The FDP mirror framework for financial statement fraud risk assessment: integrating deterrence and analytical detection

Financial statement fraud remains a persistent challenge for auditors, particularly in environments with weak deterrence and complex financial disclosures. Auditing standards such as ISA 240 require auditors to integrate professional scepticism, fraud risk assessment, and analytical procedures. However, conventional audit approaches often treat behavioural deterrence assessment and analytical detection as separate considerations. This study empirically evaluated the Fraud Deterrence Propeller Mirror (FDP Mirror) as an applied audit framework that integrated deterrence maturity assessment with analytical procedures for financial statement fraud risk assessment. Using data from corporate entities and public sector organisations in Indonesia, PLS-SEM was employed to assess deterrence maturity, while logistic regression and machine learning techniques were used to evaluate fraud detection performance. The findings indicated that stronger deterrence maturity was associated with improved governance integrity, while hybrid analytical models combining financial indicators, anomaly testing, and narrative analysis demonstrated stronger fraud detection capability than conventional assessment approaches. The results suggested that fraud risk assessment was strengthened when behavioural governance conditions and analytical evidence are evaluated jointly. This study contributes to auditing literature by extending the practical interpretation of ISA 240 and enhancing the integration of behavioural governance assessment and analytical procedures in fraud risk assessment.