Certified Credit Risk Management Specialist
This course provides an in-depth exploration of credit risk theory, quantitative modelling, and risk mitigation techniques.
Instructors:
Price: €1500
€1500
Self study and virtual classes
Approx. 60 hours to complete
Examination
Certificate
Introduction to the class
How it works?
This course provides an in-depth exploration of credit risk theory, quantitative modelling, and risk mitigation techniques. Participants will engage with both traditional methodologies and cutting-edge approaches—including machine learning applications—to assess, manage, and mitigate credit risk in dynamic financial environments. Real-world case studies, interactive workshops, and a capstone project ensure that learners not only understand the theoretical underpinnings but also gain hands-on experience in risk analysis and decision-making.
This course includes:
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10 hour of virtual meetings with the instructor
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50 hours of self study including articles and video presentations
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Full lifetime access to learning material
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Certificate of achievement
Virtual classes take place on Hapeiron, an Interfima e-learning platform.
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Enroll to the class from this page
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After enrollment you'll receive a registration link to access the platform
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Complete all live classes and learning material
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Take the examination online
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Pass the exam and get your certification
Do you want this class in-house?
We can deliver this class in-house for your organization's employees.
About this Professional Certificate
Pass the exam at the end of the course and earn a market focused certification. Interfima is a MENJE accredited vocational organization in Luxembourg.
Skill you will gain
Risk management
Risk Analysis
Risk assessment
Risk mitigation
Instructors
The training is conducted by Stanley. Check his profile by clicking on his name below.
Requirements
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Three years experience in the financial services industry either/or an undergraduate or graduate degree in Finance, Economics, Business or Law from an accredited university, college or school
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Continuous Education: 3 hours of related financial training every year
Examination
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Passing Grade 70%
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Multiple choice questions and / or essay type questions
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One (1) hour duration
What you will learn
By the end of this course, participants will be able to:
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Analyse the fundamental drivers and evolution of credit risk
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Develop and validate quantitative credit risk models including PD, LGD, and EAD estimation
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Evaluate credit portfolios using advanced risk metrics and simulation techniques
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Design and implement stress testing and scenario analysis frameworks
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Integrate regulatory requirements (e.g., Basel II/III/IV) into credit risk management practices
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Employ risk mitigation strategies including collateral management, loan restructuring, and credit derivatives
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Leverage emerging technologies and data analytics (including machine learning) for enhanced credit risk assessment
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Communicate complex risk issues effectively to stakeholders and regulators.
Foundations of Credit Risk
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Evolution of credit risk management
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Role of credit risk in financial stability
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Economic, borrower, and portfolio-level factors
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Impact of credit cycles and systemic risk
Regulatory Environment and Governance
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Overview of Basel Accords (Basel II, III, and emerging Basel IV)
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Capital adequacy and risk-weighted assets
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Credit risk policies, internal controls, and the role of supervisory bodies
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Disclosure, transparency, and risk culture within financial institutions
Lending Practices and Credit Analysis
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Credit underwriting and risk pricing
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Differences in SME vs. corporate lending
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Financial statement analysis and cash flow assessment
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Evaluating non-financial qualitative factors
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Identification of distress signals
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Monitoring delinquency trends and resolution strategies
Quantitative Credit Risk Modelling
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Estimating Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD)
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Structural models vs. reduced-form models
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Credit scoring: traditional methods (logistic regression, discriminant analysis) and advanced techniques (machine learning algorithms)
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Back-testing, stress testing, and model risk management practices
Mitigation Strategies and Risk Controls
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Collateral management, guarantees, and credit derivatives
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Loan restructuring and recovery processes
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Credit administration and monitoring practices
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Best practices in delinquency management and resolution
Integrating Technology and Innovation
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Big data applications and real-time risk monitoring
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Advanced analytics and AI-driven credit scoring
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Emerging trends and challenges in digital credit platforms
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Cyber risk and operational risk integration
Credit Portfolio Management
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Diversification, concentration, and correlation risks
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Credit Value-at-Risk (Credit VaR)
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Monte Carlo and scenario-based simulations
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Dynamic risk assessment and rebalancing strategies
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Use of technology for real-time monitoring
Practical Applications and Case Studies
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Simulation exercises on credit portfolio management
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Hands-on modelling sessions using statistical software and programming tools
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Deep-dive analyses of credit risk failures and success stories
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Guest lectures by industry experts and regulators
Stress Testing and Scenario Analysis
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Sensitivity analysis and scenario design
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Reverse stress testing methodologies
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Integrating macroeconomic variables and systemic risk considerations
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Analysis of past financial crises and lessons learned
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Regulatory stress test frameworks in practice
Capstone Project and Assessment
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Comprehensive analysis of a real or simulated credit portfolio
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Development of a risk mitigation framework incorporating stress testing and regulatory requirements
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Presentation of findings and strategic recommendations
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Peer and instructor feedback sessions