To develop an artificial intelligence-based system for automating the trade reconciliation process in capital markets.
To improve the accuracy and efficiency of trade reconciliation through machine learning algorithms and natural language processing.
To incorporate education-related data and information into the system to enhance the reconciliation process and provide valuable insights to traders and analysts.
To evaluate the performance of the AI-powered trade reconciliation system and compare it with traditional manual methods.
Conduct a literature review on trade reconciliation processes in capital markets and the use of AI in financial technology.
Develop machine learning algorithms for data processing and reconciliation tasks.
Implement natural language processing techniques for analyzing educational data and information.
Test and evaluate the AI-powered trade reconciliation system using real-world trading data.
Write a research report documenting the development process, results, and findings of the project.
