Fraud Detection Methods in Banking in Egypt Gain Momentum Amid Rising Financial Crimes

A Growing Concern for Banks and Regulatory Bodies in Egypt

The digital transformation of the global economy has accelerated, resulting in an increasing concern for financial fraud in banks and regulatory bodies in Egypt. Annual losses from such crimes are now estimated to run into billions of dollars worldwide.

Researchers Identify Data Mining Techniques as a Key Tool in Preventing and Detecting Financial Fraud

A recent study by researchers at Helwan University’s Faculty of Commerce & Business Administration has identified data mining techniques as a key tool in preventing and detecting financial fraud. The study, which reviewed various loan banking and financial fraud detection methods, found that data mining techniques are currently the most widely used approach to identify and prevent such crimes.

Data Mining Techniques for Fraud Detection

According to the study, the use of datasets for fraud detection complies with established norms of data mining, including:

• Feature selection: selecting relevant variables from a dataset
• Representation: representing data in a suitable format for analysis
• Data gathering and management: collecting and managing data from various sources
• Pre-processing: cleaning and transforming data to prepare it for analysis
• Classification: identifying patterns or relationships in the data
• Summative evaluation: evaluating the results of the analysis

Implementing Effective Strategies to Prevent Income Statement Fraud

The study’s findings have significant implications for the Egyptian banking sector, which is currently grappling with rising levels of financial crime. The researchers’ recommendations are expected to inform policy decisions aimed at preventing and detecting such crimes.

Prioritizing Data Mining Techniques in Loan Banking and Financial Fraud Detection

Deterrent technologies are most effective in reducing fraud and overcoming cons. Banks and regulatory bodies are recommended to prioritize the implementation of data mining techniques to prevent and detect financial crimes.

Conclusion

The study’s findings highlight the importance of implementing effective strategies to prevent income statement fraud and prioritizing data mining techniques in loan banking and financial fraud detection. The recommendations of the study are expected to inform policy decisions aimed at preventing and detecting such crimes in the Egyptian banking sector.