CHALLENGES FACING INSURANCE BROKERS IN KENYA

Purpose: The insurance industry, like other industries, has faced obstacles that have threatened its productivity, profitability, and capacity to compete against its rivals. The objective of this study to identify and discuss the challenges facing insurance brokers in Kenya. The aim of this work is to enable the readers understand the various challenges facing insurance brokers and their impact on the insurance industry. Methodology: A desktop literature review was used for this purpose. Relevant seminal references and journal articles for the study were identified using Google Scholar. The inclusion criteria entailed papers that were not over five years old. Findings: The study concluded that customer experience & satisfaction, workflow inefficiency, uncertainties in the market, unfavorable government regulation, cybersecurity risk and lead generation are some of the challenges that affect insurance brokers in Kenya. These challenges have greatly been influenced by the ever-changing technology that has revolutionized the workforce labour and business activities generally in all organizations and government influence on the regulations set by the Insurance Regulatory Authority. Unique contribution to theory, practice and policy: The study therefore recommended that insurance brokers should embrace the use of well-developed digital services that will enable them service their customers efficiently and meet their needs while the Insurance Regulatory Authority should come up with strategies that will help mitigate the unfavorable government regulations that affect insurance brokers.

Economic aspects of telemedicine

Introduction. For the recent years telemedicine (TM) has been actively integrated into daily life, and its growth was especially significant during COVID-19 pandemic. However, its economic component has its own specificities depending on the health financing system. The aim of this article is to analyze reasons of economical inefficiency of TM technologies in different health financing systems and to determine its further development path in economic terms. Results. It’s not justified to expect cost reduction of health care after integrating TM technologies into medical practice. In private health-care system TM technologies in the form of TM consultation aren’t cost-effective for beneficiaries. Representatives of private clinics use TM as a part of lead generation. From private clinics’ point of view, it’s cost-effective to use distant monitoring technologies integrated into programs of patients’ management. It’s economically appropriate to apply all varieties of TM including TM consultation on the voluntary health insurance (VHC) system. However, due to the low prevalence of VHC in Russia we can’t expect significant growth of TM in Russia based on using this sector. Conclusions. TM technologies require financing in its formative stage, implementation, development and further functioning phases.

Selective Optimization of Side Activities (SOSA) as an Efficient Approach for Generation of New Leads from Old Drugs

The selective optimization of side activities (SOSA) approach appears to be a promising strategy for lead generation. In this approach old drugs are used to generate new hits or leads. The objective of SOSA is to prepare analogues of the hit molecule in order to transform the observed “side activity” into the main effect and to strongly reduce or abolish the initial pharmacological activity. The idea of taking a molecule with a primary activity in humans and then enhancing a secondary effect through structural changes describes the most common implementation of SOSA. An advantage to starting a drug discovery program with molecules that have already been tested in humans is that those molecules have already satisfied many safety criteria. Such molecules also likely have favourable pharmacokinetic profiles. In the present review different successful examples of SOSA switches are summarized. We hope that the present review will be useful for scientists working in the area of drug design and discovery.

Rocchio Nearest Centroid and Normalized Neural Network based Lead Generation in Social Media Marketing

The employment of the internet and social media has transposed consumer behavior and the methods in which business organizations carry over their business. Social and digital marketing recommends noteworthy changes to business establishments via cost curtailment, enhanced brand understanding and surged sales. Despite enormous amount of potentialities, noteworthy disputes subsist from gloomy digital oral message in addition to trespassing and troublesome online presence of brand. Deep learning (DL) has fascinated escalated awareness owing to its notable processing power in tasks, to name a few being, speech, image, or text processing. Due to its aggressive evolution and extensive accessibility of digital social media (SM), examining these data utilizing conventional materials and methods is substantial or even complex. Also with the large growth in the volume of data, the multifariousness in data heterogeneity, are the most distinguished reasons, why and how the SM data mounted. In this paper we study the impact of tweets on distance learning to understand people’s opinions and to discover facts. However, adding redundant features minimizes the generalization capability of the model and may also minimize the overall accuracy of a classifier. We introduce Rocchio Nearest Centroid Laplacian Feature Selection model that combines Rocchio Nearest Centroid and Laplace function for selecting relevant features or tweets. Next an Arbitrary Normalized Attention-based Recurrent Neural Network Lead Generation algorithm is designed aggregating characterizations from preceding and succeeding tweets while generating lead via digital marketing tweet funnel. We validate and evaluate our method using data from distance learning dataset. Experiments and comparisons on distance learning data show that, compared to existing SMM methods, considering generalization capability and digital marketing tweet funnel results in improvements in processing time, lead generation accuracy and precision to a significant extent.