The fraud landscape for FinTech industry has increased over the past few years, certainly during the time of COVID-19, FinTech market reported rapid growth in the fraud cases…
Abstract
Purpose
The fraud landscape for FinTech industry has increased over the past few years, certainly during the time of COVID-19, FinTech market reported rapid growth in the fraud cases (World Bank, 2020). Taking the consideration, the paper has qualitatively understood the loopholes of the FinTech industry and designed a conceptual model declaring “Identity Theft” as the major and the common fraud type in this industry. The paper is divided in two phases. The first phase discusses about the evolution of FinTech industry, the second phase discusses “Identity Theft” as the common fraud type in FinTech Industry and suggests solutions to prevent “Identity Theft” frauds. This study aims to serve as a guide for subsequent investigations into the FinTech sector and add to the body of knowledge regarding fraud detection and prevention. This study would also help organisations and regulators raise their professional standards in relation to the global fraud scene.
Design/methodology/approach
This paper revisits the literature to understand the evolution of FinTech Industry and the types of FinTech solutions. The authors argue that traditional models must be modernised to keep up with the current trends in the rapidly increasing number and severity of fraud incidents and however introduces the conceptual model of the common fraud type in FinTech Industry. The research also develops evidences based on theoretical underpinnings to enhance the comprehension of the key fraud-causing elements.
Findings
The authors have identified the most common fraud type in the FinTech Industry which is “Identity Theft” and supports the study with profusion of literature. “Identity theft” and various types of fraud continue to outbreak customers and industries similar in 2021, leaving several to wonder what could be the scenario in 2022 and coming years ahead (IBS Inteligence, 2022). “Identify theft” has been identified as one the common fraud schemes to defraud individuals as per the Association of Certified Fraud Examiners. There is a need for many of the FinTech organisations to create preventive measures to combat such fraud scheme. The authors suggest some preventive techniques to prevent corporate frauds in the FinTech industry.
Research limitations/implications
This study identifies the evolution of FinTech industry, major evidences of Identity Thefts and some preventive suggestions to combat identity theft frauds which requires practical approach in FinTech Industry. Further, this study is based out of qualitative data, the study can be modified with statistical data and can be measured with the quantitative results.
Practical implications
This study would also help organisations and regulators raise their professional standards in relation to the global fraud scene.
Social implications
This study will serve as a guide for subsequent investigations into the FinTech sector and add to the body of knowledge regarding fraud detection and prevention.
Originality/value
This study presents evidence for the most prevalent fraud scheme in the FinTech sector and proposes that it serve as a theoretical standard for all ensuing comparison.
Details
Keywords
Shefali Saluja, Arun Aggarwal and Amit Mittal
The fraud landscape talks about the existence of fraudulent activities and can be assessed with the help of fraud literature. Taking this into consideration, this paper…
Abstract
Purpose
The fraud landscape talks about the existence of fraudulent activities and can be assessed with the help of fraud literature. Taking this into consideration, this paper qualitatively revisits the famous fraud triangle theory developed by Donald R. Cressey (1950) which is the most traditional theory to detect a fraud. This paper aims to discuss various fraud models that have been extensions to fraud triangle theory and reviews the factors that drive a corporate fraud. This study is divided into two phases. The first phases discuss the various theories which have been developed to detect and prevent corporate frauds in organisations, and in the second phase the authors recognize “integrity” as a new extension to the basic fraud theory. The integrity model has been introduced as “fraud square” contributing to the development of fraud theory. Integrity plays a very important role in detecting corporate frauds, and this paper will act as a theoretical benchmark for future references. The implication of this study would help future researchers, academicians and practitioners to understand the fourth element of the fraud theory and would help improve the professional standards of organisations and regulators.
Design/methodology/approach
This paper revisits the literature in detail and reviews the most acknowledged models to explain “why people commit frauds” – the fraud triangle, fraud scale, the fraud diamond, the ABC model, the MICE model and the SCORE model. The authors contend that the traditional models need to be modernized to acclimate to the current developments in the rapidly increasing fraud incidents, both in occurrence and seriousness. Additionally, this paper builds on theoretical background to generate new model so as to improve the understanding behind the major factors which lead to commitment of frauds.
Findings
The authors identify a major element – integrity – in the research. As per ACFE 2020, “There are more than 3.3 billion people in the global workforce, half of them takes illegal use of gains from the organisation and some are discipled with integrity who does not cause any harm to the organisation.” To prevent fraud, integrity plays a very important role in organisations (Bakri et al., 2017). It has been found that individuals with less integrity are basically specified to a greater level of mismanagement. The organisations that have worked with integrity will improve performance at work and will always promote the best employees to work with less supervision.
Originality/value
This paper develops the integrity model to contribute to the development of fraud theory by identifying the key factors that play a major role in whether fraud will actually occur and acting as a theoretical benchmark for all future reference.