This specialization provides a comprehensive pathway to mastering credit risk modeling from theory to practical application. Learners will explore key concepts such as Probability of Default (PD), Loss Given Default (LGD), and Expected Loss (EL), progressing to advanced frameworks like the Altman Z-Score and Merton’s Model. Through sector-specific and real-world case studies, participants will learn to assess financial statements, assign credit ratings, and build robust risk models aligned with banking and regulatory standards. Designed for finance professionals and analysts, this specialization bridges data-driven analysis with decision-making proficiency in corporate and institutional credit risk.
Credit Risk Modeling & Analysis Mastery Specialization
Credit Risk Modeling & Analysis Mastery Specialization
Master Credit Risk Models and Analysis. Build, analyze, and apply credit risk models for real-world financial institutions.
Instructor: EDUCBA
Included with 
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Apply advanced credit risk modeling techniques including PD, LGD, and EL estimation.
Analyze and interpret corporate financial data to assess creditworthiness and default risk.
Build, validate, and communicate credit risk models aligned with banking and regulatory standards.
Overview
Skills you'll gain
- Risk Modeling
- Risk Analysis
- Risk Management Framework
- Financial Modeling
- Financial Statements
- Working Capital
- Regulatory Compliance
- Cash Flows
- Credit Risk
- Financial Statement Analysis
- Financial Analysis
- Financial Acumen
- Financial Data
- Balance Sheet
- Financial Regulation
- Risk Management
- Business Metrics
- Corporate Finance
- Lending and Underwriting
- Bank Regulations
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
October 2025
31 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from EDUCBA
Specialization - 3 course series
What you'll learn
Analyze financial statements to assess company performance and creditworthiness using real-world data and key financial metrics.
Apply Altman Z-Score and Merton’s Model to evaluate structural and market-based credit risk in corporate finance scenarios.
Formulate credit recommendations by synthesizing risk metrics, assigning ratings, and designing exit strategies.
Skills you'll gain
Credit Risk, Financial Analysis, Financial Statement Analysis, Balance Sheet, Cash Flows, Financial Modeling, Working Capital, Bankruptcies, Risk Modeling, Risk Management, Risk Analysis, Financial Acumen, Business Metrics, and Financial Data
What you'll learn
Skills you'll gain
Credit Risk, Financial Analysis, Risk Modeling, Working Capital, Bankruptcies, Corporate Finance, Lending and Underwriting, Financial Modeling, Financial Statements, Risk Analysis, and Case Studies
What you'll learn
Skills you'll gain
Credit Risk, Risk Modeling, Regulatory Compliance, Bank Regulations, Financial Regulation, Financial Modeling, Risk Management Framework, Financial Analysis, Lending and Underwriting, and Risk Management
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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Frequently asked questions
The Credit Risk Modeling & Analysis Mastery Specialization can be completed in approximately 10 to 11 weeks, with a recommended study commitment of 3–4 hours per week. This flexible schedule allows learners to progress at a manageable pace while gaining a thorough understanding of credit risk principles, model development, and their application in real-world financial environments. By the end of the program, participants will have developed both the theoretical foundation and the practical expertise needed to evaluate, build, and apply advanced credit risk models confidently.
A foundational understanding of finance, accounting, and statistics is recommended. Familiarity with Excel or Python will be beneficial for performing data analysis, financial modeling, and interpreting quantitative outputs effectively.
Yes. It is recommended to follow the courses in sequence, as each course builds upon the previous one—starting with fundamental credit risk principles, advancing into modeling frameworks, and culminating with practical applications in the banking sector. This structured progression ensures a cohesive and comprehensive learning experience.
More questions
Financial aid available,