BASEL III Capital Adequacy Implementation, Process Automation, and Sustainability Saroj Das Managing Director, KPMG Banking & Capital Market Risk Advisory Practice
Drivers of Change and Key Considerations BASEL regulatory regime incremental rule changes are replete with complexity around managing data, quantitative computational methods, and reporting metrics. In meeting these challenges, the financial institutions have found it necessary to establish a multi disciplinary process automation that must furnish a sustainable operating environment. Challenges arising from Basel key considerations to mitigate the Framework effec Gol t den source of data: Data at its most fundamental level requires to be collected, integrated and retained in a single data warehouse. Unified data management: The data management process must ensure reconciliation, quality, traceability, auditability, and flexibility to add & change data. Computational flexibility: The calculation and analytics engines must ensure flexibility that can run complex quantitative models and can implement rule changes fairly quickly. Adaptive reporting engine: Reporting engine must support report level calculations, validation rules, regulatory metrics & template, audit trails, access to granular data, and can implement changes fairly quickly. Future proof information architecture: The information architecture should be designed for flexibility that can anticipate changes, and implement fairly quickly. March 2013 PwC Shared ownership: There should be an active 2 inter-department collaboration and shared ownership of the processes and data.
Reference Information Architecture for Process Automation & Sustainability Process & Data Governance Technology Support March 2013 PwC 3
Data & Analytics for Capital Instruments and RWA BASEL data collection & analytics for Capital Instruments and RWA warrant a shared ownership and active collaboration bet S w en e io e r n M R an i a sk ge , m F en i t nance, Regulatory Group, Internal Audit, and IT. Process Agility & Governance Credit Risk Market Risk Counter Party Credit Risk Operational Risk Capture & maintain credit Capture & maintain Capture & maintain Capture & maintain Op- risk exposure and ref. data market risk exposure and counter party exposure risk events and KRIs Develop & maintain credit ref. data and ref. data Estimate & maintain Op- models (PD, LGD, EAD, Develop & maintain VaR Develop & maintain risk exposure (BIA, AMA) UL) models (daily and 10-days) product valuation & CVA Develop & maintain Op- Develop & maintain Develop & maintain analysis risk VaR stressed credit stressed VaR Develop & maintain EPE Develop & maintain Op- parameters models for current market risk Stressed VaR position and estimate EAD Develop & maintain EPE models for stressed market position and estimate EAD Finance Regulatory Group Capture and maintain Maintain snapshots of risk exposure (market, credit, T1 / T2 capital Technology CCR, and Op) instruments Calculate RWAs (market, credit, CCR, and Op) Implement new rules Capital deductions changes Estimate & maintain CET1, T1 / T2 Capital Internal Audit Implement new data Calculate Capital Ratios and other reg. metrics Ensure information changes Maintain model ref. data & org. hierarchy quality and accuracy Implement changes to Maintain updates of Basel reg. rules & calculation Ensure data quality and RWA rules & calculation methods accuracy engine Maintain new regulatory ask and coordinates March 2013 implementation PwC 4
Data & Analytics for RWA – CCR Illustration As illustrated below, it is germane for Market Risk department to own and champion Counter Party core transaction data, market reference data, and analytics from contract origination to the completion of the term; and then pass on the final results (e.g., Exposure, CVA value, Current market EPE, and Stressed EPE etc.) to Finance / Reg. Group for RWA and C Ca a pt p u i r t e a d d l ra & m & t ai a io nt n s ai a ncea d lculation. by by M a M r a ke k t e t R i R sk s k De D p e a p r a tm t en e t n Cal a cu c la u t la e t d e & d m & ai a nt n a t in a e in d e d by by F ina in n a ce n ce / /R eg e . g G r G ou o p u Total CCR Capital = CCR (Default) Capital + CVA Risk Capital March 2013 CCR RWA = (Total CCR Capital * 12.5) PwC 5
Data Governance and Change Management A sound governance framework is required to meet the needs of multiple internal functionalities and departments while ensuring the ongoing validity, consistency, and completeness of data across the organization. Functional Departments Cred Mark Op- IA it et Ris Finance Reg. Risk Risk k Group Data governance Clear ownership and accountability for data inputs, analytics, reporting and data hand-offs. Updated policies and procedures. Institute a centralized DG & GQ organization. Data Identify and employ data stewards for each source Management of data Develop “golden source” information and standardized reference data. Analytics & Calculation Empower Internal Audit organization to audit & Engines ensure data quality, and to collaborate remediation. Improve data quality – accuracy, consistency, completeness, and timeliness. Information Need for computational flexibility and “horse Delivery power” to support Basel RWA calculation and risk analytics. Need for access to granular data from information Organization layer. Processes & Change Mgmt. Establish interdepartmental collaboration and effective communication strategy Promote agile process controls to adapt and March 2013 PwC implement changes quickly. 6