Basel II: Operational Risk Implementation based on Risk Framework

Transcription

1 Systems Ltd General Kiselov 31 BG-9002 Varna Tel Fax WEB: Basel II: Operational Risk Implementation based on Risk Framework Dr. Anatoliy Antonov Systems

2 Presentation Agenda Overview of Approaches Basic Indicator Approach Standard Approach OR Loss Database and Loss Event Data Entry Self Assessment Advanced Measurement Approach (AMA) Requirements of AMA Internal Operational Risk Data Model - Stochastic Models for Severity - Stochastic Models for Frequency - Correlation of Key Risk Indicators Business Structure and Aggregation Loss Distribution Simulation Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 2

3 Main Risk Types Capital allocation Market Risk ca. 15 % Credit Risk ca. 50 % Operational Risk ca. 35 % > Do you share this opinion? Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 3

4 Operational Risk Regulatory Capital 8 Business Lines Investment Banking Corporate Finance Trading & Sales Banking Retail Banking Commercial Banking Payment & Settlement Others Retail Brokerage Agency Services & Custody Asset Management Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 4

5 Operational Risk Regulatory Capital 3 Methods Basic Indicator Approach Standard Approach Advanced Measurement Approach BIA STA AMA Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 5

6 Risk Framework Modules English, German English, German English, German Core System Databases Oracle, MS SQL, Import Interface, Excel Export Crystal Reports, XML/XSL COREP / XBRL Reporting Batch Processing, Internet GUI Model&rule-based Modules English, German ALM&Liquidity Asset /Liability Mgmt. Cash Flow(GAP) Fund Transfer, LVaR Liquidity Scenarios Turkish English, German English, German English, German Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 6

7 Risk Framework System Features Main Features Encloses all regulatory risk types: credit, operational, market, rating&scoring Registering of main objects: Exposures, Instruments, Customers, Collateral s Simple Integration to existing portfolio management or core banking systems Support of different data bases without changes: Oracle, MS SQL WEB Browser User interface and server mode Supporting Functionalities Multi-User Feature, Roles and Rights: show, create, modify, confirm, delete Support of historic storing/accessing for all Object persisted into data base Rule based expert system Rule based business Logic: model scripts controls fully Risk Framework Definition of GUI, automatic structuring of the data base, business logic Automatic adjustment of GUI and data base at model changes Interfaces and Reporting Importer to import data from external sources using flat files COREP Reporting for regulatory results, Crystal reporting tool Export and Import Interfaces to MS Windows directly and via Clip Board Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 7

8 Risk Framework Product Architecture Risk Framework Windows desktop WEB Browser Rule based Engine CLIPS Expert System Core Busines Logic Model- Script Import Files Importer RFW Tables Core DB Tables Host Data Base Risk Framework Tables Data base Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 8

9 Basic Indicator Approach Capital Requirement Calculation Operational Risk Requirement = (α x indicator)/n α = 15% n = max 3, average over 3 years Indicator = gross income Gross income = yield income + non-yield income Negative income is excluded Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 9

10 Basic Indicator Approach Income Example Yield incomes Yield expenses (70) (70) Pure yield incomes Provisions (3) Net fees / commissions 5 5 Realized gains / losses from sale of securities in the banking book Income from trading 5 5 Other non-interest income 5 5 Non-interest income Non-interest expenses (25) (25) Taxes 3 Extraordinary income 6 5 Pure income = 25 Gross income = 20 Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 10

11 Basis Indicator Approach Input Data and Capital Requirements in Risk Framework Evaluation Currency Incomes for 3 years Capital Requirement Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 11

12 Standard Approach Capital Requirements Calculation Operational Risk Requirement = {years (1..3) max [ (GI (1..8) x β (1..8) ),0]}/3 GI (1..8) = Gross annual income for each of the 8 business lines β (1..8) = fixed percentage, set for each business line The activities of the bank is distributed in the 8 business lines: GI (1..8) Indicator: Gross income averaged over 3 years: years (1..3) Capital requirements for each business line is calculated by multiplying its gross income at a certain Beta percentage: β (1..8) Negative income is included in the calculations Total capital requirement is the sum of capital requirements on business lines Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 12

13 Standard Approach Business Lines and Beta Factors Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 13

14 Standard Approach Income Example Year 1 Gross income * Beta Total Corporate Banking 60 15% 9 Retail Banking % -1.2 Marketing and sales 30 18% 5.4 TOTAL Year 2 Gross income * Beta Total Corporate Banking 30 15% 4.5 Retail Banking % -4.8 Marketing and sales % -1.8 TOTAL Year 3 Gross income * Beta Total Corporate Banking 80 15% 12 Retail Banking 10 12% 1.2 Marketing and sales 30 18% 5.4 TOTAL Requirements = 10.6 Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 14

15 Standard Approach Input Data in Risk Framework Incomes for 3 years for marketing and sales Incomes for 3 years for retail banking Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 15

16 Standard Approach Capital Requirement Calculation in Risk Framework fixed percentage for each business line Capital Requirement Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 16

17 Basic Indicator & Standard Approach Operational Risk COREP Reporting in Risk Framework Preparation of COREP Reproting Data Gross income of business lines for last 3 years Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 17

18 Basic Indicator & Standard Approach COREP and Crystal Reporting (Example in Cirillic) Show COREP Reporting XBRL on Internet Explorer Generate Reports by Crystal Reproter Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 18

19 Basic Indicator & Standard Approach COREP Reporting in Excel forms (Example in Cirillic) Generate COREP Reports in Excel forms Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 19

20 OR Loss Data Base Loss Event Data Entry in Risk Framework Dates: Occurence, Encovering, Accounting Loss Event Description Loss Amounts: Gross Amount, Recovery Amount, Net amount Qualitative Features Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 20

21 OR Loss Data Base Loss Event Data Entry in Risk Framework Gross Loss Amount Distribution of Loss over business lines Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 21

22 OR Loss Data Base Loss Event Data Entry in Risk Framework Basel II Categorisation of Loss Event: Level 1, Level 2, Level 3 Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 22

23 OR Loss Data Base Loss Event WEB Protocol in Risk Framework Loss Events sessions are stored by time stamp. Every session registers a Loss Event Loss. A standard session protocol can be generated and printed out. Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 23

24 OR Loss Data Base Calculation of Risk Matrix for COREP in Risk Framework Preparation of COREP Reporting Data Matrix: Busines Lines x Key Factors Total Loss Amount Max Loss Amount Number of Losses Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 24

25 OR Loss Data Base COREP and Crystal Reporting (Example in Cirillic) Show COREP Reporting XBRL on Internet Explorer Generate Reports by Crystal Reproter Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 25

26 OR Loss Data Base COREP Reporting in Excel forms (Example in Cirillic) Generate COREP Reports in Excel Forms Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 26

27 OR Loss Data Base Single Losses and COREP Reporting in Risk Framework Preparation of COREP Reporting Data for single Losses Show COREP Reporting XBRL on Internet Explorer for single Losses Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 27

28 OR Loss Data Base COREP Reporting in Excel forms (Example in Cirillic) Generate COREP Reports in Excel forms Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 28

29 Self Assessment Example for Internal Frauds in Risk Framework Questions about potential occurence of Internal Frauds Question Replay giving Severity (0..4) and Probability (0..4) Expected Loss Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 29

30 Self Assessment Risk Matrix for Internal Frauds in Risk Framework Categorization within risk matrix: Loss Volume x Probability Categorization within matrix of remaining risk: Risk Reduction x Risk Distribution of Losses over business lines Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 30

31 Advanced Measurement Approach (AMA) Approach Requirements and Steps Management of Internal historic Events and Loss Data Fitting historic Series to theoretical Distribution Models Fitting to Severity Models (Loss Probability Distribution) Fitting to Frequency Models (Probability of Event Frequency) Numerical Distributions Construction by Self Assessment Mapping Events and Loss Data from external Sources Use Network Representation of Bank Processes based on: Nodes, Rules and Distribution Aggregation Expressions Script Language to ensure high level of Flexibility Connection of Distributions to leave Nodes of Network Perform Monte Carlo Simulation over the Network Aggregate total OR Loss Distribution and obtain OR VaR Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 31

32 Advanced Measurement Approach (AMA) Data Modeling for Operational Risk Interviewing experts in business lines Identify OR types (e.g. Basel II definition) Mapping OR types to business lines (Basel II) Definition of loss event data base Import the own data in data base Using and mapping of external OR data bases Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 32

33 Advanced Measurement Approach (AMA) Stochastic Data Modeling No requirements for the selection of a particular model or distribution function of parameters such as: Frequency - Poisson, Negative binomial, Binomial Severity - Lognormal, Weibull, Pareto, Gamma, Inverse Gaussian Banks should demonstrate that their approach meets the standard of comparability to internal models for assessing credit risk (1-year horizon and 99.9% confidence) The model should cover the main risk factors, including potential extreme losses Correlation can be used if the system exposes stable calculation, fully encompasses the activities which take account of potential cover of stress situations Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 33

34 Advanced Measurement Approach (AMA) Stochastic Modeling Assumed Distributions for Severity 4 Parameter Generalized Beta 1 Generalized Beta 2 3 Parameter Beta 1 Log-t Generalized Gamma Beta 2 Burr 12 2 Parameter Power Log-Cauchy Lognormal Weibull Gamma Pareto 1 Parameter Uniform Normal (Gaus) Rayleigh Exponential Model Quality Test by Kolmogorov-Smirnov Method Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 34

35 Advanced Measurement Approach (AMA) Stochastic Modeling Assumed Distributions for Frequency Poisson Binomial Negative Binomial Geometric Hypergeometric Polia-Appli (Poisson-Geometric) Model Quality Test by Chi-Squared Method Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 35

36 Advanced Measurement Approach (AMA) Stochastic Data Modeling Distribution Aggregation Steps Aggregation of Severity and Frequency Distribution Models 1 Step: Sample Frequency Distribution (for example Poison) 2 Step: Sample Severity Distribution (for example Lognormal) many times as given in Step 1 by Poison Distribution 3 Step: Sample possible Recovery Distribution and reduce Losses 4 Step: Cumulate Losses for Step2 accounting for Recovery of Step3 5 Step: Repeat times Steps 1,2,3,4 and build Loss Distribution 6 Step: Obtain OR VaR at 99,9 % Confidence Level Testing the Prediction Quality Back Testing using historic loss event series Use Kupiec Test or Q-Test (Crnkovic-Dracham) Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 36

37 Advanced Measurement Approach (AMA) Severity of Loss Events Example Figures Class Definition Loss Volume (EUR) A Catastrophic >= 30 Mio B Large 5 Mio < B < 30 Mio C Middle 0.5 Mio < C < 5 Mio D Small < D < E Minor < Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 37

38 Advanced Measurement Approach (AMA) Frequency of Loss Events Example Figures Class Definition Expected Event Frequency A Extremely high < 50 times in year B High 10 < B < 50 C Middle 2 < C < 10 D Low 1 < D < 2 E Extremely Low Very rarely, once every years Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 38

39 Advanced Measurement Approach (AMA) List of Basic Key Indicators for Operational Risk 1. Internal fraud: Unauthorized Activity, Theft and Fraud 2. External fraud: Theft and Fraud, Systems Security 3. Employment Practices and Workplace Safety : Employee Relations, Safe Environment, Diversity & Discrimination 4. Clients, Products & Business Practices: Suitability, Disclosure & Fiduciary, Improper Business or Market Practices, Product Flaws, Selection, Sponsorship & Exposure, Advisory Activities 5. Damage to Physical Assets: Disasters and other events 6. Damage to Physical Assets: Disasters and other events 7. Execution, Delivery & Process Management: Transaction Capture, Execution &Maintenance, Monitoring and Reporting, Customer Intake and Documentation, Customer / Client Account Management, Trade Counterparties, Vendors & Suppliers Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 39

40 Advanced Measurement Approach (AMA) Hierarchic Network for OR Simulation and Aggregation OR VaR VaR VaR Result Business Units Business Lines Bank Processes BL1 BL3 BL2 Script for Bank Structure Basic Key Indicators Distributions Monte Carlo Simulation Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 40

41 Probability Advanced Measurement Approach (AMA) Operational Risk Distribution an Confidence Levels Recognition by Provisions and prices 50% of distribution square 99,9% of distribution square Capital Requirements Can t be assumed by bank Expected Loss (ЕL) Unexpected Loss (UL) OR VaR Stress (catastrophic) Loss (CL) OR Losses The model should cover the level of expected and unexpected losses. The bank may be allowed accounting unexpected loss only if he proves that he is able to assess adequately provisioned and the amount of expected losses Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 41

42 Advanced Measurement Approach (AMA) Example Network for OR Simulation and Aggregation OR Total VaR VaR BANK VaR Result INVESTMENT BANKING BU1 BU2 BANKING Business Units Corp. Finance BL1 Trading& Sales BL2 Retail Banking BL3 Comm. Banking BL4 Basel II Business Lines External Fraud Clients, Products, Bus. Services Basic Indicator Distributions Execution, Delivery, Processes Basel II Oper. Risk Event Types > Integration, Mapping Business Process Model to Basel Bank Model? Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 42

43 Advanced Measurement Approach (AMA) Theoretic Distributions for Basic Key Factors Possible assumptions of example theoretic distributions for Basic Key Factors: Normal Lognormal Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 43

44 Advanced Measurement Approach (AMA) Theoretic Distributions for Basic Key Factors Possible assumptions of example theoretic distributions for Basic Key Factors: Beta Rayleigh Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 44

45 Advanced Measurement Approach (AMA) Theoretic Distributions for Basic Key Factors Possible assumptions of example theoretic distributions for Basic Key Factors: Weibull Inverse Normal Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 45

46 Advanced Measurement Approach (AMA) Editing and Aggregation of Distributions for Basic Key Factors Left and right min and max values can be set to adjust the distribution X - axis The distribution profile can be edited by mouse allowing for user defined distribution shape Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009,/ Page 46

47 Advanced Measurement Approach (AMA) OR VaR from Result Distribution at Confidence Level Distribution mean = Expected Loss = 25,30 Unexpected Loss OR VaR = 13,98 Value at confidence = 39,28 Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009,/ Page 47

48 Advanced Measurement Approach (AMA) Aggregation Operations of Distributions in Risk Framework Algebraic Distribution Operators Add two Distributions Add Constant to Distribution Multiply two Distributions Multiply Constant to Distribution Scale Distribution Value Scale Distribution Probability Normalize Distribution Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 48

49 Advanced Measurement Approach (AMA) Severity, Frequency and Recovery Input Distributions Internal Frauds Result Distribution External Frauds Expected Loss and OR VaR Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 49

50 Advanced Measurement Approach (AMA) Simple&Cumulative Result Distributions for Business Units Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 50

51 Advanced Measurement Approach (AMA) Correlation Matrix (default values) Correlations between each two OR Indicators Values from -1.0 to 1.0 The upper triangle matrix is editable Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 51

52 Advanced Measurement Approach (AMA) Correlation Matrix (loaded from Data Base) Load Correlation Matrix Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 52

53 Advanced Measurement Approach (AMA) Loss Distribution Reporting on Business Units Level Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 53

54 Advanced Measurement Approach (AMA) Monte Carlo Simulation Approach Aggregation Principle Loss Event Correlation Matrix Normal Distributed Correlated Random Samples Cumulative Distribution Lognormal Distribution Aggregated Distribution Equally Distributed And Correlated Random Samples (0...1) Cumulative Distribution OR Net Work Aggregated Values Beta Distribution Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 54

55 Advanced Measurement Approach (AMA) Monte Carlo Simulation Approach Data Flow Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 55

56 Advanced Measurement Approach (AMA) Monte Carlo Aggregation Approach Different OR Sources Monte Carlo Simulation Example weigth 0,45 0,25 0,30 From Loss Data Base Potential Losses From Self Assessment Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 56

57 Advanced Measurement Approach (AMA) Back Testing and Adjustment of Probability Distributions Severity Database for internal losses 5 years Frequency Monte Carlo Simulation Gross economic capital by loss event type Extern Loss Data Correction of probability distributions 1. Internal fraud 2. External fraud 3. Employment Practices and Workplace Safety 4. Clients, Products & Business Practices 5. Damage to Physical Assets 6. Damage to Physical Assets 7. Execution, Delivery & Process Management Total gross economic capital Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 57

58 Advanced Measurement Approach (AMA) Consolidation along the Bank Structure in Risk Framework Finance Centers and Divisions of a Bank Concern Hierarchy of Finance Centers and Divisions Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 58

59 Advanced Measurement Approach (AMA) Current steps in AMA Development Data Sourcing Internal historic Events and Loss Data Mapping Events and Loss Data from external Sources Fitting internal historic Series to theoretical Distribution Models Numerical Distributions Construction by Self Assessment Aggregation of Key Factor Distributions: From Loss Data Base From Potential Loss From Self Assessment Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 59

60 Risk Framework using WEB Browser Interface Examples of OR Models - BIA Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 60

61 Risk Framework using WEB Browser Interface Examples of OR Models Self Assessment Internal Fraud Model Questionnaire Basel II: Operational Risk Implementation based on Risk Framework/ Feb 24, 25, 2009 / Page 61