1. BASEL III Capital Adequacy Implementation,
Process Automation, and Sustainability
Saroj Das
Managing Director, KPMG
Banking & Capital Market Risk Advisory Practice

2. PwC
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 Framework
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key considerations to mitigate the effect
 Golden 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.
 Shared ownership: There should be an active inter-
department collaboration and shared ownership of the
processes and data.

3. PwC
Reference Information Architecture for Process
Automation & Sustainability
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Process & Data Governance
Technology Support

4. PwC
Data & Analytics for Capital Instruments and RWA
BASEL data collection & analytics for Capital Instruments and RWA warrant a shared ownership and
active collaboration between Risk, Finance, Regulatory Group, Internal Audit, and IT.
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March 2013
Senior Management
Process Agility & Governance
Credit Risk Market Risk Counter Party Credit Risk Operational Risk
 Capture & maintain credit risk
exposure and ref. data
 Develop & maintain credit
models (PD, LGD, EAD, UL)
 Develop & maintain stressed
credit parameters
 Capture & maintain market
risk exposure and ref. data
 Develop & maintain VaR
models (daily and 10-days)
 Develop & maintain stressed
VaR
 Capture & maintain counter
party exposure and ref. data
 Develop & maintain product
valuation & CVA analysis
 Develop & maintain EPE
models for current market
position and estimate EAD
 Develop & maintain EPE
models for stressed market
position and estimate EAD
 Capture & maintain Op-risk
events and KRIs
 Estimate & maintain Op-risk
exposure (BIA, AMA)
 Develop & maintain Op-risk
VaR
 Develop & maintain Op-risk
Stressed VaR
Technology
 Implement new rules changes
 Implement new data changes
 Implement changes to RWA
rules & calculation engine
Regulatory Group
 Maintain snapshots of risk exposure (market, credit, CCR,
and Op)
 Calculate RWAs (market, credit, CCR, and Op)
 Estimate & maintain CET1, T1 / T2 Capital
 Calculate Capital Ratios and other reg. metrics
 Maintain model ref. data & org. hierarchy
 Maintain updates of Basel reg. rules & calculation methods
 Maintain new regulatory ask and coordinates
implementation
Finance
 Capture and maintain T1 /
T2 capital instruments
 Capital deductions
Internal Audit
 Ensure information quality
and accuracy
 Ensure data quality and
accuracy

5. PwC
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 Capital ratios calculation.
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Captured & maintained by
Market Risk Department
Total CCR Capital = CCR (Default) Capital + CVA Risk Capital
CCR RWA = (Total CCR Capital * 12.5)
Calculated & maintained by
Finance / Reg. Group

6. PwC
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.
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March 2013
Credit
Risk
Market
Risk
Op-
Risk Finance
IA
Reg. Group
Functional Departments
 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.
 Identify and employ data stewards for each source of data
 Develop “golden source” information and standardized
reference data.
 Empower Internal Audit organization to audit & ensure
data quality, and to collaborate remediation.
 Improve data quality – accuracy, consistency,
completeness, and timeliness.
 Need for computational flexibility and “horse power” to
support Basel RWA calculation and risk analytics.
 Need for access to granular data from information layer.
 Establish interdepartmental collaboration and effective
communication strategy
 Promote agile process controls to adapt and implement
changes quickly.
Data
Management
Analytics &
Calculation
Engines
Organization
Processes &
Change Mgmt.
Information
Delivery