Insurance industry
Insurance can be defined as a contract accompanied by a policy, in which an individual or organization transfers its potential risk of financial loss to an insurance company that obligates to compensate the insured upon the occurrence of the insured risk. The parties involved are the insured and the insurance company (Cummins & Weiss, 2013). The insured is a person or an organization which seeks for financial protection of its property with an insurance company. The insured is compensated when the risk insured against occurs. On the other hand, an insurance company is a legalized body that takes an obligation of compensating the insured an equal amount of the loss in case of the risk insured occurs. It is also called the insurer. From the individual point of view, insurance contract is based on life and property compensation. A person or organization expects to be compensated just in case the risk involved occurs (Dipert, 2013). One can take insurance against loss of his life or property. Basically, society understands insurance as a financial risk management tool in which the insurance company benefits upon compensating the insured. In this case, profit making policy by insurance company is majorly stressed on.
There are two essential elements for any insurance mechanism to operate. These are; the insurance company and the insured. As explained earlier, an insurance company is that entity which accepts to return the insured in the financial position he was before the risk insured occurred (Handel, 2013). Compensation is done either financially or by equivalent property according to the initial legal agreement of the two parties involved in the contract. The basic knowledge upon the operation of insurance company is that a central fund system is created i9n which the insured parties make interval deposits of premiums with the company (Cummins & Weiss, 2013). Don't use plagiarised sources.Get your custom essay just from $11/page
The Law of Large Numbers can be described as the measure of the probability of the occurrence of the insured risk (Olayungbo & Akinlo, 2016). The likelihood of occurrence of a risk is attributed to the frequencies of the previous occurrence of that event. As the number of trials or experiments increases, the ratio of actual outcomes converges on the theoretical or expected outcomes (Dipert, 2013). This law helps insurance companies to predict amount for compensation of any risk. The insurance company opts to acquire a large number of identical policy holders who will contribute to a fund that will pay the losses (Nerlove, 1928). The law of large numbers can clearly be explained by a toss of a coin. If a coin is tossed equal number of times, it is mostly likely that the number of heads showing up equals the number of tails though each event is independent. If after researching, each policyholder’s contributions to the pool’s resources overcomes the expected loss payment amount, new policyholders are encouraged to join in order to reduce the probability that pools resources will fail to compensate for the loss occurred (Outreville, 2013). Although the entry of additional policyholders increases risks, it also leads to increase of the pools resources hence high probability of compensation (Olayungbo & Akinlo, 2016). If the insured parties increase their contribution of the expected loss of risks, it will result to ‘risk bearing capacity’. In this case, capacity to absorb possible deviations from expected value increase to overcome the actual deviations.
Significantly for any loss to be compensated upon occurrence of insured risk, there are underlying principles that must be put into consideration. First, the loss must be due to chance. Regular and common risks cannot be compensated. For instance, the insurance company will not be in a position to compensate losses such regular shoplifting in a supermarket because they are always tide to price (Dipert, 2013). Secondly, the amount involved in loss must be substantial. It means that the insured will only be compensated if the loss has led to real suffering. However, this prediction is always tied to the value of the property. Thirdly, the risk leading to loss must be accidental. Some individuals or organization will subject their old property to the insured risk in order to be compensated. It is against the set policy and on realization, the insurance company will not be in a positions to compensate the insured. Fourthly, compensation is valid only if the loss is due to the risk insured (Handel, 2013). For instance, if an individual insures his property against fire, loss caused by theft of the property will not be compensated at all. Finally, the loss must be definite and measurable. It should be easy to estimate any loss for compensation.
Adverse selection can be defined as the tendency of the high risk lifestyles or dangerous jobs to secure life insurance. In areas with high risk of death, customers may be willing to take life insurance. If the insurance company opts to charge an average price but only high risk consumers buy, there is likelihood that the insurance company will make loss (Dipert, 2013). In contrast, if the company chooses to raise the premiums, it will have more money to pay for those benefits. The number of the policy holders who will be willing to take the life insurance with the high premiums decreases. Therefore, two challenges will arise in this case, that is; the problem of insurance company to make high loss if they raise the premiums and only few policyholders are willing to take the insurance with the company. Secondly, low-risky customers will starve to get insured for their property in the areas with high risks of life even if the insurance company charges the average prices (Olayungbo & Akinlo, 2016). However, insurers can avoid the problem of adverse selection can be minimized through clear identification of groups of insured. Premiums for the high risk insured should be apparently different as compared to those living in low risk areas.
According to Yao & Gao, (2016), insurance has great contributions to the economy of a state. First, insurance promotes financial stability of individuals and organizations. The individuals that suffers loss as a result of the insured risk occurring are returned to the financial position they were before the occurrence of the risk (Handel, 2013). Therefore, they gain energy and returns to operation. This encourages the firms to invest being guaranteed for compensation once the risk occurs. Insurance facilitates trade. Most of the people are likely to acquire products for sale without fear because in the long run, they are guaranteed of compensation of their products in case of any loss (Cummins & Weiss 2013). Insurance makes businesses safer. Insurance keeps confirmation to the businesses of the risks involved in its daily operation. This makes businesses work in the safer programs. Insurance promotes recovery. Businesses are returned into the positions they were before the occurrence of major catastrophes such earthquakes (Dipert, 2013). In addition, it helps to protect people’s purchases. Some people will consider to purchase most expensive buildings cars and other property since there is compensation after all. Finally insurance company facilitates effective risk management. For instance, pricing system is managed by charging highly more risky cases or where a great loss is expected and charging less premiums in the case of low risky or low loss cases.
References
Cummins, J. D., & Weiss, M. A. (2013). Analyzing firm performance in the insurance industry using frontier efficiency and productivity methods. In Handbook of insurance (pp. 795- 861). Springer New York.
Dipert, R. (2013). The essential features of an ontology for cyberwarfare (pp. 35-48). Taylor & Francis.
Handel, B. R. (2013). Adverse selection and inertia in health insurance markets: When nudging hurts. The American Economic Review, 103(7), 2643-2682.
Nerlove, S. H. (1928). The Investment Element in Life-Insurance Contracts. The Journal of Business of the University of Chicago, 1(3), 273-293.
Olayungbo, D. O., & Akinlo, A. E. (2016). Insurance penetration and economic growth in Africa: Dynamic effects analysis using Bayesian TVP-VAR approach. Cogent Economics & Finance, 4(1), 1150390.
Outreville, J. F. (2013). Insurance Markets in Developing Countries: Economic Importance and Retention Capacity. In Handbook of Insurance (pp. 941-956). Springer New York.
Yao, K., & Gao, J. (2016). Law of large numbers for uncertain random variables. IEEE Transactions on Fuzzy Systems, 24(3), 615-621.