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International Conference on Data Science Applications in Finance and Risk Modeling

📅 7–8 Jun 2027 📍 Seoul, South Korea 👤 Standard / Listener

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$185

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Conference session tracks

Key research areas covered across the sessions — tap a track to read more.

This track focuses on the application of predictive analytics techniques in finance, emphasizing their role in enhancing decision-making processes. Contributions exploring novel algorithms and methodologies for financial forecasting are particularly encouraged.

This session will delve into the integration of machine learning methodologies in assessing and managing financial risks. Papers that demonstrate innovative applications of these techniques in real-world scenarios are welcome.

This track aims to explore advanced statistical methods used in the analysis of financial data. Submissions should highlight the effectiveness of these methods in deriving insights and informing financial strategies.

This session will address the challenges and opportunities presented by big data in the financial sector. Contributions that showcase successful case studies or novel approaches to big data analytics are encouraged.

This track invites papers that utilize econometric models to enhance risk modeling practices in finance. Emphasis will be placed on innovative applications and theoretical advancements in econometrics.

This session will focus on the development and application of algorithms specifically designed for financial forecasting. Researchers are encouraged to present their findings on algorithmic performance and predictive accuracy.

This track explores the role of data mining techniques in extracting valuable insights from financial datasets. Papers that demonstrate the practical implications of these techniques in finance are particularly welcome.

This session will highlight the application of quantitative methods in the field of risk management. Contributions that provide empirical evidence or theoretical advancements in this area are encouraged.

This track examines the transformative impact of artificial intelligence on financial services, including its applications in risk assessment and customer analytics. Researchers are invited to share their insights and innovative applications.

This session will focus on forecasting techniques that aid in understanding and predicting market trends. Contributions that integrate various methodologies and provide empirical validation are highly encouraged.

This track invites discussions on the development and application of risk analysis frameworks within the financial sector. Papers that propose new frameworks or enhance existing ones with empirical evidence are particularly welcome.