In the era of accelerating digitalization, artificial intelligence (AI) has become a pivotal element in many aspects of daily life, including financial management. AI has evolved significantly over the past two decades, and has had a profound impact on how assets are managed, risk analyzed, and financial operations are improved. By providing advanced tools and techniques, AI enables companies and financial institutions to make more informed and accurate decisions.

One of the most prominent applications of AI in financial management is improving data analysis. AI can process massive amounts of financial data with speed and accuracy that exceed human capabilities, allowing organizations to discover patterns and trends that may be hidden by traditional methods. Complex algorithms and machine learning are used to analyze this data and provide predictive insights into market movements, helping to make informed investment decisions.

In addition, AI contributes to enhancing the efficiency of financial risk management. By developing advanced analytical models, AI can more accurately predict potential risks and provide recommendations for preventive measures. AI tools also help improve credit management and detect fraudulent activities, reducing potential losses and improving the stability of the financial system. AI applications are not limited to analysis and risk management, but also extend to automating financial processes. For example, intelligent systems can automate routine tasks such as processing invoices and preparing financial reports, reducing operational costs and increasing data accuracy.

Who Should Attend?

• Financial analysts.
• Investment managers and fund managers.
• Financial risk managers.
• Financial advisors.
• Data managers and financial data analysts.
• Students and finance professionals.
• Entrepreneurs and startup owners.
• Financial experts in large corporations.

Knowledge and Benefits:

After completing the program, participants will be able to master the following:

• Concepts of artificial intelligence, machine learning and deep learning.
• How to apply artificial intelligence in the field of financial management.
• Collect, clean and analyze financial data using artificial intelligence tools.
• Apply artificial intelligence tools to improve investment strategies and analyze financial markets.
• Use artificial intelligence to manage financial portfolios and identify investment opportunities.
• Use artificial intelligence to analyze financial risks and predict potential risks.
• Ethical challenges associated with the use of artificial intelligence in financial management.
• Use predictive analytics results to improve strategic decision making.

• Introduction to Artificial Intelligence and Financial Management
  • Fundamentals of Artificial Intelligence, Machine Learning, and Deep Learning.
  • How AI can improve and transform financial management.
  • Latest trends in AI and future developments in financial management.
• Collect and analyze financial data using AI
  • Financial data sources (historical data, live data, unstructured data).
  • Data cleaning and preparation techniques for analysis.
  • Using tools and techniques such as Python and R to analyze financial data.
• Building and applying financial predictive models
  • Designing and building predictive models using AI algorithms.
  • Common algorithms such as linear regression, random forests, and neural networks.
  • Evaluating model performance using indicators such as prediction accuracy and F1-score.
• Improving investment strategies using AI
  • Using AI to analyze investment markets and identify opportunities.
  • Applying AI techniques in portfolio management and improving asset allocation.
  • Using tools such as trading robots and investment recommendation systems.
• Managing financial risks using AI
  • Using AI to analyze and assess potential financial risks.
  • Developing effective risk management strategies using predictive models.
• Automating financial processes
  • Using AI to automate tasks such as invoice processing and reporting.
  • Techniques to improve the efficiency of financial operations and reduce human error.
• Ethical and regulatory challenges
  • Ethical issues related to the use of artificial intelligence in financial management.
  • Laws and regulations governing the use of artificial intelligence in finance.
• Developing strategic skills
  • Using the results of predictive analysis in making strategic decisions.
  • Skills in analyzing and interpreting the results of predictive models and applying them in the context of financial management.