Flex Conference (Physical / Digital)

International Conference on Financial Services Analytics using Big Data (ICFSABD - 26)

Early Bird
10%OFF
Save up to $30 maximum per registration. Apply at checkout.
Your Code
FAST10

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals.

SDG 8 SDG 8 — Decent Work and Economic Growth
SDG 9 SDG 9 — Industry, Innovation and Infrastructure
SDG 11 SDG 11 — Sustainable Cities and Communities
SDG 16 SDG 16 — Peace, Justice and Strong Institutions
SDG 17 SDG 17 — Partnerships for the Goals
Track 01

Predictive Analytics in Financial Services

This track explores the application of predictive analytics in enhancing decision-making processes within financial services. It aims to showcase innovative methodologies that leverage big data for forecasting and risk assessment.

Track 02

Machine Learning Applications in Finance

This session focuses on the integration of machine learning techniques in financial analytics. Participants will discuss case studies and frameworks that demonstrate the effectiveness of AI-driven solutions in finance.

Track 03

Data Integration Strategies for Financial Analytics

This track examines the challenges and solutions related to data integration in financial services analytics. It will highlight best practices for combining disparate data sources to enhance analytical capabilities.

Track 04

Risk Analytics and Management

This session addresses the role of big data in risk analytics and management within the financial sector. Attendees will explore advanced techniques for identifying, assessing, and mitigating financial risks.

Track 05

Data Visualization Techniques for Financial Insights

This track emphasizes the importance of data visualization in conveying complex financial data. Participants will share innovative visualization techniques that facilitate better understanding and decision-making.

Track 06

Intelligent Systems in Financial Services

This session investigates the deployment of intelligent systems in financial services analytics. Discussions will center on how these systems can enhance operational efficiency and customer experience.

Track 07

Data Mining for Financial Intelligence

This track focuses on the utilization of data mining techniques to extract valuable insights from large financial datasets. Participants will present methodologies that uncover hidden patterns and trends.

Track 08

Compliance Analytics in Financial Services

This session explores the role of analytics in ensuring compliance within financial institutions. It will cover tools and techniques that help organizations meet regulatory requirements effectively.

Track 09

System Optimization in Financial Analytics

This track discusses optimization strategies for financial analytics systems. Participants will explore algorithms and methodologies that enhance the performance and accuracy of financial models.

Track 10

Business Intelligence Innovations in Finance

This session highlights the latest innovations in business intelligence tailored for the financial sector. Attendees will discuss emerging trends and technologies that drive strategic decision-making.

Track 11

Innovation Strategies in Financial Services Analytics

This track examines the strategic approaches to fostering innovation in financial services analytics. Participants will share insights on cultivating a culture of innovation and leveraging big data for competitive advantage.

Important Dates

Early Bird Registration :26th July 2026

Paper Submission Deadline :31st July 2026

Last Date of Registration : 10th August 2026

Date of Conference : 25th - 26th August 2026

Supporting Academic Continuity

APSTE ensures that research and publication processes continue without interruption in the current global situation. Participants can present their work through digital and integrated formats.

Close button will appear in 20s...