PROGRAM DETAILS

Introduction

This course is designed to help participants understand the significant components and features of credit portfolio modelling and management (CPM). The aim is to elucidate how a broad range of risk modelling and risk assessment approaches can be brought together to enable risk-based pricing and assessment—ultimately enabling portfolio managers to choose investments based upon fundamentals as well as market dynamics as prescribed in the Nigerian Pension Guidelines for Investment.

Airms

Primary focus is given to best-practice and to quantitative methods that are actually demonstrated to work in practice across many countries but with specifics to Nigeria Pension Commission

Learning Objectives

At the end of this program, participants will be able to:

•  To create awareness of managing Risks in investment
• Provide insight to known global risks and country specific risks
• Deepen knowledge of identifying risks
• Detail various means of Risk avoidance and mitigations
• Use of various tools and accelerators to mitigate risk potentials

Learning Outcomes

• The elements necessary for internally developing and testing a ratings and scoring system that can be used with various exposure types—including privately listed, small to medium-sized enterprises (SMEs)

• How to integrate a quantitative, credit scoring platform with a qualitative ratings system in Basel II/III-compliance fashion
• How to develop the necessary CPM databases for estimating and validating scoring models and risk components, such as Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD)
• Portfolio-level measures of risk, including measures of concentration using tail dependence and other advanced measures
• How to use Monte Carlo simulation and basic programming to develop and test scoring models and to model portfolio dependence, persistence, dynamics and stress-testing
• How to use this integrated system in both origination and portfolio management activities
• How to assess Expected Loss (EL) for provisioning and Unexpected Loss (UL) for capital allocation—both on a standalone and portfolio basis
  How to create a Risk-Adjusted-Performance-Measurement (RAPM, aka RAROC) system. As well as useful techniques related to specific topics, such as:
• Strategies for extracting important information from problem accounts
• How to explain quantitative model results to qualitative-oriented directors and shareholders

Program Content

Day 1

• Overview of Risk Management
• What Risk Management boils down to
• Buy and hold strategy
• Static risk (loss) distribution
• Lack of Risk-Adjusted Performance
• Expected Loss (EL) and Unexpected Loss (UL) can be underestimated
• The All-In-Spread (AIS) of traditional lending
• The Credit Portfolio Model
• Breaking the Credit Process into components
• Alternative credit strategies
  • Selling Exposures
  • Establishing SPVs
  • Use of Credit Derivatives and Structures
  • Digital and other opportunities to derive revenue
• The Role of Risk Management
• The AIS under CPRM

Day 2

• Hurdles in emerging markets
• The Psychology behind implementing Credit Management and getting buy- in
• Helping Management Make Strategic Choices
• The primary tool for strategic choice: Risk-Adjusted Performance Management (RAPM)
• The Traditional (Commercial Bank) Investment Portfolio model
• Risk Adjusted Performance Measurement (RAPM)
• Risk Contribution
• How RAPM helps us select and manage exposures
• Developing a RAPM Model
• Determining Economic Capital
• Summary and Best-Practice on RAPM

Day 3

• Developing Analytics to Support RAPM
• Portfolio dynamics
• Valuation
• Migration
• Value-at-Risk and default
• Economic and Regulatory Capital
• Risk Components
• The Basel Back drop
• Basel I, II and III compared
• The Risk Components under Basel Rules
• Dynamics of Risk components (in spreadsheets)
• Basel at the Portfolio Level
• Portfolio Dynamics
• PD estimation
• Why we do not like statistical obligor PDs in retail
• Segmentation – Vintage analysis – Delinquency status – Developing a PD model – Smoothing
• Loss given default measurement (LGD)
• Various loss model techniques

Day 4

• Risk Component Back testing
• Probability of Default (PD) back testing – Hosmer/Lemeshow – Binomial Tests – Brier Score – Other tests – Problems with the Central Limit Theorem in practice
• Loss Given Default (LGD) back testing – Choosing a low operational risk LGD estimation method – Back testing and confidence intervals
• Developing the Retail and SME scoring models
• Public companies• Dealing with private, unaudited companies• Structural

models: Black-Scholes-Merton – Public firm variants – Private firm variants

• What will like work in African markets
• Models and exercise
• Expected Loss (EL) and Unexpected Loss (UL) for Single exposures
• Provisioning and Basel II-related issues
• Economic capital allocation
• Using your risk model for capital allocation
• Developing a Risk-adjusted-performance measurement (RAPM) system

Day 5

• Correlation and joint default estimation
• Obtaining a Credit Value-at-Risk (CreditVaR)
• Setting Economic Capital
• Portfolio stress testing, provisioning and recapitalisation
• Defining stress tests
• Distinguishing scenarios and sensitivity analysis
• Interpreting results
• Articulating results    internally    and    to    investors    and    regulators