HARNESSING THE POWER OF DATA ANALYTICS TO DRIVE BUSINESS VALUE: IMPLEMENTATION FOR FERRERO INTERNATIONAL S.A. OF A D&A AND CONTINUOUS MONITORING MODEL TO PREVENT FINANCIAL FRAUD.

In contemporary organizations, Journal Entries serve as fundamental components of financial statements and hold valuable information. Nevertheless, these entries are frequently generated and managed by employees who have access to sensitive financial data. As a result, they become a significant source for carrying out fraudulent activities. Implementing robust data analytics and continuous monitoring models has become crucial in preventing fraud and mitigating associated risks. These models aid organizations in identifying anomalies within their accounting systems. However, designing an effective data analytics model requires careful consideration of various factors, particularly the selection of Key Risk Indicators (KRIs) and the technical execution of the model. Considering these aspects is vital to ensure the success and efficacy of the data analytics framework. The first part of this master thesis provides an extensive literature review, highlighting the evolution, concepts, tools, and techniques utilized in big data analytics nowadays. Additionally, it surveys the existing literature on the application of data analytics models in fraud detection and prevention to identify current trends and challenges in the field. The second segment focuses on anomaly detection in accounting examining various types of financial fraud, their impact on organizations, and the traditional methods employed to mitigate such fraudulent activities. The third part emphasises proactive measures to identify potential fraud risks before they occur. It investigates the integration of data analytics into existing control systems, enabling organizations to detect early warning signs and develop effective preventive strategies. The thesis further explores the challenges and ethical considerations associated with utilizing data analysis for fraud prevention. Lastly, a comprehensive case study is conducted to demonstrate the practical implementation of a data analytics and continuous monitoring model. The study presents a real-world scenario where big data analytics techniques are applied to detect and prevent financial fraud in an accounting setting. It evaluates the effectiveness of the model and highlights the benefits, limitations, and practical considerations involved in its implementation.