Xây dựng mô hình xếp hạng tín dụng nội bộ

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Sau khi tham gia khóa học này, học viên có thể

• Hiểu tiêu chí cho một mô hình đánh giá tín nhiệm hiệu quả

• Hiểu được yêu cầu từ quan điểm của nhà điều hành

• Thực tiễn tốt nhất trong xây dựng mô hình tín dụng

• Biết cách xác nhận mô hình tín dụng

• Các kinh nghiệm quý báu để tránh các sai lầm và lỗi khi xây dựng mô hình

 

Giới thiệu khóa học


Khóa học 3 ngày từ 2pm - 5pm, ngày 22, 24 & 26 tháng 3.2021.

Học trực tuyến qua Zoom, tương tác và thực hành trực tiếp với giảng viên.

Khóa học được giảng dạy bằng tiếng Anh, phiên dịch tiếng Việt.

Khóa học thực hành xây dựng và thẩm định mô hình trên Excel.

Yêu cầu học viên có kiến thức về thống kê và biết sử dụng Excel. 

Cần sử dụng máy tính khi tham gia khoá học

TẢI CHI TIẾT KHÓA HỌC TẠI ĐÂY

Ai nên tham gia khóa học này:

• Người lập/xây dựng mô hình tín dụng,

• Các nhà phát triển thẻ điểm tín dụng,

• Các nhà quản lý tín dụng,

• Các nhà phân tích tín dụng Nhóm dự án Basel,

• Những người tham gia vào kiểm định mô hình

 

Nội dung khóa học

  • Hướng dẫn tham gia khóa học. Học thử
  • Credit risk definition
  • Credit rating definition
  • Credit rating v.s Credit scorecard
  • Credit rating roles
  • Credit rating limitation
  • Credit rating models
  • • The basic methodologies for credit rating
  • • The existing external rating models
  • • Data gathering, data management for credit rating models
  • • Other requirements for credit rating models
  • • The various concepts of credit risk
  • • Credit ratings
  • • Traditional and current definitions of credit risk: default and credit migration
  • • Credit risk for bank lenders and fixed-income investors
  • • Categories of credit risk: lending, issuer, contingent, pre-settlement, settlement, country / transfer, other
  • • Credit risk during and after the pandemic
  • • Credit risk and societal issues: impact, ethics, environment
  • • From Altman (1967) to 2021
  • • Credit risk loss distributions: quantifying expected and unexpected losses
  • • Contrasting credit and market risk measurement
  • • Data gathering for credit rating
  • o Probability of default: using rating models and rating migration
  • o Loss given default: recognition, calculation issues
  • o Exposure at default: estimation issues for different risk types
  • o Default correlation: importance and issues with estimation
  • • Basic statistics for risk management:
  • o Multiple regression basic techniques and tests
  • o Default models and mark to market / multi-state models
  • o Fuzzy logic
  • o Conditional and unconditional models
  • Practice: a case with Excel, with multiple regression
  • Practice: a financial analysis of a company, which will include ratios and qualitative analysis of business model
  • • Model validation
  • o Data management
  • o Introduction to machine learning and artificial intelligence
  • Practice: a case of PD model validation with data of borrowers and data of refused credits
  • Practice: case of LGD model validation
  • • Basel II/III/IV framework for credit risk
  • • Model validation process
  • • Role of ratings, misuses of ratings
  • • When ratings go wrong and microfinance
  • • Applicability for Vietnam and the way forward

Thông tin giảng viên

Fred Vacelet, FRM, PRM
60 học viên 4 khóa học

Fred is a trainer and consultant, developing and delivering, in various continents, public and private training programs for senior bankers, including general risk management, Basel Accords, stress-testing, ICLAAP, ALM, model validation, financial and project risk, general finance; acquiring and updating a thorough knowledge of current issues and their solutions, and in-depth research into practical issues as experienced by different institutions in various financial places, building case studies and other exercises for course participants, originated and coming from more than 80 countries; an overwhelming majority of course participants declare that they enjoyed their course and learned a lot

The client list includes ABN Amro, Barclays, Lloyds TSB, CDC Paris, Credit Suisse, DePfa, Deutsche bank, National Bank of Egypt, IBM Consulting, Sungard, the UK Regulatory body (then FSA, now PRA/FCA), Reuters and numerous other institutions of various countries and sizes.

Students talked about Fred:

"I attended a seminar conducted by Fred a few years ago. It was enjoyable, informative and well-thought through. Fred made discussions run quite actively amongst participants. In particular, the case studies discussed were quite fun as well as instructive." - Zernil Lurthanathan, Director, Group Risk, Business Management Office at CIMB

"As a central banker, I'd say that I have learnt a lot from Fred. He is a great instructor and I would strongly recommend his training in Risk appetite, stress-testing, governance fields. The training was not a theory but it was a practical and case-study." - Sara Almadani, Senior Financial Economist at the Central Bank of Saudi Arabia

"Fred is a true expert when it comes to financial risk management, he can spot potential shortfalls in an approach a mile out. He enjoys passing his knowledge on and has stayed close to PRMIA and GARP since their foundation. It’s been an honor to have worked with him!" - Michael Berns, AI & FinTech Leader | Author | Keynote Speaker | PwC Europe

"Fred ran a very successful GARP Financial Risk Manager (FRM) study group at IBM, several of whom went on to senior roles at banks and risk software vendors. With his characteristic humour, Fred not only taught us the risk manager exam material but also how to think like good sceptical risk managers" - Martin Campbell, Director, Market, Credit, and Liquidity Risk at Mizuho Securities Europe

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