1. Sydney December 11, 2006 Seite 1 Lessons from implementations of Basel II and for Solvency II Part 0: Who is QRM & cross-sectoral overview Part 1: Market risk models for the trading book of banks Part 2: Credit risk models at banks Part 3: Operational risk models at banks Part 4: Market risk models at investment funds Part 5: Holistic models at insurers (Solvency II) Part 6: Economic capital and use test Gerhard Stahl & Stefan Jaschke, BaFin

2. Sydney December 11, 2006 Seite 2 Lessons from implementations of Basel II and for Solvency II - Who is QRM & cross-sectoral overview

3. Sydney December 11, 2006 | 03.04.2015Seite 3 BaFin as the German financial regulator As from BaFin’s mission statement: Preserve stability of the German financial system Maintain confidence of investors and consumers Safeguard fair behaviour of market participants BaFin approach: Integrated supervision (banking, insurance, financial services) Risk identification and risk limitation Prevention before punishment Principle based (not rule based) regulation

4. Sydney December 11, 2006 | 03.04.2015Seite 4 Cross-sectoral supervision by QRM BanksFundsInsurers market risk models (Amendment to Basel I, since 1998) interest rate risk banking book (since 2004) internal ratings (Basel II IRBA, since 2005) OpRisk (Basel II AMA, since 2006) hedge funds (DerivateV/OGAW -RL, since 2004) since 2005 (pre- visits) potentially: Solvency II (starting 2008- 2010) on-site inspections of internal models: head count:about 28 in Q3/2006

5. Sydney December 11, 2006 | 03.04.2015Seite 5 Internal Model (IM) Auditing Background Regulation was almost juridical, typically off-site supervision, before 1997 Development of internal auditing expertise at BaFin and Deutsche Bundesbank since 1996 Institutions may use suitable internal risk models for determining the capital charges or partial capital charges for the market risk since 1997, provided that BaFin has confirmed their suitability in writing upon the institution's request (“Principle I concerning the capital of institutions” )

6. Sydney December 11, 2006 | 03.04.2015Seite 6 Lessons from IM Audits for Basel II Stochastic modelling and regulation Non-linear instruments, complex hedging strategies Large-scale forecasting models with thousands of variables Portfolio view of risk Are multivariate non-linear stochastic models complex? No! – the complexity comes from the interdisciplinary use of VaR-Models

7. Sydney December 11, 2006 | 03.04.2015Seite 7 Investment funds, banks, insurers funds hedge funds banks derivates houses insurers re-insurers complexity of products complexity of risk drivers market risk + credit risk + exotic deriv. (z.B. wheather) +insurance risks +longer time horizons more uncertainty

8. Sydney December 11, 2006 | 03.04.2015Seite 8 Similarities and Differences Similarities / Synergies similar products: structured products interest rate and credit derivatives similar tools and models: market risk (Black-Karasinski) credit risk (CreditMetrics) Banks / Basel IIinsurers / Solvency II input-oriented partial models (market and ratings) shorter horizons aggregation of risk numbers in market risk: thousands of risk drivers or simple „earnings at risk” absolute risk measure output-oriented holistic modeling longer horizons aggregation of distributions King’s road: small number of accumulation events, which explain losses at the group level risk relative to a benchmark (RNP)