Integration and transformation: The impact and applications of artificial intelligence in the financial sector
Explores AI's transformative impact on finance, focusing on investment management, risk assessment, and fraud detection.
What it examines
This paper explores the transformative impact of AI in finance, focusing on investment management, risk assessment, and fraud detection. It examines how AI recalibrates these areas through innovations like robo-advisors and AI-driven methodologies, reshaping traditional financial paradigms and operations.
What it concludes
AI revolutionizes finance by improving portfolio recommendations, risk management, and automated trading. Future research should address AI's limitations and enhance regulatory oversight. Potential applications include more accurate investment advice, better risk mitigation, and efficient automated trading systems.
Evidence objects
AI revolutionizes finance by improving portfolio recommendations, risk management, and automated trading. Future research should address AI's limitations and enhance regulatory oversight. Potential applications include more accurate investment advice, better risk mitigation, and efficient automated trading systems.
key_findings bullet 1 · key_findings · validation V0
Raw abstract and provenance
This paper explores the intersection of artificial intelligence (AI) and the financial sector, showcasing their transformative synergy. The integration of AI into finance has led to pioneering advancements like robo-advisors and AI-driven risk assessment methods. These innovations reshape investment strategies and risk management, ushering in a new era of financial operations. The study's focal question examines how AI recalibrates investment management, risk assessment, and fraud prevention in finance. The paper comprises sections on AI's impact on investment management, risk assessment, and fraud detection, detailing how robo-advisors provide personalized portfolio recommendations, AI aids risk identification and management, and transaction surveillance benefits from AI-powered fraud detection. Ethical, regulatory, and accountability considerations are discussed, reflecting AI's transformative influence on traditional financial paradigms. The application of AI in transaction detection and its role in enhancing portfolio recommendations, risk management, and automated trading are examined. While AI holds potential, its limitations such as data quality, model risks, and ethical concerns must be addressed. Regulatory oversight is crucial to ensure responsible AI implementation, fostering a balance between technological progress and financial stability. This paper underscores the intricate relationship between AI and finance, portraying AI's capacity to reshape the financial landscape and drive innovation
Source row: 1114 · abstract type: unknown