Effect of Islamic Insurance on the Growth of the Insurance Industry in Kenya
Notice bibliographique
Résumé
The Kenyan insurance market wrote KES.100 billion of Gross Direct Premiums in the year 2011. It has grown at an average rate of 16% p.a. over the last 5 years. The market comprises of 47 insurance companies, transacting long-term and short-term insurance business. In addition, there are over 140 insurance brokers operating in the Kenyan insurance market. In Kenya the penetration rate is 3% for a population of 40 million while India at 4% penetration for a population of over a billion and contrasts with South Africa with a penetration of 16% for a population of 50 million. This shows the importance of having an insurance sector which can add more to economic development of the country, which signifies a huge potential for the insurance business in the country. The industry's insurance premiums grew by 16.4% during the first quarter of 2015. The 2015 quarter one premiums stood at KES 50.41 billion growing from KES 43.29 billion. The premium income reported under life insurance business amounted to KES. 15.98 billion while general business premiums were 34.43 billion. This study aimed to establish the effect of Islamic Insurance (Takaful) on the growth of the insurance industry in Kenya. The study aimed to fulfill following objectives; to find out the effect of General Takaful on the growth of insurance in Kenya, to establish the effect of Family Takaful on the growth of insurance in Kenya, to determine the effect of health takaful on the growth of insurance in Kenya and to investigate the effect of Re-Takaful on the growth of insurance in Kenya. This study adopted a descriptive design. The population of this study was all insurance companies in Kenya. Purposive sampling was used to select the insurance companies that offer Islamic insurance (Takaful) products. There is only one Insurance company Islamic insurance products and that is Takaful Insurance of Africa which began its operations in Kenya in 2011. Takaful Insurance of Africa sells its policies directly or through agents, brokers and commercial banks. The study used secondary data from insurance companies from 2011 when the first insurance company (Takaful East Africa) begun offering Takaful products, to 2015. Data was analysed using Statistical Package for Social Sciences (SPSS). Results showed that there was a significant positive relationship between Islamic insurance and the growth of Kenya's insurance industry. Specifically, it was found that general re-takaful had the greatest impact on insurance growth with family takaful having the least effect. This study recommends that industry players invest more in marketing as well as innovation to come up with a wider range of general takaful products and to increase awareness in the market to increase its uptake. Family Takaful has been found to be the least consumed Islamic insurance product. There are still a lot of opportunities in Kenya for this kind of product. Industry players should increase the awareness campaigns to increase its uptake. The majority of Kenyans still do not have medical insurance. This study recommends that Islamic insurance companies ought to take this advantage and invest more on the campaigns to sell health insurance to Muslims and non-Muslims alike. The study therefore recommends for the formation of a fully-fledged reinsurance company for takaful products.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».