OPERATIONAL RISK MANAGEMENT

OPERATIONAL RISK MANAGEMENT

Tanggal
13-14 DESEMBER 2010

Jam Pelaksanaan
8.30 – 17.00

Tempat
HOTEL AMBHARA, JAKARTA

Pembicara / Fasilitator
Salman Taufik is a finance professional with years experiences since 1990 in the area of treasury and capital market, derivative, corporate finance and planning, and risk management. He had become consultant to develop a risk management system in several financial institutions. His background in mathematical modeling will make risk modeling clearly and easily understood.

Rahmat Mulyana is finance professional with years experience in banking and finance. He holds master degree in risk management from the University of Indonesia and a certified trainer in risk management certification program from BSMR & GARP. As a consultant, he served one of the biggest banks in Indonesia, Central Bank, several middle-class banks and non-bank state own company.

Harga
Rp. 4,500,000,- per peserta
Rp. 12,500,000 untuk 3 peserta

Materi
This two day program will provide you with the knowledge you need to implement Advance Measurement Approach as recommended to measure operational risk by BASEL II. Participant will learn how to develop data management of loss event and calculate the operational risk using aggregate distribution in software of  MODEL RISK.

The course focuses on both qualitative and quantitative techniques, offering
integrated solutions for operational risk and suggesting approaches to the problems that an institution will face in meeting these demanding requirements.

DAY-1: 13 DESEMBER 2010
SESSION -1 : INTRODUCTION TO OPERATIONAL RISKMANAGEMENT

• What is Operational Risk?
• Operational Risk Exposure Indicators
• Classification of Operational Risk
• Internal versus External Operational Losses
• Direct versus Indirect Operational Losses
• Expected versus Unexpected Operational Losses
• Operational Risk Type, Event Type, and Loss Type
• Operational Loss Severity and Frequency
• Capital Allocation for Operational, Market, and Credit Risks

SESSION-2 : OPERATIONAL RISK IN BASEL II

• The Basel Committee on Banking Supervision
• The Basel Capital Accord
• Pillar I: Minimum Capital Requirements for Operational Risk
  • Decomposition of Capital
  • Capital for Expected and Unexpected Losses
  • Three Approaches to Assess the Operational Risk Capital Charge
    • The Basic Indicator Approach
    • The Standardized Approach
    • The Advanced Measurement Approaches
• Ten Principles of BASEL II
• The Pillars’ Action points
• More in depth with AMA: measurement system, framework, supervisory standard, and criteria

SESSION-3: Challenge in Modeling Operational Risk

• Operational Risk Models
• Models Based on Top-Down Approaches
  • Multifactor Equity Pricing Models
  • Income/Exp. -Based Models
  • Operating Leverage Models
  • Scenario Analysis and Stress Testing Models
  • Risk Indicator Models

• Models Based on Bottom-Up Approaches
  • Process-Based Models
  • Actuarial Models
  • Proprietary Models

• Specifics of Operational Loss Data
• Scarcity of Available Historical Data
• Data Arrival Process
• Loss Severity Process
• Dependence between Business Units

DAY-2: 14 DESEMBER 2010
SESSION – 4 : MEASURING OPERATIONAL RISK USING ADVANCE MEASUREMENT APPROACH

• Developing and designing Key Risk Indicator (KRI)
  • Consideration of the use of a balanced scorecard
  • Practical case studies using real business scenarios
  • How to find key risk indicators were not working in practice?
    • Case Study developing KRIs
    • Practical case study reviewing an actual KRI database

• Frequency distribution of operational loss : using @RISK
  • Binomial distribution
  • Geometric Distribution
  • Poisson distribution
  • Negative Binomial Distribution
  • Empirical distribution with operational loss data analysis
  • Exercise case study

• Loss Severity Distribution : non-parametric and parametric distribution: using @RISK
  • Non-parametric approach
  • Parametric approach : common and mixture distribution
  • Empirical Evidence with operational loss data
  • Alpha Stable Distribution
  • Extreme Value Theory (EVT)
  • Truncated Distributions
  • Exercise case study

SESSION – 5: MODELING AGGREGATE LOSS DISTRIBUTION : MONTE CARLO SIMULATION USING @RISK

• Aggregating frequency loss and severity loss using @RISK
• Calculating OpVAR in Monte Carlo Simulation using @RISK
• Coherent Risk Measures
• VAR Sensitivity Analysis
• Backtesting VAR
• Benefits and Limitations of VaR and Alternative Risk Measures
• Empirical Studies with operational loss data

SESSION – 6 : MANAGING OPERATIONAL RISK WITH LOGISTIC REGRESSION AND BAYESIAN BELIEF NETWORK

• Logistic regression
• Case Study: Nostro break and volume
• Bayesian Belief Network
• Case Study: software product risk

SESSION – 7: REVIEWING SOFTWARE

WHO SHOULD ATTEND?

• Risk Managers/Officers
• Auditors
• Compliance officers
• Project managers
• Risk management professional