Optimizing the Use of Information and Communication Technology (ICT) in Nigerian Banks
Notice bibliographique
Résumé
The study identified various Information and Communication Technology (ICT) in use and determined how they could be utilized for optimal performance on business transactions in the banking industry. The selected transactions for the study are deposit, withdrawal, enquiries, reference letters, opening and closing of accounts, funds transfer, special bills, loans and overdraft. The study covered 24 banks stratified into old and new generations. In all there were 14 old generation banks and 75 new generation banks as at December 2005. Proportional sampling technique was used to select samples from the two groups using ratio 1:5. Random sampling technique was then used to select on the basis of this ratio. Consequently, 4 ‘old’ and 20 ‘new’ generation banks were randomly selected. One thousand and two hundred customers were observed (Fifty customers from each of the selected banks) for the identified transactions. The Queuing model was thereafter used to measure the service standard and analyse the capacity utilisation in the studied banks. About half of the respondents (48.08%) in the studied banks came to withdraw while 34.75% came to make deposits. Special bills ranked least among the activities of customers in the studied banks. Only 23 out 1200 customers observed engaged in transfer of funds while 33 came for loan and overdraft. It was discovered that design of (ICT) in banking has not been adequately focused on deposit and withdrawal which are activities that directly impact on customer services. Products such as ATM, Electronic Data Interchange, Electronic Home and Office Banking and Telephone Banking that could have hastened these activities were the least fully adopted technologies. The rate of adoption of ATM was 16.7%, Electronic Home and Office Banking was 16.7% and Telephone Banking was 20.8%. The new generation banks appeared to be more efficient in utilising ICT to enhance performance. The traffic intensities in 50% of the old generation banks where ICT was not efficiently utilised were between 0.89 and 0.95 as against the theoretical limit of 0.80 thus making the queue of infinite length. The traffic intensity for all the new generation banks was less than 0.8. On the average, customers spent 23.01 minutes in the old generation banks as compared to 7.50 in the new generation banks. Similarly, average number of customers in the system in the old generation banks was 8.39 as compared to 2.56 in the new generation banks. The idle times in banks 3, 6, 12, 16, 17, 19, 21, 23 and 24 seemed to be too high, an indication of over-utilization or inappropriate allocation of products. The study concluded that banks should incorporate ICT into their strategic plans for effective performance in payment and delivery systems. Adoption and allocation of ICT should be based on proper analysis to determine the type, nature and extent of products required for effectiveness and efficiency.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».