THE DATA-DRIVEN ACCOUNTANT: LEVERAGING DATA ANALYTICS FOR IMPROVED DECISION-MAKING AND RISK MANAGEMENT
Keywords:
Data-driven, Accountant, data analytics, Improved, Decision-making, Risk managementAbstract
This paper is on the data-driven accountant: leveraging data analytics for improved decision-making and risk management. The work critically assesses the current state of data analytics adoption in accounting, exploring trends such as the integration of advanced technologies, emphasis on predictive analytics, and blockchain implementation. It delves into the challenges faced, including the skills gap, data quality issues, and ethical concerns, hindering the effective utilization of data analytics tools. Furthermore, the impact of data-driven decision-making on accounting outcomes is examined, emphasizing enhanced accuracy, improved financial forecasting, efficient risk management, increased productivity, strategic resource allocation, and adaptability to market dynamics. Challenges related to data quality, skills gap, and ethical considerations in the implementation of data-driven decision-making are also addressed. The role of data analytics in enhancing risk management practices within the accounting domain is explored, highlighting implications such as real-time risk identification, enhanced predictive modeling, and strategic decision support. The benefits of data analytics in risk management practices, including improved accuracy, automation of routine tasks, and dynamic risk monitoring, are discussed. Challenges related to data quality, technological infrastructure, and ethical use of data in risk management are also examined.
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