leveraging an enterprise-wide stress testing automation
DESCRIPTION
This presentation, from a seminar co-hosted with PRMIA on October 22, discusses the following: 1. Stress testing industry challenges, such as the main areas of focus from regulators, governance, technology, process and reporting, and data and models. 2. Best practices of efficient infrastructure and data management, such as workflows, automation, datamarts, and risk data aggregation principles. 3. End-to-end automation across models, scenarios, and reporting.TRANSCRIPT
Leveraging an Enterprise-wide Stress Testing Automation
OCTOBER 22, 2014
Agenda
1. Stress Testing Industry Challenges
2. Best Practices of Efficient Infrastructure and Data Management
3. End-to-End Automation across Models, Scenarios, and Reporting
4. Conclusion
3
Global regulatory radar: growing trends of stress test regulations and data integration
Source – Moody’s Analytics market research and own analysis as of April 2014
AS
IA P
AC
IFIC
EMEA
AM
ER
ICA
S
2014
2015
2016
2017
2014
2015
2016
2017
20132014201520162017 2014 2015 2016 2017
CRD IV/CRR
CCAR/DFAST ST
EBA / ECB ST
B3/ CRDIV
Volker Rule
Review of trading book (market risk)
Large exposures/ concentration risk
Basel 3 (IRB) Vickers Reform
LEI
Review of Securitization rules
LCR framework
Basel 2Basel 3
Global systemic risk report (FED)
Basel 3
UK FDSF Basel 3 (STD)
Stress tests FBO
Cover Bonds Rule 3
Review of trading book (market risk)
Large exposures/ concentration risk
Review of Securitization rules
Review of trading book (market risk)
Large exposures/ concentration risk
Review of Securitization rules
LEI
LEI
Basel 3
RBC 2/ ERM Ins. Inv.req
CROSSIBA
Superann. Req. Ins Prud. Stand
SAM
Full Solvency II
Solvencia II
SII-like P1 BMA
ORSA
SST
ORSA US
AIFMD
CRDIV AM?
MIFID II
UCITS Liquidity Stress Test
MMF Internal Ratings/ST
CCP EMIR
G-SIIs rules
G-SIIs rules
G-SIIs rules
SIFI surcharge & risk mgt
SIFI surcharge & risk mgt
SIFI surcharge & risk mgt
UK ICAS
NIMM
NIMM
COREP/ FINREP
ECB CR4
IFRS 4,9
LCR
LCR
Insurance Capital Standard
Insurance Capital Standard
Insurance Capital
Standard
Interim Measures
SII Interim Measures
NIMM
CCAR/DFAST ST
Capital Plan Submission1
CRR LCR2
CRR LCR2
Qatar Insurance Prudential rules
IRDA risk-based solvency
Capital Rules & Final Market Risk Rule)
BoE / PRA ST(Top 8 banks)
BoE/PRA ST (Top 8 banks + Mid sized + SIFIs)
Internal Ratings
ICAAP
ICAAP / ILAAP
ICAAP / ILAAP
ICAAP / ILAAP
CCAR/DFAST ST
CCAR/DFAST ST
ICAAP
ICAAP
ICAAP
Retail Banks ST
FSA ST
FSA ST
FSA ST
Blue – Stress Testing-related Regulatory Requirements
Black – Other Regulatory Requirements
BoE / PRA ST
ICAAP
EBA/ECB ST
FI/Riksbank ST
FI/Riksbank ST
FI/Riksbank ST
Retail Banks ST
Stress Testing – Main Areas of Focus from Regulators
» Increased expectations for scenario design
» Firm-wide risk identification and assessment
» Auditing and automation
» Risk data aggregation (RDA)*
» Analytics: Granular models; challenger process
» Narrative: Validation, documentation, and calibration
» Road mapping: Show a commitment to building out processes, controls, and governance of/for the exercise
*Principles for Effective Risk Data Aggregation and Risk Reporting; Basel Committee on Banking Supervision. January 2013
Stress Testing – Industry Challenges
Process & Reporting
» Integration of stress testing with forecasting processes and resources
» Increasing frequency of stress testing
» Lack of harmonization between regulatory stress testing methodology and accounting
» Evaluation of banks on the basis of ex-ante / ex-post analysis (i.e., backtesting)
» Auditability of results
» Publish reports in required format; fully automated process
2
Technology
» Spreadsheet-based infrastructure
» Manual processes constrain:- Frequency of stress testing- Reconciliation (FINREP, COREP) and
controls- Ability to analyze results
» Competing priorities:- Need for long term infrastructure
planning and enhancements - Short-term stress tests timeline
» Existing infrastructure not well-suited for stress testing process
3
Governance
» Coordination efforts across finance, treasury, and risk groups
» Need for timely communication through chain of command as C-suite and senior management are engaged in scenario definition, results review
» Ongoing board education efforts
» Transparency of the process
1
Models & Data
» Methodologies continue to evolve
» Emphasis on greater granularity
» Consistency of loss estimation and new business methodologies
» Quantifying “unknown unknowns”
» Event-driven scenarios need to use thorough and well-governed analysis rather than routine models
4
The Industry’s Response Focuses on Automating & Streamlining the Stress Testing Process across the Enterprise
• Data quality and integrity
• Harmonized NPLs and RWAs definitions
• Regulatory and internal driven scenarios
• Strategic planning
• What-if analysis
• Inclusion on the living wills
• Quantify contingency planning metrics
• Linkage stress testing to capital plan
• Dynamic balance sheet forecasting
• Pre-provision net revenue forecasting
• Margins & Volumes
• M&A activity
• Early warning indicators
• Growth strategy, M&As, deleverage
• Setting risk limits & RAROC pricing
• Capital allocation
• ILAP
• LCR forecasting
• Funding projections
• Liquidity stress testing
• HQLA optimization strategies
• Forecasting dividend policies
• Reverse Stress Testing
• RoE/RoA analysis/projections under scenarios/strategies
• Budgeting planning
Stress Testing
AQR & Balance Sheet
Reviews
Strategic Planning & Forecasting
Capital Planning &
ICAAP
Risk Appetite
Liquidity Planning &
Management
Dividend Planning & Budgeting
One of the biggest challenges for banks is coordinating the stress testing process amongst the different stakeholders in a way that is transparent, controlled, auditable, dynamic, and repeatable
Source – Moody’s Analytics
How Are Institutions Using Stress Testing? Capital Planning & Risk Management is High on the agendas of Banks and regulators
Regula
tory
Com
pliance
Capita
l Adeq
uacy
Mea
sure
men
t and P
lannin
g
Risk
Appetite
Def
initi
on
Risk
Man
agem
ent a
nd Mea
sure
men
t
Finan
cial
Pla
nning /
Budgetin
g, Stra
tegic
Pla
nning
Limit
Settin
g and M
easu
rem
ent
Portfolio
Stru
cturin
g
Pricin
g
Source – Moody’s Analytics
Stress Testing – Key Areas of Investment / Changes Planned for 2015 and Beyond
Process/Workflow Infrastructure Governance Structure Organization
Source – Moody’s Analytics
Do Banks Have a Roadmap for Improving the Stress Testing Results Over the Next Two Years?
Yes 77%
No 23%
Key areas of enhancement in the roadmap – Modeling / automation of the process / risk data aggregation / staffing / reporting / governance
….but it is a work in progress to define the contents of the
roadmap.
Source – Moody’s Analytics
Agenda
1. Stress Testing Industry Challenges
2. Best Practices of Efficient Infrastructure and Data Management
3. End-to-End Automation Across Models, Scenarios, and Reporting
4. Conclusion
The Stress Testing Workflow
Structured
Corporate CRE C&I Retail
Forecast RWA
Required Capital
Forecast NCO / ALLL
Forecast Other Losses
Forecast Net Interest Income
Forecast Non-Interest
Inc / Exp
PPNR
Changes to Available Capital
Business Forecasting
Models
Forecast Positions
P & L Models
Financial Planning & Analysis
• Other revenue• Op losses• Trading losses• Counter-party
losses• Other expenses
Forecast Positions
Treasury / ALM
• Base Runoff• New Business
Interest Income / Expense Models
Market Risk
Strategy / Risk
Appetite
Regulatory Reports
Key Performance Indicators / Balanced Scorecard Variables
Source Database
Source Database
Source Database
Current PositionsRegulator Scenarios
Stress Testing Inputs
Economic Variables and Alternate
Scenarios
Pricing Curves
C & I
Credit Models
CRE
Mortgages
Credit Cards
Auto
Other
Forecast Positions
Op Risk
Market Risk
Risk
12
Stress Test Infrastructures and Automation Leverage the Effective Risk Data Aggregation Principles
Overarching governance
and infrastructure
Risk data aggregation capabilities
Risk reporting practices
Supervisory review, tools,
and cooperation
3. Accuracy and Integrity
4. Completeness
6. Adaptability
5. Timeliness
1. Governance
2. Data Architecture and
Infrastructure
7. Accuracy
8. Comprehensiveness
10. Adaptability
9. Clarity
11. Distribution
12. Review
14. Home/Host Cooperation
13. Remedial actions/supervisory
BIS will start to assess the above principles implementation starting 2013 and to comply by 2016
Not enforceable, but APRA is aligned with core principles (validation, automation, timeliness, control, etc.)
13
Best Practice Infrastructure: a Centralized Datamart to integrate Counterparty, Credit Risk, and Finance data
Central Datamart3 Tier Infrastructure
CalculationRules
Historical Views
CalculationWorkspaces
Portfolio
Source Systems Treasury,Investments,Assets & Liabilities,Commitments,Counterparties
Results
Overseas
Head Office
DomesticAU SG
Market Data Bloomberg, Reuters
General Ledger
GL Recon.
Capital
Items
Risks & Behavioral Models
Stress Scenario
Regulation
Configuration maintenance
Local Reporting requirements at each consolidation level
Business Rules & Workflows
Calculation & Reporting
Risk Engines
Data Editing & QueryingData Patching ToolError Checking
GL reconciliationAdjustment Workflows
Publishable ReportsDashboard & AlertsGraphical Analytics
Regulatory ReportsUpdated regularly for local compliance
Domestic
Overseas
Stress Test Data Completeness Requires a Bank-wide Data Model for Instruments and Referential Management
14
Fitness for Use: Data Quality, Correction, Validation, and Adjustments Can Be Automated at Data/Dataset Levels
» Data validation: format, type, value range, currency, presence, consistency, and completeness
» Cleansing: default value, patching, bulk-edit, adjustment, reload/upload
» Data set validation: control totaling, GL reconciliation, benchmarking, variance
15
Agenda
1. Stress Testing Industry Challenges
2. Best Practices of Efficient Infrastructure and Data Management
3. End-to-End Automation Across Models, Scenarios, and Reporting
4. Conclusion
StructuredCard
Auto
Resi
CRE
C&I
MuniOther Retail
Trading
MSR
Funding
Other
A Stress Testing System Is Seen as Mission ControlStress Test solution: the backbone to automate and integrate for firm-wide stress testing
WORKFLOW
MODEL MANAGEMENT
INPUT/OUTPUT AND ASSUMPTION
MANAGEMENT
ETL SYSTEM ACCOUNTS
HIERARCHY MANAGEMENT
» Centralized management of all primary credit models
» Can be extended to challenger credit models and econometrically-based PPNR calculations
» Supports reconcilement across all legacy “feeder” production risk and finance systems
» Supports all required regulatory and internal reporting
» Single point-of-entry to compile all stress test submission elements (inputs, scenarios, results)
» Highly configurable to support each unique client business model and user requirements
GL RECONCILIATION ACCOUNTING REPORTING
Model Inventory: Banks rely on the Stress Testing platform to centralize and monitor the catalog of models
» Commonly required details:
– Owner, validity, validation dates, Model input/output description, Upstream/Downstream dependencies
– Model documentation, comments, missing doc, alerts…
» Categorization of models per:
– Group/Portfolios/Sub-Portfolios
– Importance, Risk Types, Status…
Banks Expect Multi-jurisdictional Regulatory Reports with Granular Drill-down to Underlying Scenario Results
Internal Dashboard Can Support Results Sign-off Via Flexible Slice & Dice Across Portfolios, BU, Countries
Understand Stress Testing & Capital Forecasting Results Under Multiple Scenarios with Drill-down Discovery
Agenda
1. Stress Testing Industry Challenges
2. Best Practices of Efficient Infrastructure and Data Management
3. End-to-End Automation across Models, Scenarios, and Reporting
4. Conclusion
23
Stakeholders Expect the System to Centralize the Stress Testing and Forecasting Process across the Enterprise
» Enterprise-wide view – consistent view at a group and subsidiary level; meet regulatory and business requirements across jurisdictions
» Multiple models (internal & third-party vendor) – development and deployment of multiple models (top-down, bottom-up) from different stakeholders
» Cost-effective, consistent , centralized architecture – flexibly adapt to changes in stress testing regulatory requirements, future enhancements and integration of banks’, third-party, or regulators’ models, scenarios, and data
» Scalability, maximize return-on-investment – highly configurable framework to support changing and varied methodologies
» Drill-down and auditing capabilities – users are able to drill-down into loan-level data; audit the stress testing results and end-to-end workflow
» Off-the-shelf regulatory reporting – produces stress testing regulatory reporting and reconcile results across jurisdictions
Thank You
moodys.com
25
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