Fraud and Performance of Deposit Money Banks
Bibliographic record
Abstract
Banks serves as an indispensable part of the financial system, performing a crucial role in intermediation which results in a flow of financial resources in an economy. However, the recurring nature of fraud has hindered the effective performance of Deposit Money Banks (DMBs). The broad objective of this study was to examine the impact of fraud on DMBs in Nigeria. The study was driven by the positivist research philosophy. Hence, the study adopted a quantitative research design using the ex-post facto strategy. Data was sourced from the Nigeria Deposit Insurance Corporation (NDIC) annual reports covering the period of 2006 to 2016. The Ordinary Least Square (OLS) was used to predict the impact of fraud on DMBs after fulfilling major regression assumptions. It was revealed that total fraud amount was negative, although insignificantly affect the performance of DMBs; the number of reported cases significantly and positively affect the performance of DMBs and lastly it was discovered that the total staff involved also significantly and positively affect the performance of DMBs in Nigeria. Therefore, the study concluded that the impact of fraud in the banking sector affects the performance of DMBs in Nigeria. The regulation and supervision of DMBs should be stricter, that is, the CBN and NDIC should tighten their grip in regulating and supervising so as reduce the increasing fraud incidence.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".