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Fraud in the financial sector is a critical issue that adversely impacts financial institutions, businesses, daily lives, and also economy. The financial sector has always been to different types of fraud such as credit card fraud, identity theft, money laundering, and others. With the onset of advanced technologies, financial frauds have also evolved and become more sophisticated which are difficult to detect and prevent using the traditional rule-based system. This has led to the increasing importance of the latest technology such as Artificial Intelligence (АГ) and Machine Learning (ML). This paper is a conceptual study that discusses the various AI and ML capabilities and thereby assesses how they affect the effectiveness of financial fraud detection. This paper also attempts to identify various ethical concerns and challenges such as data privacy and quality, inherent biases and others in its implementation and recommend the best possible solution to it. Further, this paper extends its reach to future innovations and trends that are critical in the deployment of Al in financial fraud detection.
Keywords: frauds, financial sector, artificial intelligence, machine learning, ethical concern
Fraud in the finance sector is a major and challenging issue for any country as it impacts not only the financial institutions but also daily lives, businesses, and the economy as a whole. Financial fraud is a broad spectrum that includes illicit and illegal activities targeted to deprive someone of their money, or capital or negatively affect their financial health (Kunwar, 2019). This can be achieved through different means such as identity theft, credit card fraud, money laundering, insurance frauds, and others. These frauds can erode public confidence in financial institutions, destabilise the economy, and also have an immediate impact on all stakeholders (West & Bhattacharya, 2016). Financial sector has always been prone to fraudulent activities as it deals with large volumes and sensitive data. Further, financial frauds ramifications are also linked with drug trafficking and organized crimes (Bhattacharya et al., 2011). According to KPMG report (2023), financial frauds reported in the year 2023 exceeded USD 10 billion globally where identity theft is found to be the most prevalent fraud. This is an increase of 14 per cent from the year 2022, indicating a surge in financial frauds all over the world. A recent...