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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.