Applicability of Actuarial Science
Actuarial science is being widely used in many different industries nowadays. Actuarial science can make wonders when it is applied wherever risk is present. Though actuarial science has been applied in insurance and pension sectors since its origin, now the trend is being changed and it is widely used in different areas including shipping, consultation, criminal sentencing etc.
Insurance companies cannot run practically without applying actuarial science effectively. It is applied to predict profit and risk in insurance companies so as to make sure that the company is able to meet targets with minimal risk and maximum profit. Health risks over a life time are to be calculated in order to plan different activities of the company. Appropriate mathematical and statistical calculations are done to design new insurance products, determine premiums, choose target people for insurance products, analyse mortality rate and produce life tables etc. Now, short term insurance policies are also available for one year or two year period. Here actuarial science is used to check how different factors affect the policy for that particular period of time.
Health insurance companies also make use of actuarial science in order to analyse rates of morbidity, disability, fertility, death and other unforeseen events. Though it is really difficult to predict accidents, death and other unexpected events accurately, actuarial science can predict all these studying existing records and regular patterns. Thus, if a person is too sick and thus highly risky, most of the health insurance companies would not be ready to insure that person as there are more chances for the company to lose money on him. While calculating risk in case of a person’ s life, factors like gender, age, disease history etc are considered for making predictions.
Pension industry also applies actuarial science to determine payouts for pensions. This input is mainly used while designing, maintaining and re-designing new plans. Pension plans should be practical for both the company and people. The company would be left destitute if pension payments are too high or people live too long. So, pension plans should be well designed evaluating the risk by considering factors like age, diseases, unexpected events etc.
Banking is another sector where actuarial science is widely used. Consider the case where a customer does not have minimum balance most of the time in his account.
Actuarial science can be used to predict whether this customer is worth keeping or risky. Similarly, before approving loans, actuarial science can be used to foresee whether the customer would make monthly installments on time considering many different factors like income, qualification etc. If the customer is found to be risky, banks would not approve loan. Even investment management makes effective use of actuarial science for investment analysis, portfolio management and asset management. Consultancies offering investment management, enterprise risk management, corporate recovery, merger and acquisition advice etc are of high demand today and these consultancies apply actuarial science to find the risk associated with all these.
Criminal sentencing is an area where actuarial science is being used nowadays. In order to develop criminal sentencing guidelines, many US states now use actuarial science. Different factors like age, gender, type of crime, educational background, ethnicity etc of the offender is considered to predict the chance of relapsing. This kind of criminal sentencing provokes criticism saying that ethnicity and educational background are considered to discriminate people. Even to assess sex reoffending and decide sentencing, actuarial science is being applied. Different actuarial models like Static-99, SORAG (Sex Offender Risk Appraisal Guide) and MnSOST-R (Minnesota Sex Offender Screening Tool-Revised) have been in use since late 1990s to decide the probability of a sex offender relapsing to the behaviour and whether he needs to be kept in an institution or sent free.
