Electronic Payment Systems and Tele-banking Services in Nigeria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The paper examined electronic payment systems and tele-banking services in Nigeria. Thirty six out of the 89 banks in Nigeria as at the end of 2005 were selected for the study. Questionnaire method was used to gather data from bank workers. Findings revealed that there has been a very modest move away from cash. Some payments are now being automated and absolute volumes of cash transactions have declined. Connectivity via the use of Local Area Network (LAN) and wide area network has facilitated electronic transfer of funds. Thirty five out of the 36 banks studied have fully networked their systems to ease communication of account information. The use of Smart Cards, Point of Sales System and Computerized Credit Ratings were not very popular as less than half of the studied banks had fully adopted them. The least fully adopted technologies were ATM, Electronic Home and Office Banking and Telephone Banking. Low rate of adoption of these technologies might be due to low level of economic development, ineffectiveness of NITEL, epileptic supply of power, high cost, fear of fraudulent practices and lack of facilities necessary for their operation. The paper concluded that Tele-banking is capable of broadening the customer relationship, retain customer loyalty and enable banks to gain commanding height of market share if their attendant problems are taken care of.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it