Motor Insurance Industry Research Articles

Interpersonal communication in the motor insurance sector during the claims stage

Orientation: The South African short-term motor insurance industry is highly competitive, offering clients many choices. Therefore, the long-term retention of clients is crucial for an insurance company’s sustainability.Research purpose: The study aims to report on the context-specific communication challenges during the claims stage and to propose recommendations to mitigate them from an interpersonal communication perspective.Motivation for the study: Studies on client retention have been conducted from a marketing or corporate communication perspective, but it is not known how interpersonal communication during the claims phase could impact long-term relationships.Research design, approach and method: We followed a qualitative approach, with a single case study design. Semi-structured interviews were conducted with senior management and claims administrators in the motor insurance department of a large South African insurer. The data were inductively analysed through qualitative content analysis from which the challenges were identified.Main findings: A lack of mutual understanding, ineffective conflict management, a lack of trust and one-way communication were identified as the main challenges experienced by claims administrators in their communication with clients during the claims stage.Practical/managerial implications: Practical principles such as sympathy and empathy, listening, feedback, respect, providing and clarifying information and providing access to resources, together with ethical and transparent communication, two-way symmetrical communication and dialogue should be included in claims administrators’ training to enable them to understand and adapt to the client’s needs.Contribution/value-add: A framework for training claims administrators operating in this context is presented, offering a theoretical and practical contribution.

Key Determinants to Drive Motor Insurance Customer Acquisition in Western Province, Sri Lanka: A Focus on the Marketing Mix

Purpose: There is a significant need for a comprehensive insurance policy for all vehicle owners, especially considering the growing emphasis on health and safety, and public protection. The substantial preference for 3rd party insurance over comprehensive policy covers has created a hurdle for insurance companies, both in terms of acquiring new customers and retaining existing ones. This prevailing trend has presented a significant challenge to the growth potential of general insurance firms in the market. The main purpose of this study is to investigate how factors such as product, price, promotion, and distribution network influence the customer purchase intention towards motor insurance. Design/methodology/approach: This was a cross-sectional study using a deductive research approach. Data were gathered from 412 policy holders in Sri Lanka using a self-administered structured questionnaire. Multiple regression analysis was used to determine the most influencing factor among product, price, promotion and distribution network influencing customer purchase intention towards motor insurance. Findings: Based on the analysis, the insurance service [product], insurance premium [price], promotion and distribution network have a significant relationship with the customer purchase intention towards motor insurance policies in Sri Lanka. Among the factors tested, distribution network and insurance service have the most significant impact on customer purchase intention with reference to motor insurance segment. Originality: This study provides a unique contribution by highlighting the critical role of the distribution network, particularly the combination of Place and People elements, in driving motor insurance customer acquisition in Sri Lanka. Unlike prior studies that emphasize price and promotional strategies, this research focuses on the integrated influence of accessibility and personalized service. The findings demonstrate that a well-established distribution network outweighs traditional marketing factors in influencing purchase decisions, offering a new perspective on consumer behavior in the Sri Lankan motor insurance industry. Implications: The findings of this study will pave the way for a paradigm shift where, insurance firms could understand and develop relevant strategies to improve services provided to the existing and potential motor insurance customers. By analyzing what truly matters to Sri Lankan drivers, both insurance service providers as well as regulatory authorities can ally and develop a holistic insurance policy that comprehensively covers all aspects of vehicle ownership, filling the void in the current market. According to the findings, it can be advised that the insurance corporations should focus more on providing a product with more unique features and invest in creating a solid network of branches across the country which are fortified with skilled and service-oriented personnel who could persuade the customers in buying comprehensive insurance covers. Future researchers can also focus on income and educational level as moderators since both of which have an impact on consumer behavior as suggested in prior literature. Also, there is a possibility of widening their scopes by considering other types of insurance products and expand the geographical area as well.

A Comparison of Generalised Linear Modelling with Machine Learning Approaches for Predicting Loss Cost in Motor Insurance

This study explores the insurance pricing domain in the motor insurance industry, focusing on the creation of “technical models” which are essentially obtained after combining the frequency model (the expected number of claims per unit of exposure) and the severity model (the expected amount per claim). Technical models are designed to predict the loss costs (the product of frequency and severity, i.e., the expected claim amount per unit of exposure) and this is a main factor that is taken into account for pricing insurance policies. Other factors for pricing include the company expenses, investments, reinsurance, underwriting, and other regulatory restrictions. Different machine learning methodologies, including the Generalised Linear Model (GLM), Gradient Boosting Machine (GBM), Artificial Neural Networks (ANN), and a unique hybrid model that combines GLM and ANN, were explored for creating the technical models. This study was conducted on the French Motor Third Party Liability datasets, “freMTPL2freq” and “freMTPL2sev” included in the R package CASdatasets. After building the aforementioned models, they were evaluated and it was observed that the hybrid model which combines GLM and ANN outperformed all other models. ANN also demonstrated better predictions closely aligning with the performance of the hybrid model. The better performance of neural network models points to the need for actuarial science and the insurance industry to look beyond traditional modelling methodologies like GLM.

The study of the influence of service quality, service fairness and trust on customer loyalty in the Malaysian motor insurance industry

The objective of this study was to examine the influence of service quality and service fairness on customer loyalty in the Malaysian motor insurance industry. Further, it also aimed to examine how the above relationships mediated by trust. The quantitative research was conducted based on 399 completed survey questionnaires collected on convenience sampling basis within Klang Valley, Malaysia. The analysis of the study primarily based on partial least square-structural equation modelling (PLS-SEM) approach using the Smart PLS 3.0 software. The result indicated that both service quality, service fairness and trust had a significant positive influence on customer loyalty with trust appeared to be a significant mediation variable which partially mediates the relationship between the constructs understudied. This study observed that service fairness which mediated by the trust had a more substantial impact on the determination of customer loyalty for motor insurance relationship exchange as compared to service quality.

The study of the influence of service quality, service fairness and trust on customer loyalty in the Malaysian motor insurance industry

The study of the influence of service quality, service fairness and trust on customer loyalty in the Malaysian motor insurance industry

Short Review of the Motor Vehicle Insurance Industry In Malaysia

Motor vehicle insurance (MVI), which is the most effective and widespread means of protecting personal property, has attracted a great deal of attention. It is crucial to understand the current development of Malaysia’s motor vehicle insurance industry. Based on this context, this article examines the development model of the Malaysian motor insurance industry and its relationship with the Malaysian economic development. This article reviews ways to achieve targeted product promotion and customization of motor vehicle insurance (MVI) according to regional characteristics. The purpose of this article is to lay a solid foundation for promoting the development of the Malaysian automobile insurance industry and its relationship with motor production in Malaysia. The article investigates the MVI policy’s effect on the economy and the production of car motors in Malaysia compared with other advanced countries. In addition to that, the article highlights the effect of COVID- 19 on the MVI industry.

Measuring the effectiveness of intermediary loyalty programmes in the motor insurance industry: loyal versus non-loyal customers

PurposeThe insurance industry has not been able to effectively retain its customers and struggles to establish and maintain long-lasting relationships with them. The purpose of this paper is thus to identify the main factors that explain the cancellation of motor insurance policies by individual customers, considering the influence of intermediaries on their decisions.Design/methodology/approachThe data used in this research is based on a sample of 3,500 insurance policies that lapsed during the period of analysis between January and July 2017, against another sample of 3,500 policies that did not lapse, from a major insurance company in Portugal. Binary logistic regression was used for data analysis, using IBM SPSS software.FindingsAggressive tactics by insurance companies for customer acquisition may induce the cancellation of insurance policies. More valuable customers, the policies with higher premiums and recent claims, as well as the ancillary intermediaries and agents, are determinants of insurance cancellation. Conversely, the payment of policies by direct debit and without instalments reduces the probability of cancellations.Research limitations/implicationsThe main limitation of this study is the restriction on data access. Insurance companies are significantly resistant to sharing their customer data – including with academic researchers – even in an anonymised form.Practical implicationsThe paper highlights internal and external practices of insurance companies that should be reformulated to significantly improve their performance regarding product cancellation, related to customer information management, mistrust behaviours related to stakeholders and new value propositions that deepen the relationships with intermediaries.Originality/valueThis research developed a framework with which to identify the factors that are mainly associated with motor insurance cancellation and to predict its likelihood.

AN EFFECTIVE MACHINE LEARNING MODEL FOR CUSTOMER ATTRITION PREDICTIONIN MOTOR INSURANCE USING GWO-KELM ALGORITHM

The prediction of customers' churn is a challenging task in different industrial sectors, in which the motor insurance industry is one of the well-known industries. Due to the incessant upgradation done in the insurance policies, the retention process of customers plays a significant role for the concern. The main objective of this study is to predict the behaviors of the customers and to classify the churners and non-churners at an earlier stage. The Motor Insurance sector dataset consists of 20,000 records with 37 attributes collected from the machine learning industry. The missing values of the records are analyzed and explored via Expectation Maximization algorithm that categorizes the collected data based on the policy renewals. Then, the behavior of the customers are also investigated, so as to ease the construction process training classifiers. With the help of Naive bayes algorithm, the behaviors of the customers on the upgraded policies are examined. Depending on the dependency rate of each variable, a hybrid GWO-KELM algorithm is introduced to classify the churners and non-churners by exploring the optimal feature analysis. Experimental results have proved the efficiency of the hybrid algorithm in terms of 95% prediction accuracy; 97% precision; 91% recall & 94% F-score.

Antecedents of Customer Retention with Special Reference to Motor Insurance Industry in Sri Lanka

Antecedents of Customer Retention with Special Reference to Motor Insurance Industry in Sri Lanka

Risk-adequate motor underwriting of automated vehicles: a qualitative evaluation using German focus groups

The advent of automated vehicles is already taking place and will significantly disrupt the motor insurance industry. The shift from the human driver to the system as the driver cannot be reflected in the current insurance risk assessment. This call for an amendment of the insurance underwriting was discussed with German experts from both the primary insurance and reinsurance sector with their professional background on motor insurance. Based on the findings, we propose an alternative method to underwrite automated vehicles of level 4 & 5 using an enhanced telematics approach which considers new risk categories such as systems used and the transformed role of the driver as the general user of the automated vehicle.

The Automated and Electric Vehicles Act 2018 Part 1 and Beyond: A Critical Review

Abstract On 19 July 2018, the Automated and Electric Vehicles Act 2018 (AEVA) received Royal Assent. As motor vehicles are becoming increasingly technologically based, with driving aids having taken over many of the more mundane (and possibly dangerous) aspects of driving from the driver, it is imperative that legislation keeps pace to determine the responsibilities of the parties. Motor insurance provides protection for those involved with vehicles and who may suffer harm, injury, and loss due to the negligence of the actors. This is most frequently driver error, but may also include manufacturing defects, which result in deaths and less serious injuries. It is also here where the intersection between torts and insurance laws needs careful management. It would be particularly unfair to ask drivers or third-party victims of motor vehicle accidents to seek redress from a manufacturer for losses incurred during the actions of an autonomous vehicle. Consumer law has historically removed this burden from affected consumers and it is entirely sensible for the law to protect individuals in an emerging field—and perhaps even more so given the trajectory of vehicles with driver-enabled qualities and the numbers of vehicles currently featuring such innovations. Yet, the AEVA consists of aspects which are troubling in respect of the motor insurance industry’s dominance of this market, the application of compulsory insurance, and exclusions and limitations to responsibility which expose policy holders and victims to EU-breaching levels of risk.

Impact De-Tarrification in Modeling Motor Insurance Premium in Malaysia

De-tariffication has become a hot topic for Malaysian motor insurers after effectively implemented on 1 July 2017. Generally, the insurance companies need to set a rating factor for their premium before calculating the price on selected premium. Typically, these rating factors are based on the risk profile of the policyholder. That means, the price of the premium determined by the risk factors from the profile of the policyholder. The aim of this research to investigate the impact after de-tariff implemented among the motor insurance industry. This research also investigates the effect of de-tariff on the Good Service Tax (GST) in the premium calculation. Multiple Linear Regression (MLR) was used to determine the most significant rating factor that influence the calculation of the premium received by the motor insurance industry. Once these k rating factors and parameters are identified, the value of premiums can be calculated by taking into account these rating factors and parameters in the de-tariff formula and comparing with the existing model. The result of the study indicates that de-tariff model has lower premium compared to Malaysia tariff model. Furthermore, GST is also found to have a significant impact on the motor insurance premium, where policyholders are required to pay higher premiums than non-GST premiums. The results will help the insurance companies to find new formulas in considering new rating factors and improve the accuracy of premium calculations.

Driving to a future without accidents? Connected automated vehicles’ impact on accident frequency and motor insurance risk

Road traffic accidents are largely driven by human error; therefore, the development of connected automated vehicles (CAV) is expected to significantly reduce accident risk. However, these changes are by no means proven and linear as different levels of automation show risk-related idiosyncrasies. A lack of empirical data aggravates the transparent evaluation of risk arising from CAVs with higher levels of automation capability. Nevertheless, it is likely that the risks associated with CAV will profoundly reshape the risk profile of the global motor insurance industry. This paper conducts a deep qualitative analysis of the impact of progressive vehicle automation and interconnectedness on the risks covered under motor third-party and comprehensive insurance policies. This analysis is enhanced by an assessment of potential emerging risks such as the risk of cyber-attacks. We find that, in particular, primary insurers focusing on private retail motor insurance face significant strategic risks to their business model. The results of this analysis are not only relevant for insurance but also from a regulatory perspective as we find a symbiotic relationship between an insurance-related assessment and a comprehensive evaluation of CAV’s inherent societal costs.

Telematics System in Usage Based Motor Insurance

For the premium calculation and billing process in the motor insurance, current billing models are very general and not optimally tailored for the end users. Important parameters such as mileage, driving behavior and types of roads driven are not considered for the premium calculation. Development of advanced information and communication systems, significant drop in the technology cost of ownership, as well as the necessity for market differentiation in the insurance industry, facilitated the appearance of new billing models in the motor insurance industry. The purpose of this paper is to demonstrate underlying principles of the technology facilitating new billing models in the motor insurance industry. This paper gives an overview of the system architecture of one of the telematics systems offered and used on the market, as well as the data model used in the billing process. The potential of such a system is demonstrated through the real case project implemented in Eastern Europe.

Modelling the supply chain perception gaps

This study applies the research of perception gap analysis to supply chain integration and develops a generic model, the 3-Level Gaps Model, with the goal of contributing to harmonization and integration in the supply chain. The model suggests that significant perception gaps may exist among supply chain members with regards to the importance of different performance criteria. The concept of the model is conceived through an empirical and inductive approach, combining the research discipline of supply chain relationship and perception gap analysis. First hand data has been collected through a survey across a key buyer in the motor insurance industry and its eight suppliers. Rigorous statistical analysis testified the research hypotheses, which in turn verified the validity and relevance of the developed 3-Level Gaps Model. The research reveals the significant existence of supply chain perception gaps at all three levels as defined, which could be the root causes to under-performed supply chain.

Quest for Optimal Bonus-Malus in Automobile Insurance in Developing Economies: An Actuarial Perspective

This paper evaluates the bonus-malus system in practice in the Nigerian motor insurance industry. It would appear that the regulation is a bit fluid so that what actually looks like a bonus-malus system is more like a rule of thumb as operators do not honor the industry agreed tariff. This paper constructs an alternative bonus-malus scale that has reasonable penalties and that is yet commercially feasible. The model can easily be replicated for other developing economies.

The Motor Insurance Industry in Kenya: Adopting the No-Fault Insurance System

This research paper seeks to evaluate the Kenyan insurance industry which is based on the fault law, its shortcomings and the applicability of the no fault system to cure the ills of the fault insurance regime in this country. The study will also heavily refer to the New Zealand no fault law. The choice of reference for New Zealand is informed by the commonalities of the common law legal system in Kenya and New Zealand and the population of both countries. The fault insurance is always said to be a social symbol, a cultural mirror that reflects the morals of society. It focuses on the party at fault. The no-fault system on the other hand is an administrative remedy that is largely devoid of a moral content. This system is used to describe any type of insurance contract under which insured persons are indemnified for losses by their own insurance company, regardless of fault in the incident generating losses. Thus the injured parties are compensated by the insurance companies without proof of fault. They are also restricted in the right to seek recovery through the civil justice system for losses caused by other parties. The main goal of the no-fault insurance is that of lowering premiums costs by avoiding expensive litigation over the causes of accidents, while providing quick payments for injuries. In that regard this research paper will mainly focus on the two systems, identifying the pros and cons of each system and finally recommending which system would be suitable for Kenya. In some instances however, the two systems can be used interchangeably. In uncertainties, the standard liability procedure can be invoked or the courts can be allowed to handle cases in instances where the damages exceed a certain amount. This study will also evaluate this option in regard to the Kenyan industry. This research paper will seek to review the place of the injured party both under the fault and the no fault systems and the adequacy of damages in both instances and then provide the way forward. The main basis for the recommendation of adoption of the no fault system stems from the fact that, the no-fault system provides for prompt payment to accident victims regardless of how the accident happened or who was at fault. Unlike the current insurance regime in Kenya where an injured party has to file a suit to recover damages in regard of a motor accident, the no fault system offers faster settlement of damages and is more efficient as it avoids delays, expenses in litigation and uncertainty. In Kenya for example, seriously injured victims are collecting nothing from the insurance industry and most are getting inadequate compensation after several years of attending court hearing.

Understanding price competition in the German motor insurance market

This paper analyzes price competition in the German motor insurance market since 1994 and looks for evidence to back up a claim frequently found in the trade literature—that there have been two recent price wars in this industry, the first in 1996–1999, the second in 2005–2006. In a first step, we analyze the development of the German motor insurance market and compare it to that of other property-liability lines of business. In a second step the applicability of price war definitions found in the marketing literature to the German motor insurance market is checked. In a third step, a comparison to reference cases from other industries, where price wars have been subject to academic analysis, is conducted to complement the analysis. We conclude that, contrary to reports in the trade literature, the periods of 1996–1999 and 2005–2006 should be considered as times of intense competition in the motor insurance industry, not as times of price war.

Firm size distribution: Testing the “independent submarkets model” in the Italian motor insurance industry

This paper tests the presence of multiple independent submarkets in the Italian motor insurance industry. We find that independence effects are sufficient to induce a minimum degree of inequality in the size distribution of firms once submarkets are aggregated. These results are consistent with the predictions of Sutton [Sutton, J., 1998. Technology and market structure. MIT Press, Cambridge, MA.]. At the submarket level, some degree of inequality can be explained by a model of equilibrium price dispersion based on costly consumer search. Our findings show that Sutton's limiting approach and one based on a game theoretical analysis of an industry are good complements when the industry is made of several independent submarkets.

How Deregulation Shapes Market Structure and Industry Efficiency: The Case of the Italian Motor Insurance Industry

How Deregulation Shapes Market Structure and Industry Efficiency: The Case of the Italian Motor Insurance Industry