Findings
Singapore is a well-established nation with a good road network that is well connected. This has eased transportation in the country as moving from one point to another has been made easier by their roads which follow acceptable international standards for road quality and safety. Over the years, Singapore has improved their road safety measures by implementing different policies and ensuring its roads are well maintained (Li et al., 2018, p.1277). There are different selections in insurance markets with varying dimensional information, which significantly defines the characteristics of automobile owners and insurance companies. Some aspects that form the dimensional information include policyholders’ riskiness and the degree of risk aversion.
Objectives
This article evaluates the relationship between policyholders and their insurance selection in Singapore’s automobile market. The impact of vehicle and driver characteristics on accident experience is also essential because it acts as a pointer in explaining the relationship between the main two factors (Koh and Lee, 2017, p.365-372). The existing relationship between the policyholder and their selected insurance dramatically influences the market price of the insurance coverages.
Although the adverse selection problem in insurance markets has been the subject of substantial theoretical study, its practical applicability is still hotly contested. According to this viewpoint, the key empirical topic is to discuss adverse selection as a significant issue with allocating resources in many marketplaces (Shi and Zhang, 2016, pp.557-578). Risk categorization is mainly connected to perverse incentives in the markets for auto insurance. However, different deductibles may also be explained by proportionate transaction costs with various apparent hazards.
Hypothesis
Singapore’s automobile and insurance industry has changed drastically over the years as technology continues to improve. Automobile insurance in the country has also been following new trends as different factors have affected the industry. Still, the main factor that has helped the industry’s growth is the relationship between the policyholders and the insurance companies (Spiteri and Azzopardi, 2018, pp.173-178). With the adaptation of EVs in the country, the insurance companies have been forced to adjust to meet the new requirements.
Literature review
For a long time, the most vulnerable users of the road system have been motorcyclists and pedestrians. The Land Transport Authority has incorporated several measures in the land transport master plan 2008 to improve the safety of those users. The attempts to improve the facilities for improved motorcycle safety include paving high-skid resistant materials in crash-prone areas, placing more substantial vehicle impact guardrails suitable for motorcyclists, and providing more rain shelters to encourage motorcyclists not to ride in the rain (Hsieh et al., 2014, pp.90-103). These measures have helped to reduce accidents in Singapore but, at the same time, have defined new parameters which have affected the relationship between the policyholder and the insurance companies.
The most lucrative insurance market segment in Singapore among the many insurance subsectors is motor insurance. Different insurance companies in the country have related more with the key partners and stakeholders like the authorities and safety council to improve road safety among road users. Additionally, sales of EV vehicles increased in the year leading up to September 2020, which will increase the demand for auto insurance (Owens, 2020). Additionally, Singapore’s insurance clients are becoming more environmentally sensitive and favour EVs. This spike in interest in electric cars is expected to increase demand for new motor vehicle insurance coverage, fueling the expansion of Singapore’s motor insurance industry.
Variables to be measured
The main variables under investigation are dichotomous and the deductible options in the event an accident occurs. A different variable is also necessary to carefully evaluate the relationship between the variables (Jeong et al., 2018, p.69). Therefore, it is necessary to analyze both decision variables and those that cannot be seen. Considering these variables makes the study more effective because it helps to establish an empirical strategy that omits the deductible options.
The vehicle insurance market’s excellent results attest to government policy’s success. The division generated underwriting gains to make up for the losses recorded in 2020 Q2. Due to rising urbanism and consumer per capita income, there is a significant growth in the demand for motor cars in Singapore (Nizamuddin and Abugabah, 2021). Insurance for the ‘ car sector is backed by several reasons, including manpower resources, R&D initiatives, topographical benefits, and state assistance, which has resulted in a growth in automotive sales in Singapore. Businesses implementing automation and digital advances, and the insurance association collaborates with other organizations to save operational costs, boost productivity, and lower fraud instances.
Data collection
Different methods have been used to evaluate the relationship between policyholders and insurance companies in Singapore. Some data collection methods used are surveys to help analyze the percentages of different insurance policies in the country, scientific studies, and observational studies (Koh and Lee, 2017, p.365-372). Scholars, business professionals, and government officials have recently focused on the link between insurance, the frequency of road traffic accidents (RTAs), and overall traffic safety. It is possible to determine if drivers with higher insurance coverage are more likely to be engaged in RTAs using data on vehicle damage insurance in Singapore and whether the connection is affected by the insured party’s gender and the age of both the vehicle and the insured party (Hanafy and Ming., 2021 p.42). If an insured party with a wrong claims history is more likely to be engaged in road traffic accidents, assessing systems may be used to demonstrate a positive correlation between cover and claims.
Data for analysis
According to a survey done on the number of people with comprehensive motor insurance in the country, it revealed that as of 2018, the total number of vehicles in Singapore was 957,006, which was a decrease of 0.5% compared to the previous year (Fong and Borowski, 2022 pp.73-90). The number increased in 2019 to 967,768 but has been affected again by Covid-19 because of the impacts of theInsurance Options of Policyholders pandemic on the economy of the world (Owens, 2020). The number of private cars in the country was about 600,000, which was also an increase compared to the previous year (Desyllas and Sako, 2013, pp.101-116). A measure of car ownership in the country is also an essential indicator of the insurance market and available policies.
Data analysis
It is essential to carefully examine the top companies in Singapore dealing with automotive insurance to analyse the adverse selection with all the related pressure. The data to be analyzed is from 2019, which gives detailed information on the types of insurance policies available in the country and the sales for the same year (Shi and Zhang, 2016, pp.557-578). This helps paint a clear picture of the preferred policy and how other policies are affected by specific factors, and a more solid conclusion can be made on the relationship between the policyholder and the insurance company.
The price of auto insurance in Singapore ranges from $700 to $1,000 yearly. Still, the precise amount is determined case-by-case since it mainly relies on your age, employment, driving history, and other criteria (Jeong et al., 2018 p.69). Detailed analysis of the different factors that influence the type of policy insurance gives are:
- Gender and age
- Relational status
- Occupation
- Driving knowledge
- History of claims and the no claims discount (NCD)
- Discount for a certificate of merit (com)
- Type, model, age, and use of the vehicle
In Singapore, drivers are required by the law to have insurance in case of an accident. Comprehensive insurance covers the vehicle and third party in case of an accident or theft and is mostly preferred by many (Desyllas and Sako, 2013, pp.101-116). It is, however, relatively expensive compared to third parties alone. Motorists often consider getting auto insurance to pay for physical damage or losses from crashes, theft, or other tragic incidents to fund the monetary losses resulting from RTAs. To cover themselves against any legal obligation resulting from incidents resulting in personal harm and/or property damage to other people or their cars, drivers must have insurance coverage in the country.
Results and conclusion
The amount deductible is the “deducted” amount from an insured loss and plays a major role in a contract by representing sharable risk between the policyholder and the company. Usually, selecting a lower deductible by a policyholder is less vulnerable to risks, but the expenditure to be incurred is often higher (Li et al., 2018, p.1277). The choice of either a lower or higher deductible by a person, therefore, establishes a lower or higher bound for his coefficient of absolute risk aversion. Verifying if latent information asymmetries explain the presence of different deductibles in an insurance portfolio is challenging empirical research related to this discussion regarding the deductible decision.
Variables used in the study can be categorized into different groups:
Contracts
The insurance companies in Singapore offer different covers which have varying deductibles.
- Third-party liability. All vehicles are required to have this policy, but the policy is cheaper.
- Comprehensive cover. This cover has different levels of deductibles, but the difference between the deductibles is insignificant.
Drivers knowledge
The driver’s knowledge about the insurance policy is the parent factor. It is important forthe driver to fully understand the policy and the insurance cover in detail.
Drivers characteristics
Under the driver’s characteristics, different factors directly affect the driver (Desyllas and Sako, 2013, pp.101-116). Gender, age and occupation are some important factors considered under the characteristics. The occupation is important to define the profession of the policyholder.
Cars’ condition
The origin of the car is an important aspect here. The year of manufacture is used to determine the car’s age and mileage (Fong and Borowski, 2022, pp.73-90). The car’s overall condition is also an important aspect that defines some of the deductibles in the policy. Involvement in past accidents is also considered and greatly affects the policy.
The study has been based on empirical data and is greatly affected by the type of insurance portfolio. Singapore is a well-developed country with a good automotive industry (Hsieh et al., 2014, pp.90-103). The country has different companies offering automotive insurance and gives different policies. Some policies have different deductibles and are preferred by a specific group. The insurance company must choose a reasonable premium that must be accepted by the policyholder and should also be beneficial to the company. Because of this, overestimating or underestimating the premium can support a strong and healthy insurance system.
Reference
Desyllas, P. and Sako, M., 2013. Profiting from business model innovation: Evidence from Pay-As-You-Drive auto insurance. Research Policy, 42(1), pp.101-116.
Fong, J.H. and Borowski, A., 2022. Long-term care insurance reform in Singapore. Journal of Aging & Social Policy, 34(1), pp.73-90.
Hanafy, M. and Ming, R., 2021. Machine learning approaches for auto insurance big data. Risks, 9(2), p.42.
Hsieh, S.H., Liu, C.T. and Tzeng, L.Y., 2014. Insurance marketing channel as a screening mechanism: Empirical evidence from Taiwan automobile insurance market. The Geneva Papers on Risk and Insurance-Issues and Practice, 39(1), pp.90-103.
Jeong, H., Gan, G. and Valdez, E.A., 2018. Association rules for understanding policyholder lapses. Risks, 6(3), p.69.
Koh, S.H. and Lee, R., 2017. GST and Insurance: Singapore. In VAT and Financial Services (pp. 365-372). Springer, Singapore.
Li, Y., Taeihagh, A. and De Jong, M., 2018. The governance of risks in ridesharing: A revelatory case from Singapore. Energies, 11(5), p.1277.
Nizamuddin, N. and Abugabah, A., 2021. Blockchain for automotive: An insight towards the IPFS blockchain-based auto insurance sector. International Journal of Electrical and Computer Engineering (ICE), 11.
Owens, E., 2020. Big Data Analytics, Disclosure and Ethical Underwriting: A Balancing Act within the Motor Insurance Sector.
Shi, P. and Zhang, W., 2016. A test of asymmetric learning in competitive insurance with partial information sharing. Journal of Risk and Insurance, 83(3), pp.557-578.
Spiteri, M. and Azzopardi, G., 2018, September. Customer churn prediction for a motor insurance company. In 2018 Thirteenth International Conference on Digital Information Management (ICDIM) (pp. 173-178). IEEE.
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