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Basel 2 - Internal credit rating models

 

INTERNAL CREDIT RATING MODELS

Duration: 4 days 

Open: 27-30 Mars,  2018

 


 

 

CONTENT

 

 

COURSE OUTLINE

 

Part 1: Credit rating models
    This outline is for the three-day with sessions including Excel exercises. A prerequisite is a good working knowledge of Excel and knowledge of statistics. Participants are requested to bring a laptop
Day 1
Session 1: Credit Risk Management and modelling
• Common processes
• Structuring/restructuring credits
• Legal framework on bankruptcy
• Credit risk mitigation
• Credit risk handling techniques
• Credit crises
• Credit derivatives
• Common credit risk models
• Roles and limitations of models
• A credit risk evaluation framework
Session 2: Credit Ratings
• Common ways
• Ratios analysis
• Discriminant analysis
• Probabilities of Default (PD)
• External ratings
• Transition matrices

 

 

 

 

 

 

 

 

Day 2

Session 3: Best Practices in Credit Model Building
• Underlying causal systems
• Audit trail
• Evaluation
• Modular approach
• Data
• Building models
• Integrating models in processes
• Time series and black swans
• Macroeconomic issues
• Uses and misuses of credit models
• Building a model culture
Session 4: The Regulator’s Perspective on Credit Risk Modelling
• Basle I, Basel II, Basel III
• The approaches
• The Internal Ratings-based (IRB) approach
• Loss Given Default (LGD)
• Exposure At Default (EAD)
• Validation in Basel II/III
• Vendor models viewed by regulators
• The model approval process

 

 

Day 3

Session 5: Credit Scoring and Advanced Credit Risk Models
• Scorecards
• Rating agencies
• Prediction of Loss Given Default
• Credit correlations
• Portfolio-based credit modelling
Session 6: Case Study: Validation of an existing model

 

 

Part 2: SPSS Practice
     PSS Statistics is a software package used for logical batched and non-batched statistical analysis. This outline for the one day of guidance on SPSS practice. Participant need to install SPSS before the class.
Day 4
• Introduction to SPSS
• Descriptive statistics (frequency, mean,standard deviation, etc.)
• The foundation steps to set up the model
• Correlation analysis
• Exploratory factor analysis (EFA)
• Time series analysis.
• Single & multiple regression analysis
• Two-group comparison (T-test)
• Non-parametric testing
• Analysis of variance (ANOVA)
• Regression with dummy variables.
• Stepwise regression analysis
• Logistic regression

BENEFIT

What you will learn in this course:
  • Understand criteria for an effective credit rating model
  • Understand the requirement from regulator’s perspective
  • Best Practices in Credit Model Building
  • Know how to validate a credit model
  • Practice on SPSS Statistic package

WHO SHOULD ATTEND

Who should attend the course?
  • Risk analysts,
  • Credit modelers,
  • Credit scorecard developers,
  • Credit managers,
  • Credit analysts Basel project team,
  • Those involved in model vetting/validation and auditing

TESTIMONIAL

 

"The Courses at ARFQuant vary in many topics which reward for those who work in the financial sector. The pursuit of these specialized courses is a very arduous process, but the results are well worth the effort. The courses go from theoretical to practical, thus helping to better understand the nature of the problem, as well as how to apply it in practice. Overall, ARFQuant course leaders are very good at teaching and dedicated. Participation in ARFQuant courses helps to increase the systematic and effective learning compared to self-study and self-study." Phương Phùng- OCB

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"A survey on the main issues that the trainees are interested in has been conducted to make sure that the course’s content is fit the needs of the trainees. The training environment was open which encourage the participation of all attendants. Instructors are enthusiastic, supportive and willing to share their knowledge and experience" Phượng Phan - FeCredit

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"The course leader has deep knowledge in risk management, he is enthusiastic and open to the students. Teaching methods attract the attention of students. He usually use stories mixed with humor as examples for the whole class and to create a dynamic atmosphere. The course was  organized professionally" Hien Phan - BIDV

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"From the beginning of 2017, I have been experiencing 02 courses at ARFQuant - Statistics - modeling risk, internal credit rating model.

Even the duration of the courses were quite short but the knowledge I obtained from the course is huge, thanks to the special way that ARFQuant’s teachers deliver the course: simple, understandable and valuable. During the course I felt quite comfortable and easy to grasp knowledge. In addition to the mandatory content in the curriculum, teachers share more experiences in learning and research (eg, Mr. Hoang shared his experiences in reading and reviewing FRM and Mr.Fred taught how to handle data when it is bias, etc.).
Materials and lectures are well designed and focused. At the end of the course, I can take advanced knowledge gained in these materials to study and work. However, it would be more complete if the material introduces some other sources of reference so that I can read more after the courses.

 If I have the opportunity to attend other courses, I would like to experience at ARFQuant again. " Thảo Nguyễn - OCB

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STATISTIC AND RISK MODELLING

 

STRESS TESTING

 

INTERNAL CREDIT RATING MODELS

 

DERIVATIVE AND PRICING

 

MARKET AND LIQUIDITY RISK MANAGEMENT

 

APPLICATION OF SPSS IN FINANCIAL FORECAST

 

APPLICATION OF SPSS IN RISK MODELLING

CREDIT RISK PORTFOLIO MANAGEMENT

 

ASSET LIABILITY MANAGEMENT & FUNDS TRANSFER PRICING

 

MARKET RISK MANAGEMENT

 

OPERATIONAL RISK MANAGEMENT

 

CREDIT RISK MANAGEMENT

 

COUNTER PARTY RISK MANAGEMENT

 

 

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