Enterprise-wide risk management & Internal auditing: How can technology help?

1. Copyright © 2000 , SAS Institute Inc. All rights reserved. Enterprise-wide risk management & Internal auditing:How can technology help? Rik van de Weerthof Program Manager Risk Management SAS Europe, Middle East and Africa

2. Agenda • Determination of topic, goals and challenges • How can technology help?: • success criteria • practical implications and advantages

3. Agenda • Determination of topic, goals and challenges • How can technology help?: • success criteria • practical implications and advantages

4. Topic:Enterprise wide risk management • ERM is the process of identifying, measuring and controlling the effect of internal and external factors that (can) negatively affect the value of a company.

5. R uncertainty s loss profit Goal:Managing the ERM Process J L risk factors risk objects risk mea- sures risk appe- tite beha- vior

6. R uncertainty s loss profit Goal:Managing the ERM Process J L models risk factors risk objects risk mea- sures risk appe- tite beha- vior

7. Challenges:The 6 biggest issues • Combining different risk types • Timeliness of figures • Guaranteeing accuracy of figures • Interpreting the analytical results • Running out of (computer) steam • Qualified personnel

8. ? Combining different risk types • Different risk types: • credit risk • market risk • FX risk • IR risk • legal risk • operational risk • etc. • Different risk factors: • counter party default • market risk • FX rates • Interest rates • legal structure • fraud, human errors • Different risk measures: • Credit VaR • Market VaR Total risk < sum of all risk types

9. Timeliness of figures • Main Entry: time·lyPronunciation: 'tIm-lEFunction: adjectiveInflected Form(s): time·li·er; -est1: coming early or at the right time2: especially suitable for the time <a timely book> - time·li·nessnoun

10. VaR = 150 Mln with 95% confidence VaR = 400 Mln with 98% confidence Guaranteeing accuracy of figures

11. 1,000,000 900,000 800,000 700,000 VaR 600,000 500,000 400,000 95,0% 99,9% Confidence level Guaranteeing accuracy of figures

12. Interpreting the analytical results • “ Dear CEO: • Our Value at Risk is USD 5,000,000!” • “ Dear Auditor: • What the !@&*# does that mean for my company?”

13. Running out of (computer) steam • 5,000 trades per day • 100 positions • 100 risk factors • Suppose you want to do a Monte Carlo simulation with 100,000 replications • 100 * 100 * 100,000 = 1,000,000,000 calculations

14. Challenges:the 6 biggest issues • Combining different risk types • Timeliness of figures • Guaranteeing accuracy of figures • Interpreting the analytical results • Running out of (computer) steam • Qualified personnel

15. Agenda • Determination of topic, goals and challenges • How can technology help?: • success criteria • practical implications and advantages

16. How can technology help?:Success criteria • All major analytical techniques, within a single environment • Full parametrisation of analysis attributes • Portfolio-driven data model • Full Repricing • Incorporate new instruments and pricing models • Create and adapt instrument and model attributes • Analyses integrate different risk types • Traceable calculation processes with user intervention • Market modeling • Clear and concise drill-down reporting • Web reports / GUI • Data Management

17. Design specifications • All major analytical techniques, within a single environment • No need to jump between specialist packages.. • Any number of different analyses can be performed in a single run.

18. Design specifications • Full parametrisation of analysis attributes • Users must be able to customize the specifications of the various parts of the risk analysis process. • Users must be able to mix and match different specifications as needed for different analysis projects.

19. Design specifications • Portfolio-driven data model • No fixed data model. • Ability to configure data model from an existing database schema. • Ability to process data “as is”. • Ability to pull data together from numerous heterogeneous data stores.

20. Design specifications • Incorporate new instruments and pricing models • New instrument types configured easily. • User selects and installs pricing models. • No restrictions on pricing models. • Any number of vendor supplied or user written pricing libraries can be installed.

21. Design specifications • Analyses integrate different risk types • Market risk and credit exposure handled within the same framework. • A unified and logical architecture: Consistent use of data definitions, calculation methods, representation of figures, … • (Un)conditional risk measures

22. Design specifications • Trackable calculation processes with user intervention • Not a black box. • User can define and control key calculations. • Intermediate calculations can be stored and examined for additional processing or validation checks.

23. Design specifications • Market Modeling • Powerful nonlinear statistical modeling features can be used to specify and fit models of market dynamics.

24. Design specifications • Clear and concise drill-down reporting • All analytical results can be broken down or aggregated. • You can slice and dice the risk measures for a portfolio across any set of dimensions that you choose to define (by region, counter-party, instrument type, …). • Marginal and Conditional risk measures.

25. Design specifications • Web reports / GUI HTTP HTTP Java-enabled web browser Web Server Risk Server

26. Design specifications • Data Management • A true risk management solution has extensive possibilities for data access and data processing. • Must include extensive back-end data warehousing software.

27. True differentiators... • Openness, extensibility, flexibility • Data management • Clear and concise reports • State of the art risk engine • Market modeling leading to true business advantages

28. Agenda • Determination of topic, goals and challenges • How can technology help?: • success criteria • practical implications and advantages

29. + “Managing risk is managing the future.” Rik van de Weerthof = “Managing risk = Managing information.” Some quotes... “To manage a business well is to manage its future; and to manage its future is to manage information.” Marion Harper

30. Technology helps organising • time-oriented data • coming from multiple applications • according to subjects meaningful to the business • driven by the need to inform decision makers

31. Business Intelligence Systems • Get information OUT • Small number of Complex queries • Dynamic applications • Enables Creativity • Operational Systems • Get data IN • Large volume of Simple transactions • Static applications • Automates Routine Tasks Technology can fulfill an operational or a business intelligence role

32. Product Time (to maturity) Loans portfolio >10 yr 5-10 yr 3-5 yr Option book 1-3 yr <1 yr Equity book Geographical Country Region Enterprise Office >A Ctpty B-A C-B Ctpty Type Junk Daughter Credit rating All Ctpty Enterprise Counter party Type Distribution Technology organises the information dimensions

33. Technology gives insight in multidimensionality Drill down

34. Technology gives insight in multidimensionality

35. R uncertainty s loss profit Technology supplies insight required for taking appropriate RR decisions The Power to Know™ J L models risk factors risk objects risk mea- sures risk appe- tite beha- vior

36. The Power to Know RISK R I S K D I M E N S I O N S TM