Role of Data Science and Data Analytics in Forensic Accounting and Fraud Detection

Introduction

Fraud constitutes a leakage on the resources of businesses and threat to the livelihood for individuals (Deloitte, 2018).It is an intentional and calculated deed that is against the law, precepts or policy, carried with the aim of getting undue economic or personal gains (Sharma & Panigrahi, 2012).The Oxford Dictionary defines fraud as the wrongful or criminal deception intended to result in financial or personal gain. Moreover, the Institute of Internal Auditors’ International Professional Practices Framework (IPPF) defines fraud as: “… any illegal act characterized by deceit, concealment, or violation of trust. These acts are not dependent upon the threat of violence or physical force. Frauds are perpetrated by parties and organizations to obtain money, property, or services; to avoid payment or loss of services; or to secure personal or business advantage”. Authors Vlasselaer, et al. (2015) provide an all-encompassing by defining fraud as “an uncommon, well considered, imperceptible, concealed, time-evolving and often carefully organized crime which appears in many ways”.

The various categories of fraudulent include; confidence tricks, embezzlement, corruption, counterfeit, product warranty fraud, health fraud, bankruptcy fraud, credit card fraud, insurance fraud, telecommunication fraud, money laundering and the use of tax haven countries to carry out illegal activities, click fraud, identity theft and plagiarism (Baesens et al. 2015; Bressler, 2010). Jofre and Gerlach (2018) asserted that committers of financial fraud are driven by personal gains or by explicit or implied contractual commitments such as debt agreements and the strong desire to achieve market projections. Fraud is associated with substantial economic risks that may pose a threat to the profitability and perception of business organisations (Bănărescu, 2015). Fraud is a growing issue for financial institutions, as tech-savvy criminals increasingly target the payments industry in new and inventive ways. Financial frauds are responsible for the sudden failure of many reputable organisations (Sule et al. 2019).

The importance of fraud detection and prevention is due to the colossal consequences. A typical organization is reported to lose 5% of their revenues to fraud annually; the annual insurance fraud in the United States is over $40 billion while fraud is costing the United Kingdom about £73 billion annualy (Baesens et al,2015).According to PwC’s Global Economic Crime and Fraud survey of 2018, nearly half (49%) of 7,200 global organisations have experienced economic crime in the past two years, up from 36% in their last survey. Synectics Solutions’ latest statistics showed that organised fraud rose to 59.58% during 2017 from 57% in the previous year. Similarly, the Association of Certified Fraud Examiners (ACFE) Report released in 2018 provided a global analysis of the costs and effects of occupational fraud.16% of all the cases in the study resulted in a median loss of USD 118,000 and continued for a median 18 months before they were discovered (ACFE,2018). Ernst & Young Global Fraud survey of 2018 revealed that 11% of companies have encountered a substantial fraud in the last two years while 38% of respondents affirmed that acts of bribery/corruption take place widely in organisations within their countries (Ernst & Young, 2018).The annual online fraud is 12 times larger than offline frauds of companies report, resulting in severe financial losses to the global economy (Zheng et al,2018).It is also reported that 5% of the organination revenues is lost to fraud.