The Implementation of Fraud Risk Assessment and Anti-Fraud Strategy in Government Institution XYZ

Government Institution XYZ is one of the government institutions trying to build bureaucratic reform and minimize fraud risk. This study attempted to conduct a fraud risk assessment to identify, analyze, evaluate, and determine appropriate anti-fraud strategies to various fraud risk scenarios that may occur in Government Institution XYZ. The research was conducted qualitatively with a case study approach. The data were collected through document analysis, questionnaires, interviews, and Focused Group Discussion (FGD). Based on the FRA results, researchers identified thirteen fraud risk scenarios that organization needs to anticipate. Considering the organization’s risk appetite, there are two very high-level risk scenarios, four high-level risk scenarios, four medium-level risk scenarios, and three low-level risk scenarios among all of these risk scenarios. Several anti-fraud strategies need to be implemented to reduce fraud risk, including preventive, detective, and responsive strategies by optimizing existing and other relevant anti-fraud strategies.

Factors associated with the adoption of data analytics by internal audit function

Purpose The benefits of data analytics in the internal audit function (IAF) are clear; less is known about IAF adoption of analytics. The purpose of this study is to examine the factors driving IAF adoption of analytics. Design/methodology/approach The Common Body of Knowledge of Internal Auditing Database (IIA, 2015) provides auditor responses on key variables of analysis. Findings The results of this study indicate the most critical adoption factor is data-specific IT knowledge in the IAF. Critical thinking skills and business knowledge of chief audit executive (CAEs) also contribute to adoption. IAFs with fraud risk detection responsibly are more likely to adopt. IAFs in technologically advanced cultures are more likely to adopt analytics. Originality/value The results of this study document the critical factors driving adoption of audit analytics, benefitting both industry and research.

How Does an Audit or a Forensic Perspective Influence Auditors’ Fraud-Risk Assessment and Subsequent Risk Response?

This study examines whether priming auditors with a forensic perspective improves their fraud-risk assessments and subsequent audit-plan responses. We contribute to the literature by investigating a potential improvement in fraud detection that encourages auditors to take a forensic specialist’s perspective, while retaining the audit tenets of efficiently identifying and responding to risk. We prime auditors with a forensic perspective and compare their fraud performance to unprimed auditors in both low- and high-risk contexts, finding primed auditors assess fraud-risk significantly higher in all fraud-risk environments. In a high-risk environment, primed auditors propose a more appropriate audit-plan response. Relevant to fraud detection, these audit-plan modifications were consistent with those determined by a panel of audit and forensic experts. They exhibit a sensitivity in the low-risk environment, whereby their risk response is similar with that of the unprimed auditors. Finally, we find perspective-taking affects risk response through its influence on risk assessment.

Scoring to estimate the financial statement fraud risk during the audit

Subject. This article assesses the propensity for material misstatement risk due to unfair actions of persons charged with the financial statements preparation, based on their behavioral traits. Objectives. The article aims to develop a scoring type methodology for identifying the propensity for material misstatement risk due to unfair actions of persons charged with the financial statements preparation. Methods. For the study, we used a multidimensional statistical method of discriminant analysis based on empirical data from an author-conducted survey of 515 employees charged with the financial statements preparation in companies. Results. The article presents a two-stage methodology that helps estimate whether a person has traits associated with a hyperpropensity for financial statements fraud risk. Conclusions and Relevance. The developed methodology for detecting the fraud risk is easy to use. It gives the result in binary form and does not violate the principles of audit ethics. The estimated material misstatement risk due to unfair actions makes it possible to justify the need for appropriate audit procedures when developing a strategy and audit plan.

Impact of Forensic Accounting on Financial Fraud Detection in Deposit Money Banks in Nigeria

The study examines the impact of forensic accounting on financial fraud detection in Deposit Money Banks (DMBs) in Nigeria. Survey research design was employed for the study with extensive reliance on primary data obtained through the use of structured Likert scale questionnaire. The data were tested using descriptive statistics and regression analysis on Statistical Package for Social Sciences (SPSS version 20.0). The study findings showed that forensic accounting techniques of conducting investigation, analyzing financial transactions and reconstructing incomplete accounting records have significant effect on financial fraud detection in deposit money banks in Nigeria. In the light of the study findings, the following recommendations were provided; more forensic accountants should be employed by DMBs in Nigeria to assist curb modern day financial fraud brought about by advancement in technology. The Central Bank of Nigeria (CBN) should in collaboration with all financial institutions establish an electronic fraud risk information center staffed with forensic accountants. DMBs should incorporate automated control measures such as biometric authentication of transactions to serve as deterrent for fraud occurring.

An Enhanced Cascading Model for E-Commerce Consumer Credit Default Prediction

As an important global policy guide to promote economic transformation and upgrading, the upsurge of E-Commerce has been continuously upgraded with continuous breakthroughs in information technology. In recent years, China’s e-commerce consumer credit has developed well, but due to its short time of production and insufficient experience for reference, credit risk, fraud risk, and regulatory risk continue to emerge. Aiming at the problem of E-Commerce Consumer Credit default analysis, this paper proposes a Fusion Enhanced Cascade Model (FECM). This model learns feature data of credit data by fusing multi-granularity modules, and incorporates random forest and GBDT trade-off variance and bias methods. The paper compares FECM and gcForest on multiple data sets, to prove the applicability of FECM in the field of E-commerce credit default prediction. The research results of this paper are helpful to the risk control of financial development, and to construct a relatively stable financial space for promoting the construction and development of E-Commerce.

An Enhanced Cascading Model for E-Commerce Consumer Credit Default Prediction

As an important global policy guide to promote economic transformation and upgrading, the upsurge of E-Commerce has been continuously upgraded with continuous breakthroughs in information technology. In recent years, China’s e-commerce consumer credit has developed well, but due to its short time of production and insufficient experience for reference, credit risk, fraud risk, and regulatory risk continue to emerge. Aiming at the problem of E-Commerce Consumer Credit default analysis, this paper proposes a Fusion Enhanced Cascade Model (FECM). This model learns feature data of credit data by fusing multi-granularity modules, and incorporates random forest and GBDT trade-off variance and bias methods. The paper compares FECM and gcForest on multiple data sets, to prove the applicability of FECM in the field of E-commerce credit default prediction. The research results of this paper are helpful to the risk control of financial development, and to construct a relatively stable financial space for promoting the construction and development of E-Commerce.

How could external auditors assess the rationalization of fraud?

Purpose This study aims to explore methods that external auditors can use to assess the rationalization of fraud in fraud risk assessment in auditing. Design/methodology/approach An online questionnaire was used to collect data from 150 Big 4 auditors. Findings The results reveal a total of 18 methods that auditors can use to assess the rationalization of fraud. However, some methods were recommended more than others by the auditors in this study. These methods include incorporating the assessment of rationalization into the assessment of motives for fraud and integrity, understanding the client’s business and regulatory environment, inquiring management and the board of directors about past fraud cases and observing management responses and reactions during auditors’ inquiry about fraud-related matters. Practical implications The guidance provided by this study could help enhance auditors’ skills in assessing fraud risks, which, in turn, may increase the likelihood of detecting fraud. The guide could also be helpful for audit firms in their fraud training programs. Originality/value This study is the first to explore methods for assessing the rationalization of fraud by drawing on the experience and insights of Big 4 auditors.