International Journal of Academic Research in Accounting Finance and Management Sciences · 2018 · 12 citations · 38 references
BusinessAccountancyRisk ManagementAuditingBankingFinancial Risk ManagementBank Risk ManagementFinancial Statement FraudFraud DetectionFraud Risk ManagementInternal AuditInternal AuditingAuditor’s ReportBank Performance MeasurementBanking Sector AuditingData ScreeningLikert Scale DesignLikert Scale DevelopmentMultivariate Data AnalysisRisk Culture
Fraud poses a major threat to the global economy, demanding heightened scrutiny from forensic accountants, auditors, and anti‑graft bodies. This study aims to outline the data screening, editing, and preparation steps preceding a multivariate analysis of how fraud risk management and risk culture affect Nigerian bank performance. A survey of 417 senior risk‑management, internal‑control, and branch‑manager respondents used a 5‑point Likert scale, and the data were cleaned and tested for missing values, outliers, normality, collinearity, common‑method variance, and non‑response bias in SPSS v23. The data met all multivariate‑analysis assumptions, confirming suitability for subsequent analysis.
Fraud has become the most viable threat to the global economy requiring maximum attention of forensic accountants and traditional auditors, as well as anti-graft bodies worldwide. The primary objective of this paper is to discuss the process of screening, editing and preparation of initial data collected, before any further multivariate analysis of the study regarding the relationship between fraud risk management and risk culture on bank performance. A survey method was employed to administer a total of 417 questionnaires to either the senior officer in the risk management department, internal control department, and branch manager of each bank in the Nigerian banking sector. The questionnaire is a 5 point Likert-scale. The data was analyzed using Statistical Package for the Social Sciences (SPSS) version 23 (v23). The initial data screening and cleaning were conducted as an attempt to fulfill the assumptions of multivariate analysis. Therefore, the present study assessed missing values, outliers, normality test, collinearity test, common method variance, and test of non-response bias with the help of SPSS V23. The results have shown that the data satisfied the multivariate analysis assumptions which indicate the fulfillment of conditions for further multivariate analysis.
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