Course Description
This course is designed to provide participants with advanced conceptual background and analytical tools necessary to evaluate financial systems. The course is meant to complement related studies in accounting, finance, economics, business policy, and statistical analysis. Participants will discuss the financial systems, the accounting disclosure rules, the differential effects of alternative accounting principals, and the interpretation of financial information. They will also learn how financial institutions measure and manage their risks, and how they monitor and evaluate their systems by enhancing their knowledge and basic skills for effective performance of monitoring and evaluation processes
Course Objectives
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Being familiar with the financial systems
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Being able to analyze financial performance
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Understanding how to monitor the quality of reported earnings
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Learning how to identify balance sheet strengths and weaknesses
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Being able to conduct financial analysis of companies
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Enhancing knowledge and basic skills for effective performance of monitoring and evaluation processes
Program Schedule
PART 1
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Introduction to financial systems
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Business model analysis
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Sustainable earnings analysis
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Cash flow analysis
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Balance sheet analysis
PART 2
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Credit analysis
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Equity analysis
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Financial forecasting and pro forma financial statements
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Forecasting external funding requirements
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Sustainable growth analysis
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Implications of a company's financing decisions
PART 3
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Financial analysis of specialized industries
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Pre-course expectation analysis
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Definitions, principles and types of monitoring and evaluation activities
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Program management cycle
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Monitoring & evaluation cycles
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Logical framework for strategic planning
PART 4
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Practical/group work: preparing a strategic plan
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Steps of Terms of Reference (TOR) or proposal for monitoring & evaluation activities
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Practical/Group work: Preparing a Terms of Reference (TOR)
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Monitoring and Evaluation Methods: Methods of Program Review, Supervision and Evaluation
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Basic quantitative and qualitative data collection techniques
PART 5
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Bias in data collection: definition, sources and control
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Data Processing: analysis, interpret and presentation of routine program data
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Structure of a technical report: understanding observation, interpretation, conclusion and recommendation
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Practical/Group work: Preparing an evidence-based report
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Post-course evaluation