+1 7178835943 [email protected]
Hybrid Event (In-person or Virtual participation)

International Conference on Data Science Applications in Business and Finance · Registering as Listener

ICDSABF
📅 13 – 14 Mar 2027 📍 Perth, Australia 👥 Standard / Physical Participation
Listener Registration From
$185
Registration Benefits:
Official invitation letterIssued automatically after registration
🎖 Certificate & digital materialsGet certificate, slides and resource materials
🌐 Supporting global researchConnect with researchers across 30+ countries

Select registration mode

Prices are shown before tax and bank charges — no surprises at checkout.

All sessions Networking Certificate Invitation letter Conference kit

Your details

We only need what's required to register and email your confirmation. Everything else is optional.

Coupon Code (If Any)

Have a code? Apply it here — the discount updates the total immediately.

🏷

For Support Please Contact

VISAMASTERCARDNET BANKINGUPI

Payments encrypted & processed securely. Refundable up to 14 days before the event.

Registration summary

ConferenceInternational Conference on Data Science Applications in Business and Finance
ModeStandard / Physical
ParticipationListener
Registration fee$185.00
Bank charges (5.8%)$10.73
Total payable $195.73

Includes all bank processing charges — the amount above is exactly what will be charged.

Need help?

Contact our registration team:

📞 +91 93445 35349

Benefits of Registering as Listener

👥Access to Conference Sessions
🔗Networking Opportunities
🎖Certificate of Participation
Invitation Letter Support
📚Conference Kit / Materials
🎤Access to Keynote Sessions
• Conference Session Tracks •
SDG

SDG-Aligned Research Themes

Conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 8 SDG 9 SDG 12

This track focuses on innovative approaches to predictive modeling in business and finance. Participants will explore methodologies that enhance forecasting accuracy and decision-making processes.

This session will delve into the integration of machine learning algorithms in financial analysis and risk management. Attendees will discuss case studies and practical implementations that demonstrate the efficacy of these techniques.

This track emphasizes the role of big data in transforming business strategies and operations. Presentations will highlight analytical frameworks that leverage large datasets for actionable insights.

This session aims to explore various statistical techniques used in assessing and managing financial risks. Discussions will include quantitative risk models and their applications in real-world scenarios.

This track will cover optimization strategies that enhance financial modeling accuracy and efficiency. Participants will examine algorithms and tools that facilitate optimal decision-making in finance.

This session will investigate the application of data mining techniques to uncover patterns and trends in business data. Attendees will learn how these insights can drive strategic business decisions.

This track focuses on the application of regression and classification techniques in various business contexts. Participants will discuss methodologies and their effectiveness in predictive analytics.

This session will explore simulation techniques used for forecasting financial outcomes. Participants will analyze how these methods can improve the reliability of financial predictions.

This track examines the development and implementation of decision support systems that utilize statistical analysis and data science. Discussions will highlight their impact on enhancing business decision-making.

This session will focus on the application of statistical methods in empirical business research. Participants will share insights on how statistical analysis informs business practices and strategies.

This track will highlight the latest trends and innovations in the intersection of data science and finance. Participants will explore future directions and the implications of these advancements for the industry.

COPYRIGHT © 2026 ISAR. ALL RIGHTS RESERVED