FRTB: Revised Market Risk Framework Fundamental Review of Trading Book (FRTB) Speakers Gurpreet Chhatwal Global Head of Risk & Analytics, CRISIL Global Research & Analytics Kshitij Bhatia Director, Risk and Analytics, CRISIL Global Research & Analytics Nageswara Sastry Ganduri Director, Risk and Analytics, CRISIL Global Research & Analytics April 2016
CRISIL GR&A s Credentials Global Leader in Research & Analytics Space Pioneered Global Research & Analytics; 25-year track record Works with 10 large banks for 5+ years, of which five banks have been our clients for 10 years Our primary allegiance across all our business lines is analytical rigour DNA originates from beginnings as a rating agency and differentiates our analytical quality Strength in Research & Analytics 15 of the top 20 global investment banks 37 global buy-side firms Support 176 II ranked analysts globally Experience across 70+ global sectors Round-the-clock support across languages # 1 in client satisfaction surveys consistently Best People to Work With Team of more than 2,800 analysts 50% of the talent is from premier schools Brand image to attract and retain talent Rigorous in-house training processes Experienced management team to ensure high-touch engagement McGraw Hill Financial Inc. has been CRISIL s majority shareholder and currently has 67.03% Strong balance sheet with zero debt; Revenue of USD205mn Listed on Indian Stock Exchanges since 1993: market cap of USD2.33bn Strong Parentage & Governance Rigorous & Scalable Processes Awards & Recognitions Strong project management capabilities Quality Assurance and Governance Information Security NASSCOM Exemplary Talent Practices Award Robust training programs Business Continuity Inbuilt processes and tools to enhance productivity Talent Management Award HR Project of the Year Award by World HRD Congress, 2015 2
Fundamental Review of Trading Book (FRTB) What is Fundamental Review of Trading Book (FRTB)? Revised market risk framework by the BASEL Committee for Banking Supervision (BCBS) to Calculate minimum capital requirements for market risk Avoid undercapitalized trading book exposure Plug perceived gaps and reduce regulatory arbitrage between the Trading and the Banking Books Current Trading Book rules created after the 2008 crisis aim to raise Trading Book capital requirements 2014 2015 2016 2017/2018 Current framework had overlapping capital charges leading to double and triple counting of risks Challenging modeling issues such as liquidity and constraining diversification not addressed Standard Rule calculations were non-risk sensitive and highly conservative Timeline and Current Status 2012 2014 2014/2015 2015/2016 2016/2018 2019 FRTB Consultation Hypothetical Portfolio QIS QIS II on Full portfolio QIS III and IV on full portfolio Banks initiating tactical model improvements and Strategic Implementation Project Finalization of rules Calibration Phase (2-3yrs) Implementation and Go Live 3
Evolution of FRTB Rules Evolution Timeline May 2012, BCBS 219 Trading-Evidence based boundary vs Valuation based boundary Standardized Approach - Partial risk factor approach vs Fuller risk factor approach Internal Model Approach VaR to ES, Liquidity horizons, capital add-ons against the risk of jumps in liquidity premia December 2014, BCBS 305 Internal risk transfers between the two regulatory books Standardized Approach - development of Sensitivity Based Approach Internal Model Approach Simpler method for liquidity horizons October 2013, BCBS 265 Decision to develop trading-evidence based boundary Standardized Approach - Decision to develop Partial Risk Factor Approach using cash flow based method Internal Model Approach additional risk assessment tool for risk of jumps in liquidity premia January 2016, BCBS 352 Final rules for FRTB 4
FRTB Components and Implications Component Description Implications Trading & Banking Book Boundaries Boundaries across the books are now regulated Clear guidance on instruments Clear listing of presumptions Documentation on instruments classification Transfer of instruments between books subject to regulators approval Removal of capital arbitrage across books Standardized Approach to Market Risk Credible, risk-sensitive fall back to IMA for: Smaller Financial Institutions Desks not approved for IMA Risk sensitivities as key inputs Implementation required by all banks Regular reporting regardless of IMA Internal Model Approach (IMA) to Market Risk IMA use is conditional upon approval by the bank s supervisory authority on a deskby-desk basis Stringent approval process at desk level ES, liquidity horizons and further prescription of models Yearly validation and stress tests Back-testing and P&L Attributions Specific tests to allow capitalization through IMA on a desk-by-desk basis IMA approval contingent on successful backtesting and P&L attribution tests Yearly P&L and back-testing tests Quality and reliable data to be ensured 5
FRTB Standardized Approach The Standardized Approach to Capital Requirement Risk Sensitivities Based Charge The Default Risk Charge (Jump to Default) The Residual Add-on (Notional Method) Linear Risk Charge (Delta + Vega) Non-linear Risk Charge (Curvature) Securitised Correlated Trading Portfolio (CTP) Non Securitised Non-CTP Exotic Underlying's Residual Risks 6
FRTB Internal Model Approach The Internal Model Approach to Capital Requirement Market Risk (Expected Short Fall based) Default Risk Charge (Value at Risk based) Stressed Capital Add-on Control Structure Qualitative Standards Initial Monitoring and Live testing by supervisors PnL Attribution Back-testing Stress Testing Model Validation External validation 7
Implementation Challenges Standardized Approach Key Challenge: Data and calculation intensive risk sensitivities aggregation SBA DRC Add-On DataDATA MANAGEMENT Identification of risk factors for risk classes Risk factor definition Maintaining consistency across desks and jurisdictions Defining DRC sub-bucket criteria Identification of instruments with exotics and other residual risks Developing meta data infrastructure Model MODELS & & Calculation CALCULATIONS Managing risk data aggregation Increased computational requirements Model development for SA - DRC calculations Model validation and frequency Incorporation of additional charge for exotics and non-exotic instruments Reporting REPORTING Reporting framework for aggregated capital charge across all desks (irrespective of IMA use) Governance structure 8
Implementation Challenges Internal Model Approach Key Challenge: Intensive nature of calculation of VaR and ES for IMA Expected Shortfall DRC SES Add-On DATA MANAGEMENT Risk factor classification (MRFs Vs. NMRFs) Liquidity horizons mapping Sourcing and validation of historical market data DRC data integrity to account for stressed data period Hypothetical PL Full revaluation Risk-based PL Hypothetical Vs. Riskbased database Developing meta data infrastructure MODELS & CALCULATIONS Historical simulations Enhancing VaR and SVaR models to generate ES and Scaled ES Model enhancement to account for revised/scaled liquidity horizons Model development for IMA DRC calculations DRC validation using stress tests, sensitivity and scenario analysis Historical simulation based on full revaluation method Reporting REPORTING Exception monitoring framework Fall back process for IMA desks, breaching prescribed limit Reporting framework for disclosure to regulators Governance and monitoring 9
A Typical Implementation Charter A Robust Change Management Plan and Implementation Stage III Stage I Definition and Planning Identification of all stakeholders who would be part of the implementation charter Organize workshops and trainings for all involved parties/employees Objectives, scope, responsibilities and approach are defined and sensitized Prepare an agile based modular approach Stage II Assessment Iterative assessment and review of MR components in light of FRTB guidelines Book boundaries, model and data infrastructure, risk factor modellability, P&L attribution, backtesting and reporting Different analyses Gap analysis, Impact analysis, Deep dive analysis Preparation of BRDs and FSDs Tactical initiatives towards exploring technological and operational innovations Execution Target state definition, design and Implementation Data Models - A robust risk data infrastructure aligned with pricing framework, expected shortfall implementation and risk factor modellability framework Desk level Model Risk Management and performance monitoring Infrastructure P&L Attribution and Backtesting Desk level threshold monitoring Reporting Model assumptions, threshold breaches, intra-day desk level reporting Desk re-organization or re-alignment 10
Assessment Approaches Approach 1 Implement final rules on different sets of hypothetical/real portfolios Revised SBA, IMA, P&L attribution, back testing and reporting Test under different scenarios and portfolio complexities Linear, non-linear, illiquid Impact on and assessment of the usability of current processes Objective: To assess and understand intricacies and effort involved in final implementation at firm-wide level Pros: Bottom-up strategy gives a better grip on the rules and processes Cons: Cannot provide a barometer to understand final efforts that are required in implementation Approach 2 Implement final rules on a select few desks and scale them up slowly to larger set Objective: To run eligibility rules, identify failings and strategize on filling the gaps Pros: Current scenario and gap assessment at desk-level Cons: Can become complex and tedious with every addition of a new desk to the analyses, can be repetitive 11
FRTB Where things are Most banks are in definition and planning stage Some have started on assessments based on tactical and prototype implementations 2016 would to be the year of assessments and SBA Trading desk re-organizations and realignments being mooted to avoid stressed capital add-on for non-modellable risk factors Volcker desk structures may hurt banks in FRTB regime European banks have had a head start when compared to their US counterparts Financial Technology and Operational Innovations, with an objective to bring down capital investments Technological innovations to absorb model and data governance overheads Shared data platforms to largely solve the problem on NMRFs and thereby reducing stressed capital add-on risk charge for desks Common reporting frameworks across jurisdictions to help meet regulators requirements of consistent approach across different banks 12
Summary and Way forward Fundamental overhaul of existing market risk approach New risk metrics, processes, governance and reporting requirements will change the way banks trade Requirement of robust models and process for avoiding large increase in capital charge Way forward Keep standardised approach as an embedded backup Ensure models are built on granular data Reorganise trading desk for capital efficiency Optimise infrastructure 13
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