Applications of data science in financial management

Bag code: ADMFACC104315026 Days: 3 days "Training session two and a half hours" Time: 15 training hours Targeted participants: financial affairs managers, accountants, financial analysts, planning and risk management specialists, digital transformation teams, entrepreneurs, and students of financial and administrative disciplines. About the program: This program revolves around applications of data science in financial management. Definition – types – characteristics – objectives – advantages – disadvantages... etc. Program name: Applications of data science in financial management. It will be presented through the following unit: First training unit: fundamentals and building financial understanding Second training unit: analytical and predictive models in financial management Third training unit: advanced practical applications – and automation of financial decisions Program objectives: It is expected that the participant at the end of the training program, God willing, will: Understand the basics of data science and its application in financial management. Analyze financial data using modern tools. Use statistical and predictive models in financial planning. Design and read performance indicators and financial dashboards. Apply automation and machine learning to improve financial process efficiency. Applications of data science in financial management Program topics: First training unit: (Fundamentals and building financial understanding) First session: Introduction to data science and financial management The origin of the concept of data science and its role in supporting financial decisions. The difference between financial data and operational data. How data science changed traditional financial analysis methods. Types of financial data and their sources Internal data sources: accounting – operational – budgets. External data sources: financial markets – economic reports. Financial data quality and criteria for selecting suitable data for analysis. Second session: Skills in analyzing financial data using modern tools Why use Excel Advanced Excel in financial data. Introduction to Power BI Power BI or Tableau for visual analysis. How to clean and process financial data. Descriptive analyses in financial management What is trend analysis over time. Cost and revenue analysis. Financial deviation analysis and linking to indicators. Second training unit: (Analytical and predictive models in financial management) First session: Applied statistical analysis on financial data Correlation and regression in studying financial factors. Dispersion, variance, and risk analysis. Building testable financial hypotheses. Financial forecasting using data science techniques Reasons for forecasting models to predict sales and cash flows. ARIMA and financial Time Series models (simplified). Forecasting applications in preparing estimated budgets. Second session: Financial classification and decision-making models Impact of using Decision Trees in evaluating financial alternatives. Loan analysis and customer risk classification. Logistic regression model in predicting financial default. Visual financial analysis using interactive dashboards Globalization, designing financial dashboards. Financial performance indicators (KPIs). Reading visual interactions and making immediate financial decisions. Third training unit: (Advanced practical applications – and automation of financial decisions) First session: Machine learning applications in financial management Forecasting models using Machine Learning. Analysis Anomaly to detect financial errors and fraud. Building a simple model to analyze product profitability. Investment and financial portfolio risk analysis Managing portfolios using algorithms. Risk measurement (Value at Risk – VAR). Stock performance prediction using market data. Second session: Automating financial processes using data science (RPA + Data) Simplifying financial review processes. Automating monthly reports. Automating payment orders and routine activities. Practical workshop + final project Analysis of real (or semi-real) financial data. Building an interactive financial dashboard. Presenting a project at the end of the day (Case Study). PowerPoint contents: Trainer guide: 121 Participant guide: 121 Activities: 8 Introductory guide: 6 Assessment and data forms: 2 Pre-test: 3 Videos: 3 Contents of the kit: 9 Training kit model: Please click here to view the training kit model