Acturial Science

The integration of cloud computing and artificial intelligence (AI) has significantly transformed actuarial science, particularly in life insurance pricing models. Traditional actuarial methods, often limited by static assumptions and computational constraints, are being replaced by dynamic, data-driven approaches that incorporate real-time customer behavior and external variables. AI-powered tools enable advanced risk assessment and predictive analytics, while cloud platforms provide scalable infrastructure for processing large datasets efficiently. This paper explores the evolution of actuarial models, highlighting the role of AI and cloud technologies in enhancing pricing accuracy, operational efficiency, and customer satisfaction. Key challenges, including data quality, ethical considerations, and regulatory compliance, are also discussed, alongside emerging trends and future opportunities. By addressing these challenges, the insurance industry can unlock the full potential of AI and cloud innovations, paving the way for more personalized and equitable insurance solutions.

In an ever-evolving banking landscape, understanding and effectively catering to the
diverse needs of merchants is paramount to maintaining a competitive edge. This project
report delves into the critical domain of merchant segmentation within the banking sector,
aiming to provide insights that enable financial institutions to enhance their merchantfocused
& customer-focused promotions. This study employs advanced data analytics and
machine learning techniques to analyze a comprehensive dataset encompassing a wide array
of merchant-related variables. Through a meticulous process, a classification segmentation
model is developed, dividing the merchant base into distinct and actionable segments. These
segments are defined not only by transactional behaviour but also by the Customer
demographic data such as Gender, Income, Customer Age and also the transaction related
data like Recency, Point and Merchant Category. The report presents a detailed analysis of
each identified segment, and leads to what are their expectations from their banking
partners. Additionally, it highlights the key drivers of merchant loyalty and satisfaction,
providing a strategic roadmap for banks to optimize their merchant-centric and customercentric
offerings. In conclusion, this project not only offers a comprehensive customer and
merchant segmentation framework but also provides actionable recommendations for
financial institutions in the banking sector. By tailoring their services to meet the distinct
requirements of each merchant segment, banks can foster stronger relationships, drive
profitability, and maintain their relevance in an increasingly competitive marketplace.

Pulmonary and respiratory researches play a crucial role for all implementation decisions in the human health. The studies were carried out by researchers to treat and prevent breathing disorders for all age groups. Therefore, this evaluation was performed in respiratory medicine publications of Middle East region. We conducted Medline/PubMed and SCImago journal ranking (SJR) searches using selected MeSH keywords to identify pulmonary and respiratory medicine papers published from 1996 to 2012. The SJR database, accessible free of charge, was selected as the most suitable source for ranking specifically. Furthermore, the trend analysis evaluation of clinical, basic and epidemiologic papers was performed. The used indicators were the global ranks of each country according to "number of document", "total number of citations", "citations per document", "Self-Citation", "H-index", and "international collaboration". The world rankings of these countries showed their level among 20-45. Turkey with a total of 2446 papers, 2102 citable publications, 16325 citations, 10.5 citations per paper, and the H-index of 49 took the 20st place among world countries. Iran with a total of 573 papers, 539 citable publications, 2044 citations, 13.24 citations per paper, and the H-index of 20 took the 20st place. The highest "citations per documents" and "international collaboration" among these countries were belonging to Egypt. The lowest "self-cite per documents" was belonging to Iran. Although the productions of scientific productions are neither qualitatively nor quantitatively compared with other countries, the global places of Turkey, Iran, Egypt and Saudi Arabia were 20th, 25th, 42th and 45th, respectively. As a result, scientific collaboration between these four big Muslim countries in Middle East region will boost their rankings. Furthermore, the results may improve perform of the health service policy makers in Muslim countries including Iran to do more effective attentions, management and establishing pulmonary and respiratory medicine research centers.

Commuting in big cities with heavy traffic is a real-world task faced by many on a daily basis. Finding a suitable path for commuting in real-life complex traffic networks is an important research problem with many applications. The existing work in this domain is based on the travel time and distance from source to destination. However, other than these two factors, there are many additional features that impact the overall travel time and its quality. Some of these additional features include environmental factors, road condition, and the traffic flow. The driving time can be minimized by selecting the most suitable path where there is less congestion and other travel related conditions are favorable. Commuting duration can increase even on the shortest path if there is congestion or the route is blocked. This work presents a mobile crowdsourcing-based model to find suitable commuting path(s) by considering the factors that directly or indirectly influence the overall travel time. Experiment in this work refers the naturalistic driving study to select the travel related features. An algorithm is proposed to find the suitable path from the user provided source to the destination using crowdsourced data generated using mobile application. Unlike other algorithms, the proposed approach can address the network peculiarities where travel cost is not only based on the distance between the nodes but other indirect factors are also involved. This work extracts all possible paths from a source to the destination and then computes the travel cost in terms of distance and satellite factors across the paths. This proposal is evaluated on eight large real-world road network data sets. A comparison is performed with four state-of-the-art pathfinding methods. These include, Floyd-Warshall algorithm, Bellman-Ford algorithm, open shortest path first algorithm, and Dijkstra algorithm. Empirical analysis shows that the additional factors incorporated in the proposed mobile crowdsourcing model while finding a suitable path have a significant impact on the travel time. The results show better performance of the proposed model than its counterparts.

This study discusses the impact of COVID on insurance sector. With COVID in its full swing, people have gotten homebound and became health conscious. In these times, the need to save their families because of the uncertainty of life became a great interest for them. Therefore, there is an evident response that people started buying Life Insurance policies to save the future of their families in case of any happening. With that response and increase in demand, theoretically, the supply should have been decreased and because of it, the premiums of policies would have risen. Because of this uncertainty, life insurance also started covering COVID-19 to attract more people, as this in any way is a deadly disease inflicted by nature. Death toll because of COVID was rising rapidly in 2020 and insurance companies also had to pay out a lot of benefits because of those deaths, which also lead to change in benefits given over the years and in 2020 specifically. This paper discusses the differences between the actual value of those premiums and Benefits and compared them with the calculated and expected level of these two features of Insurance policies, using regression analysis on multiple macro-economic factors, and the premiums and benefits themselves, also incorporating the mortality rate and other related changes because of COVID to reach comparable results.

Mata kuliah Statistika 2 merupakan mata kuliah yang mempelajari tentang statistika Inferensia. Setelah mengikuti mata kuliah statistika 2, mahasiswa diharapkan mampu untuk mengaplikasikan rumus dan konsep statistika inferensia untuk pengolahan data hasil penelitian dalam bidang bisnis, ekonomi, dan manajemen

Missov and Lenart (2013) derived closed-form solutions to the life expectancy and remaining life expectancy at age x when the mortality is governed by a Gompertz-Makeham hazard, which is a parametric model commonly applied to human mortality data at adult and old ages. However, the closed-form expressions provided by these authors are not correct. We provide, therefore, valid and correct expressions using elementary calculus. We also consider numerical studies using real data to show that the formulas we provide deliver satisfactory results.

There have been a number of fire outbreak cases recorded in the KNUST area that has brought about loss of lives to inhabitants and loss of properties. Some routes within the district can be reconstructed into bitumen roads so that fire attackers can traverse through the district in order to prevent fire incidents. The main objective in this study is finding the minimum travel distances and shortest paths from the Knust Fire Station to all other towns in the district of Kumasi Metropolitan area in the Ashanti Region of Ghana. Shortest path algorithms of various variants have been discussed with examples in this study as well as review of abstracts of other related books and articles. The Floyd's Algorithm has been explained in which it maximize the source node minus the destination node. It was found out that at each destination used in the objective function, the Floyd's algorithm proceeds to obtain minimum distances to every other destination. The introductory part of the paper deals with the theory of searching for optimal routes in transport networks, including a description of each type of optimization tasks. The aim of the article is demonstration of Floyd algorithm application to find the minimal paths from each node to another in network graph-in our case the network represents traffic model of road network in the region of Knust.

The output in research of South Africa is measured in terms of citable documents and it is investigated if this output is in line with what should be expected from a country with the population and economy of South Africa. The expected relationship is calculated by making use of the data of the top 86 countries. It was found that the research output of South Africa is very much in line with what should be expected.