The Independent variable in this study is forensic accounting techniques, which include financial ratio analysis, trend analysis, data mining, critical points audit, and relative size theory.

The Dependent variable is financial fraud detection.

The concept of fraud in financial statements:

Financial statement fraud is when management of the companies intentionally misleads users of published financial statements, especially investors and creditors. These practices are considered illegal and unethical and are carried out through deliberate falsification of accounting records (transactions, balances, disclosure of financial statements and misapplication of international financial reporting standards). This type of fraud involves intent and deception by a team of perpetrators with a set of well-planned schemes. financial statement fraud mainly includes the following:

1- Falsifying accounting books, supporting documents, or commercial transactions or events, or other important information used to prepare financial statements.

2- Intentionally manipulation when applying or interpretation or implementation of accounting standards, principles, policies and methods used to measure economic events, business transactions and disclosures (Rezaee, 2005).

3- Provide incomplete disclosures regarding accounting standards, principles and practices and relevant financial information.

4-Using aggressive accounting methods by applying illegal profit management practices.

5- To get benefits of loopholes which are avilable of current accounting standards, which have become very detailed and easy to circumvent to hide their true financial performance and position (Anbalagan, 2014).

Fraud theory explains the reasons of engaging individual in financial fraud or any other type of fraud. This theory explains that there are three possible predection that push individuals to practice financial fraud(Albrecht et al. ,2014): the first one is perceived pressure, when senior managers may feel pressure to meet or exceed investors’ expectations(Albrecht et al. ,2014), where Shareholders anticipate the company’s performance and use financial statements to measure ite and compare it to their prior expectations, which in turn affects the market price of the company’s stock(Brennan and McGrath, 2007). In addition to the job security and financial compensation of managment depend on maintaining strong financial performance of the company and high its stock prices.

Fraud theory explains why an individual engages in financial or any other type of fraud. This theory shows that there are three possible expectations that lead individuals to engage in financial fraud (Albrecht et al., 2014). It also includes Auditing Standard SAS (99) (Hogan et al., 2008). The first one is perceived pressure: this occurs when senior managers feel pressure to meet or exceed investors’ expectations (Albrecht et al., 2014). Shareholders expect the company’s performance, and based on the published financial statements, they measure the company’s actual performance and make a comparison between the actual performance and the xpected one in advance, which in turn affects the market price of the company’s shares (Brennan and McGrath, 2007).

In addition, job security, managers’ continuity at work, and management’s financial compensation (bonuses) depends primarily on maintaining the company’s strong financial performance and high stock prices. However, it is important to avoid using fraudulent means to achieve this, and the possibility of committing fraud should not be considered a realistic possibility without considering facing the consequences (Albrecht et al., 2014). Thus, the motivation or pressure faced by fraud perpetrators is related to the expected negative consequences when a company’s true financial performance is revealed. The second is perceived opportunity, which is generated when an individual sees a favorable opportunity to commit fraud. He may consider initiating illegal actions. This theory is based on perceptions, that is, when pressures and opportunities are viewed as real, meaning that pressures and opportunities may not be real, but they are viewed as real. The third motive is logical justification, as fraud perpetrators often attempt to reconcile their unethical behavior with their core values by searching for excuses for their thoughts, intentions, and actions through logical justifications in order to present themselves as not violating their ethical standards (Albrecht et al. ,2014), as some research has identified six motives for fraud. The three additional motivations are competence, arrogance, and deterrence. Competence refers to a person’s ability to overcome a company’s internal controls. While arrogance refers to the superiority complex of the person committing the fraud and his belief that the company and external auditors are unable to detect it, while deterrence refers to the person ignoring the potential consequences of his actions as a result of his arrogance. Understanding these motivations (perceived pressure, perceived opportunity, justification, competence, arrogance, and deterrence) can be an aid to the forensic accountant in determining the type of person behind the fraud and what to look for during the investigation (Nigrini, 2020). Therefore, shareholders and boards of directors, when exercising their oversight role, aim to reduce the perception of fraud opportunities by implementing systems and controls, such as audit procedures, which are supposed to make it more difficult for fraudulent activities to continue. However, some individuals, especially high-powered executives, may believe that they are able to manipulate and control their environment.

Forensic Accounting Techniques:

Financial ratio analysis This approach involves performing ratio to evaluate financial data on a historical, industry, or benchmark basis. The purpose is to detect fraud by studying data patterns to identify potentially deceptive transactions (Oyedokun, 2022). In recent decades, orensic accountants have increasingly turned to analytical procedures due to their practicality and general benefits. The decision to use of analytical procedures depends on their effectiveness. of these procedures. Success in forensic accounting relies on identifying financial and non-financial measures that are connected to the manipulated financial information. The main steps involve developing expectations and comparing them tothe actual results to identify any discrepancies Data analysis and financial ratios can be useful in detecting fraud cases. Ratio analysis also enables auditors to compare data from two different years, allowing them to identify the reasons for any differences in the financial statements (Jain and Lamba, 2020).

Time series tests, specifically trend analysis, are crucial forensic accounting methods for detecting fraud The focus is on identifying unusual transactions. By comparing current transaction records those of the previous year, fraudulent transactions can be easily identified. This method is particularly useful in determining if the level of sales is increasing at the same rate as the level of bad debts in the business. Businesses can use trend analysis to compare sales data and bad debts over time. This can help to identify fraudulent sales transactions or manipulation of the system to improve turnover. It is important to use trend analysis over certain period to detect such fraudulent changes (Oyedokun, 2022).

Data mining is the process of identifying deviations, patterns, and correlations within large data sets to predict results. It can help in detecting fraud faster (Bassey, 2018) through data extraction, classification, compilation, regression analysis, and data retrieval. By using data mining techniques, patterns can be identified based on available historical data, providing a basis for future predictions (Jain and Lamba, 2020). Although this technology may be considered expensive for small and medium-sized companies, they can still benefit from it by using Microsoft Office programs. According to Nigrini’s study (2020), Access and Excel programs are useful for analyzing small and medium-sized cases.

The relative volume factor can be used to detect unusual transactions and fluctuations resulting from errors or fraud. The text describes the concept of the largest-to-second-largest ratio in a data set, which is used to identify anomalies in transactions, such as exceeding credit limits or violating company policies (Bassey, 2018).

Computer-aided auditing techniques involve the use of computers to automate auditing processes. This typically includes basic office software like spreadsheets, word processors, and text editors, as well as specialized auditing software such as ACL, Arbutus, and EAS. More advanced software packages that include statistical analysis may also be used. Computer-aided audit techniques assist auditors in performing various functions, including data queries, data segmentation, sample extraction, identification of missing sequences (missing values), statistical analysis, and identification of duplicate transactions. These techniques can also aid in the detection of fraud by conducting and creating analytical tests, data analysis reports, and continuous monitoring (Okafor and Obiora, 2022).

Model Specification: This section specifies the model used to examine the determinants of fraud detection in forensic accounting techniques.

FRD = f (DM, RAS, TRD, CPA, RSF)

It is stated econometrically as:

FRD = β0+β1 RAS +β2 DM +β3 TRD + β4 CPA + β5 RSF +ε

FRD = β0+β1RAS +β2DM +β3TRD + β4CPA + β5RSF + β6NYE +ε

Where:

FRD = Financial Fraud Detection )Umar et al., 2017)

DM = Data Mining (Eko,‏ 2022).

RAS = Financial Ratio Analysis (Eko,‏ 2022).

TRD = Trend Analysis (Eko,‏ 2022).

CPA = Critical Point Audit (Ijeoma, 2015; Moses, 2019).

RSF = Relative Volume Factor (Ijeoma, 2015; Moses, 2019).

NYE = Number Of Years Of Experience.

ε = Random Error.

β1 – β6 = Unknown coefficients to be estimated