International Conference on Machine Learning Applications in Accounting

ICMLAA

7th Sep – 8th Sep 2026 Lisbon, Portugal

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Registration Summary

Conference ICMLAA

Date 7th Sep – 8th Sep 2026

Location Lisbon, Portugal

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Total Payable USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Machine Learning Techniques in Accounting +

This track focuses on the application of machine learning algorithms in various accounting processes. Participants will explore innovative methodologies that enhance accuracy and efficiency in financial reporting.

SDG 8 SDG 9

02 Predictive Analytics for Financial Decision Making +

This session will delve into the role of predictive analytics in shaping financial strategies and decisions. Attendees will discuss case studies that illustrate the impact of data-driven insights on business outcomes.

SDG 8 SDG 9

03 Risk Assessment and Management in Accounting +

This track examines how machine learning can improve risk assessment frameworks within accounting practices. Participants will analyze tools and techniques that enhance the identification and mitigation of financial risks.

SDG 8 SDG 16

04 Audit Automation and Efficiency +

This session will explore the integration of automation technologies in auditing processes. Discussions will focus on how machine learning can streamline audits, reduce errors, and improve compliance.

SDG 9 SDG 16

05 Financial Modeling with Advanced Analytics +

This track highlights the use of advanced analytics in developing robust financial models. Participants will share insights on leveraging machine learning to enhance forecasting accuracy and scenario analysis.

SDG 8 SDG 9

06 Operational Efficiency through Data Analytics +

This session focuses on strategies to enhance operational efficiency in accounting through data analytics. Attendees will explore best practices for utilizing data to optimize workflows and resource allocation.

SDG 8 SDG 9

07 Fraud Detection and Prevention Techniques +

This track addresses the critical role of machine learning in detecting and preventing financial fraud. Participants will examine innovative approaches and tools that enhance fraud detection capabilities.

SDG 16

08 Business Intelligence in Financial Reporting +

This session will explore the intersection of business intelligence and financial reporting. Attendees will discuss how data visualization and analytics can transform reporting practices and enhance decision-making.

SDG 8 SDG 9

09 Forecasting Models in Accounting Practices +

This track focuses on the development and application of forecasting models in accounting. Participants will analyze various methodologies and their effectiveness in predicting financial trends.

SDG 8 SDG 9

10 Portfolio Analysis using Machine Learning +

This session will delve into the application of machine learning techniques in portfolio analysis. Attendees will explore how these methods can enhance investment strategies and risk assessment.

SDG 8 SDG 9

11 Key Performance Indicators and Metrics in Accounting +

This track examines the role of key performance indicators (KPIs) in measuring accounting performance. Participants will discuss the integration of machine learning to refine KPI selection and analysis.

SDG 8 SDG 9