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Coursera

Advanced Financial Analysis and Credit Risk Modeling

Starweaver via Coursera

Overview

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In this course, you'll gain a strategic introduction to credit analysis and fixed income investing, blending foundational principles with practical tools to assess financial health, creditworthiness, and investment potential. Designed for professionals in investment management, corporate finance, or credit evaluation, the course explores how credit decisions are made, how debt instruments function, and how financial and non-financial data inform risk assessment. Through hands-on exercises and real-world case studies, you’ll apply analytical frameworks to real market scenarios. By the end of the course, you'll approach credit and fixed income analysis with greater precision, confidence, and strategic insight. This course is designed for finance professionals aiming to deepen their expertise in credit risk assessment and fixed income investing. Whether you're a financial analyst, fixed income trader, portfolio manager, or credit risk specialist at a bank or rating agency, the content is tailored to equip you with practical, industry-relevant skills. Investors looking to better understand the bond market will also benefit from its structured approach and real-world applications. To get the most out of this course, participants should have a basic understanding of financial concepts such as time value of money, interest rates, and financial statements. Familiarity with Excel and basic quantitative skills will be helpful for completing hands-on exercises. While no prior experience in credit analysis or fixed income markets is required, those with a background in finance, accounting, or investment will find the course especially rewarding. By the end of this course, participants will be equipped to perform detailed ratio and cash flow analyses to evaluate creditworthiness and debt servicing ability. They will also be able to apply quantitative models to calculate probability of default and expected loss, and utilize both structural and reduced-form credit risk models to support sound investment decisions. These skills will enable them to make informed credit assessments and contribute effectively to financial decision-making in professional settings. Learners will also gain the confidence to apply analytical tools to real-world credit scenarios, enhancing their ability to manage risk in dynamic financial environments.

Syllabus

  • Course Introduction
    • In this course, you’ll learn how to conduct advanced financial analysis and build robust credit risk models used by professional analysts and institutional lenders. You’ll focus on techniques like ratio and cash flow analysis, probability of default estimation, expected loss modeling, and structural vs. reduced-form credit risk approaches. Through expert instruction and hands-on Excel labs, you’ll gain the skills to evaluate creditworthiness, forecast default scenarios, and support high-stakes lending and investment decisions with data-driven insights. This course will equip you to move from foundational analysis to enterprise-grade credit risk modeling that drives real-world financial performance.
  • Ratio Analysis in Credit Evaluation
    • In this module, you’ll learn how to evaluate credit risk through comprehensive ratio analysis, using liquidity, leverage, and profitability metrics to assess financial health and debt servicing ability. You’ll examine the practical application of ratios in real-world credit assessments and explore common pitfalls to avoid misinterpretation. Through expert-led sessions, hands-on Excel exercises, and an applied case study, you’ll gain the skills to interpret financial statements with precision and make informed credit evaluation decisions.
  • Cash Flow Analysis and Debt Servicing Ability
    • In this module, you’ll learn how to assess a company’s debt servicing ability through advanced cash flow analysis techniques. You’ll explore the role of EBITDA, free cash flow, and liquidity metrics in evaluating creditworthiness, and apply stress testing and scenario analysis to gauge financial resilience under adverse conditions. Through expert instruction, Excel-based exercises, and case-driven applications, you’ll develop the skills to interpret and model cash flow data for robust credit risk analysis.
  • Credit Ratings and Their Implications
    • In this module, you’ll explore the structure, methodologies, and real-world impact of credit ratings within financial markets. You’ll examine how major credit rating agencies assign ratings, how these ratings influence borrowing costs and capital access, and how they differ across sovereign and corporate entities. Through a detailed case study, hands-on analysis of an actual credit rating report, and critical evaluation of rating limitations, you’ll build the skills to interpret, apply, and question credit ratings in professional financial decision-making.
  • Probability of Default and Expected Loss Calculations
    • In this module, you’ll examine the influence of macroeconomic factors on credit risk, focusing on how variables like inflation, interest rates, and economic cycles shape credit markets. You’ll explore sector-specific vulnerabilities, global risks, and the interplay between economic conditions and default probabilities. Through case studies and hands-on analysis using real data sources, you’ll learn to evaluate how shifting macroeconomic conditions impact credit quality and risk assessment strategies.
  • Corporate Bonds vs. Sovereign Bonds
    • In this module, you’ll analyze the distinctions between corporate and sovereign bonds, focusing on their respective risk factors, credit assessment methods, and market behavior. You’ll investigate how yield spreads signal default risk and economic confidence, and how factors like country risk, debt structure, and market sentiment shape investment decisions. Using real-world data and comparative case studies, you’ll learn to assess the creditworthiness of governments and corporations, and apply bond performance metrics to inform credit risk strategy and portfolio decisions.

Taught by

Michael McDonald and Starweaver

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