 31 of year t;

X_8tк – number of insurance agents of company k as of December 31 of year t.

The dependent variable Yit is the amount of net profit of company k as of the reporting date December 31 of year t.

With our indicators, the regression equation takes the form:

Y = Y0 + a1X1tk+ a2X2tk + a3X3tk+ a4X4tk + a5X5tk+ a6X6tk + a7X7tk+ a8X8tk +έtk

where έtk is the random component of the model (“white noise”)

In order to check the absence of correlation, a correlation matrix was compiled (Table 5.2.), which shows that there is a strong connection between the factor’s “assets” and “equity”, and that removing one of them improves the quality of the regression model. For this reason, the variable X_4tк (equity) was removed from the model.

Table 5.2. Correlation matrix

Source: Developed by the author

In Table 5.3. statistics of the regression equation are presented, according to which the density of dependence between factors is 57.0% (average level) and the level of profitability of insurance activities is determined by the given factors only by 32.5%.

Table 5.3. Regression statistics

Source: Developed by the author

The conducted Fisher’s F-test (Table 5.4.) shows that its actual (empirical) value is 4.39. With the given statistics, the Fisher’s critical value is 2.23, which means the statistical significance of the regression model under consideration.

Table 5.4. Analysis of variance

Source: Developed by the author

Estimates of the unknown parameters of the model are presented in Table 5.5.

Table 5.5. Estimates of unknown coefficients of a regression model

Source: Developed by the author

With the given statistics, the table value of the t-test is 1.9944. This means that in the model under consideration, the influence of variables X1 (premiums) and X7 (number of employees) on the profitability of insurance activities are statistically significant.

The main conclusions of the regression model. The analysis demonstrates that the level of profitability of insurance activity of insurers only by 32,5% is determined by the given nine variables and only 2 variables out of nine are statistically significant. In our opinion, such unexpected findings are a consequence of underdeveloped insurance market, aggressive marketing strategies of young companies with small capitals and weak market control by the regulator. According to our opinion, the efficiency of companies’ operations also depends on such qualitative variables as organization of the underwriting system and other business processes, the influence of which is difficult to reflect in a regression model.

Conclusions on the Fifth Chapter

1. Assessing the solvency and financial stability of insurers is a rather complex task and requires the collection, processing, and interpretation of a large amount of statistical information, the use of labor-intensive economic-mathematical and probabilistic-statistical methods using modern applied software products. To implement Solvency II solvency standards in the conditions of the Republic of Uzbekistan, at the first stage, a simplified system for assessing its main indicators is proposed. They should mainly provide prove for the optimal amount of equity capital required and methods for calculating technical provisions. Calculation of insurance reserves adequate to the risks accepted for insurance should become a key business process of the insurer. Improving the reliability and completeness of the assessment of insurance reserves and disclosing information about the sources and level of insured risks makes it possible to quickly determine the profitability and riskiness of insurance activities. Therefore, improving the insurance reserves assessment in conjunction with financial reporting according to international standards will make it possible to make timely, correct decisions necessary for the successful development of insurance companies in conditions of high competition and increasing regulatory restrictions.
2. According to Clause 23 of the Regulations on Insurance Reserves of Insurers, the size of IBNR should not be less than 10% of the amount of the basic insurance premium under non-life insurance (reinsurance) agreements for the period of twelve months before the reporting date.

With this approach to calculating the size of IBNR, the adequacy of the reserve depends on the structure of the insurance portfolio and the value of insurance tariffs. Calculation of IBNR as a share of the basic insurance premium for all insurance types, regardless of the risk profile, leads to a violation of the principle of reserves adequacy for accepted liabilities.