Financial Accounting Fraud Detection Using Business Intelligence

Abstract

The paper investigates the inherent problems of financial fraud detection and proposes a forensic accounting framework using business intelligence as a plausible means of addressing them. The paper adopts an empirical case study approach to present how business intelligence could be used effectively in the detection of financial accounting fraud. The proposed forensic accounting framework using business intelligence (BI) provides a three-phase model via novel knowledge discovery technique to perform the financial analysis such as ratio analysis for a business case scenario. The implementation of the framework practically demonstrates by using their accounting data how the technologies and the investigative methods of trend analysis could be adopted in order to investigate fraudulent financial reporting unlike traditional methods of vertical and horizontal analysis for the business case study. Finally, the results justify the effectiveness of the proposed BI model in proactively identifying, classifying and evaluating financial fraud in the organisation. This research further leads to practical follow-up steps that would serve as guidelines for the forensic accounting auditors and management to focus on the prime areas of financial fraud present in the case study. Overall, the proposed model caters to detecting various types of accounting fraud as well as aids in continuous improvement of an organisation’s accounting, audit, systems and policies through the feedback loop.