Modelling MTPL insurance claim events: Can machine learning methods overperform the traditional GLM approach?

Pricing an insurance product covering motor third-party liability is a major challenge for actuaries. Comprehensive statistical modelling and modern computational power are necessary to solve this problem. The generalised linear and additive modelling approaches have been widely used by insurance companies for a long time. Modelling with modern machine learning methods has recently started, but applying them properly with relevant features is a great issue for pricing experts. This study analyses the claim-causing probability by fitting generalised linear modelling, generalised additive modelling, random forest, and neural network models. Several evaluation measures are used to compare these techniques. The best model is a mixture of the base methods. The authors’ hypothesis about the existence of significant interactions between feature variables is proved by the models. A simplified classification and visualisation is performed on the final model, which can support tariff applications later.

Comparing different ranking functions for solving fuzzy linear programming problems with fuzzy cost coefficients

In many applications of linear programming, the lack of exact information results in various problems. Nevertheless, these types of problems can be handled using fuzzy linear programming. This study aims to compare different ranking functions for solving fuzzy linear programming problems in which the coefficients of the objective function (the cost vector) are fuzzy numbers. A numerical example is introduced from the field of tourism and then solved using five ranking functions. Computations were carried out using the FuzzyLP package implemented in the statistical software R.

Test for asymmetry on the ex-pump price of premium gasoline in Ghana, Kenya, and Colombia

Once again, the World has been faced with an oil price shock as a result of the SARS-CoV-2 coronavirus pandemic. This has resurrected an old debate of whether retail fuel prices adjust significantly to either increases or decreases in international crude oil prices. With many countries moving towards the deregulation of their petroleum sub-sector, the impact of the US dollar exchange rate on retail fuel prices cannot be overlooked. This study investigates the rate at which positive and negative changes in international Brent crude oil prices and the US dollar exchange rate affected the increases or decreases in the ex-pump price of premium gasoline between February 2012 and December 2019. Using a non-linear auto-regressive distributed lag model, the exchange rate was found to play a significant role in fluctuations in the retail price of premium gasoline in Ghana and Colombia in the long run, howev-er, the rate of adjustment between the negative and positive changes was not significant, dispelling the perception of price asymmetry. There was no significant relationship between the ex-pump price of premium gasoline and the international Brent crude oil price in Ghana and Kenya in the long run. This study recommends that the aforementioned countries prioritise the creation of ex-change rate buffers to prevent exchange rate shocks that may affect retail fuel prices.

Providing new impetus to corporate well-being programmes: improving life expectancy through risk assessment

Diseases of the circulatory system are leading causes of death, which compel stakeholders to lessen cardiovascular risks by utilising more effective prevention. These risks can be estimated based on gender, age, smoker status, systolic blood pressure, and total cholesterol. Artificial neural networks enable modelling of 10-year cardiovascular mortality rates. Understandable communica-tion of potential gains in life expectancy may enhance health consciousness through mitigating behavioural risks. The reproduction of death statistics requires the adjustment of the recommended probabilities for the occurrence of fatal cardiovascular events. This study deals with countries at high and low cardiovascular risk, selecting Hungary and the Czech Republic (high risk) and Austria (low risk). In Hungary, the gains in life expectancy are (43.4 – 36.2 =) 7.21 years for fe-males and (37.4 – 28.0 =) 9.4 years for males, both aged 40. These figures moderate to (21.2 – 15.6 =) 5.72 and (17.1 – 11.3 =) 5.8 years for elderly people aged 65, respectively. The Czech Republic represents an interim phase between the two other countries regarding ad-vancement in life expectancy, the respective gains exceed the Hungarian values: (45.8 – 37.8 =) 8.0, (39.7 – 29.7 =) 10.0, (23.0 – 16.6 =) 6.4, and (18.2 – 12.3 =) 5.9 years. In contrast, a 40-year-old woman may benefit from an additional (46.6 – 41.3 =) 5.3 years in Austria, while the corresponding accrual for men is (42.3 – 35.7 =) 6.6 years. On reaching 65 years, the increment is (23.4 – 19.3 =) 4.1 and (20.0 – 16.1 =) 3.9 years.

The effect of socio-economic status and environmental factors on the academic performance of students at Asmara College of Education

This study examines whether various environmental factors and the socio-economic status of families influence academic achievement (cumulative grade point average) of students at Asmara College of Education (Asmara, Eritrea). A questionnaire survey was conducted among students to gather information on this subject. Descriptive statistics, crosstabs, Person chi-squared tests were used and analysis of variance was performed by the authors to study data. The results indicate that none of the variables examined, except gender of students and learning resources pro-vided by their families to them, affect cumulative grade point averages. Many students perceive that their academic achievement could be improved instead by building intrinsic motivation, plan-ning, and effective time management. Furthermore, Eritrea provides free education at all levels, including higher institutions, which thereby minimizes socio-economic constraints and provides equal opportunities to all citizens. However, parents should pay attention to their children to im-prove their academic performance, while colleges should also support students by providing a conducive environment for learning.

Leader motivating language – The fuel for employee vitality

This study investigates the impact of organizational culture on employee vitality determined by leader motivating language. It is common knowledge that organizations are known for the culture they develop and maintain for their employees’ well-being and vitality. The prime focus of learning organizations is to provide their employees with a vibrant culture where they feel comfortable and grow as professionals. Culture alone does not guarantee employee satisfaction and vitality – there are other factors that play a role. From all the different factors, in this study, leader motivating language is taken as a pivotal one, which can either disturb or improve employee vitality at work. The theoretical background is built on the motivating language theory, which provides a model, helping to understand how the language leaders use, that is, speech communication affects the organization’s employees. A survey was conducted to collect data from various banks and multinational firms in Pakistan through random sampling – 270 responses from people working in these sectors, for which all the three variables, leader motivating language, organizational culture, and employee vitality, could be measured easily, were analysed. The respondents’ average length of service in their company was nearly five years and their mean age was 26.2 years. The results of this study show that leader motivating language has a positive impact on employee vitality at work and strengthens the relationship between organizational culture and employee vitality.

Macro-level road network evaluation by fuzzy signature rule bases

In our fast-growing world, we need to create increasingly efficient systems to ensure further growth and sustainability. This also applies to transportation, where a key limitation is the bottle-necks of road network capacity. To eliminate, or at least, to moderate these bottlenecks, they must first be localised. In this case study, a model is proposed to objectively identify the weak points of the road infrastructure in the Western Hungarian region, a typical part of the Hungarian road net-work, based on automated data input. This way, there is no need to visually analyse the road net-work on site, but it is possible to evaluate the available information and suggest efficient measures from the distance. The model is suitable for general application, meaning it can serve other regions or countries as well, and enables macro-level decision-makers to take steps to eliminate those weak points. A fuzzy signature rule base is applied by the authors, which systematically maps and models the various attributes of the road network. The model currently contains more than 20 independent variables as inputs, but they can be easily expanded or replaced if further inputs need to be included.

Statistical comparison of typical Hungarian administrative public service processes using key performance indicators

This study aims to comparatively analyse the front office operations of two Hungarian gov-ernment windows, one located in a capital city district and the other in a county district centre, to examine the difference in the perceived service levels. First, through an international literature review, the study describes the background of the government window system and the importance of key performance indicators (KPIs). In addition, it demonstrates how KPIs can be measured in a public service context, regardless of the type and complexity of a given service. Second, the study provides a detailed statistical analysis and a comparison of the typical administrative public services related to waiting times, processing times, and lead times. Moreover, it offers an analogy of industrial service process management by presenting how the selected meth-ods and measures can be used to review processes related to an industrial, a manufacturing, or a public service, following a holistic management approach. The study contributes to the literature by using KPIs of the private sector and industry in public service processes and shows how these common KPIs can be measured in the public service context to provide valuable insights into service processes. Finally, it demonstrates the differences between the KPIs of the government windows to help legislators to increase the efficiency and effectiveness of services.

Population dynamics and economic growth in Kenya

Since the publication of the Malthusian population principle, the overall impact of population change on economic growth has provoked huge debates that have challenged pessimistic and optimistic postulations. Pessimists’ research posits that population growth puts a strain on government services. Conversely, optimists agree that population increase is a key component of economic growth through expanded specialisation and increased labour resources. Considering these conflicts in the literature, the Malthusian population principle and the partial least square structural equation model (PLS-SEM) are used by the author to assess the impact of population dynamics on economic growth in Kenya by incorporating the effects of education and health expenditures. The results show that population dynamics influence economic growth both directly and indirectly, with their indirect impact reinforcing the pessimistic argument that an increase in population dynamics growth has a negative effect on economic growth. Without doubt, the Kenyan working population has high health- and education-related needs, which is causing a slowdown in economic growth. The study suggests that state agencies develop and implement various policy programs focusing on public health and active involvement of the population in economic activities.

Startup ecosystem rankings

The number, importance, and popularity of rankings measuring innovation performance and the strength and resources of ecosystems that provide its spatial framework are on an increasing trend globally. In addition to influencing the specific decisions taken by economic actors, these rankings significantly impact the development of innovation-related policies at regional, national, and international levels. The importance of startup ecosystems is proven by the growing scientific interest, which is demonstrated by the increasing number of related scientific articles. The concept of the startup ecosystem is a relatively new category, the application of which in everyday and scientific life has been gaining ground since the end of the 2000s. In parallel, of course, the demand for measurability and comparability has emerged among decision-makers and scholars. This demand is met by startup ecosystem rankings, which now measure and rank the performance of individual ecosystems on a continental and global scale. However, while the number of scientific publications examining rankings related to higher education, economic performance, or even innovation, can be measured in the order of thousands, scientific research has so far rarely or tangentially addressed the rankings of startup ecosystems. This study and the related research intend to fill this gap by presenting and analysing the characteristics of global rankings and identifying possible future research directions.