SAS Operations Risk Solutions

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SAS OpRisk Solution
A Case Study

V. K. Srivastava
Deputy General Manager
Punjab National Bank

Copyright © 2011, SAS Institute Inc. All rights reserved.

Contents
Objective
Components of SAS OpRisk Solution
System Architecture
Issues and Challenges
Future Enhancements


ORMF - Status
Organizational Setup
Policy Frameworks
Loss Data Collection
• Internal Losses
• Near Misses
• External Losses
Key Risk Indicators
Risk & Control Self Assessment Surveys
Scenario Analysis
Business Line wise Mapping of GI


Objectives
Replacement of the manual system of
collection of data with system driven
Technology; Making the existing ORM system
more robust, dynamic & accurate.
Measurement of Capital Charge under
Advanced Measurement Approach (AMA) as
against the present system of Measurement
under BIA & TSA approaches.
Make the Bank Basel compliant.


SAS OpRisk Solution – Components
SAS OpRisk Monitor
Internal Loss Data Collection
Risk and Control Self Assessment Surveys (RCSA)
Key Risk Indicators (KRI)
Scenarios generation and analyses
Issues Tracking System

BIA & TSA
SAS OpRisk Report Studio
SAS OpRisk VaR


IT System Architecture

Other
CBS Sources

EDW
Manual
SAS feed

Monitor


System Architecture
EDW CBS
Loss Data
Collection
Manual Feed CO/FPIS/IAD/
Security

Assessment ORMD/
Creation
All Business Owners
RCSA
Assessment
Response All Business Owners
Monitor
KRI Definition ORMD/
All Business Owners
KRI
EDW/
KRI Response
Assigned
Respondents
Scenario ORMD/
Definition
All Business Owners
Scenarios
ORMD/
Scenario Feed
All Business Owners


System Architecture
Report
Portal

Loss Data OpRisk
Collection VaR

Monitor External
Loss Data
RCSA - Public Loss
- CORDEX

Scenarios
KRI


Recording Loss Data
Create
Event

Create Create
Loss Recovery

Collection of Loss Events
Settled, Provided, Potential, Near Misses, Estimated etc.

Modification/ updation of existing events
Facilitates maker and checker


Reports Through Portal
Reports can be viewed by ORMD, HO & Circle Offices
through SAS OpRisk Report Link
The SAS OpRisk Reports provides following category
of reports
BIA/TSA Reports
Internal Loss Data Reports
RCSA Reports
KRI Reports
Scenario Reports
External Loss Reports
Trend Reports
Live Reports


SAS OpRisk VaR
Analytical tool; aids in performing analyses of operational
loss data for regulatory requirements

Provides the ability to normalize (scale) loss frequency and
severity data to the current size of business.

Incorporates effect of KRI & RCSA on VaR

Enables mixing of internal, consortium and external loss
data and the Scenario outputs


Project Components
Following project components are to be
created in SAS OpRisk VaR

Cross Classification variables: for 8x7
matrix

Filters: for filtering loss data

Insurance policies: imported from OpRisk
Monitor

Scale Adjustments: for scale adjusting for
size and time

Scenario collections


Empirical Matrix

Provides moments based on empirical loss data, for each of
internal, consortium and external loss data


Fitting / Displaying Diagnostic graphs


Mixing of data

SAS OpRisk VaR provides for mixing of internal and

external/ consortium loss data, and also set cell level sufficiency


Impact of Scenarios and KRI/RCSA


Computation of VaR and VaR plot


Generation of VaR Reports


Pre Requisite for SAS OpRisk
OR Policies, Systems and Procedures
Requirement of skill – Concepts & Tools
Management support
Creating value by leveraging the system
Integration with existing MI System
Technical support
Ownership & Perseverance


Ensuring completeness of data
Lack of pooled data
Updation of RDC
Creating impact of Insurance in VaR
Conduct of Scenarios
Handling Model Based Scenarios in OpRisk VAR
Estimation of Correlation


Setting relation of KRI to Loss data
Aggregation of KRIs and RCSA for OpRisk VaR
Implementation and support
System Upgradation
Documentation
Develop Understanding
Create awareness


Future Enhancements
Capturing loss data and BL-wise PL data from all
available sources through EDW.
Up-gradation of SAS OpRisk.
Leveraging SAS OpRisk solution for Fraud
Reporting from field for onward submission to FIU
Capturing of KRI data directly from :
RBIA
RBMA
HRMS
AML
FRM (Fraud)
ADC (Alternate Delivery Channels)


make connections • share ideas • be inspired
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Thank You
V. K. Srivastava
Mob: 9868879299
vishesh@pnb.co.in
vishesh1966@yahoo.co.uk


List of Rejected Loss Records during a period
Report of Updated Loss Records
List of all loss records above a fixed threshold sourced from
EDW
Analysis of Operational Losses with Business Figures
Analysis of Operational Risk Loss Data-Percentage of Gross/Net
Losses above Threshold (Q/HY/Total)
Summary of Trend Analysis of the major loss events (Q/HY/Y)
Comparative position of losses (event-wise) for the period
(Q/HY/Y)
Comparative position of losses (failed-control and cause-wise)
for the period (Quarter)
Loss Event Category wise position of loss data (Above
Threshold) during the last xx years


Top 50 losses (basis gross loss amount) by BL/LE
category for a quarter
Internal losses classified as loss event category and
causal factor wise (FY/HY/Q wise trend analysis)
Business Line wise and Loss Event wise causal factor
analysis- Borrowal related losses
Operational risk above threshold: gross losses by
business lines and loss event types in the last year
Operational risk above threshold: net losses (gross loss
amount net of all recoveries except insurance) by business
lines and loss event types in the last year
Operational risk above threshold: net losses (gross loss
amount net of all recoveries including insurance) by
business lines and loss event types in the last year


Total Loss Amount by BL/LE Type (YoY/QoQ/HYoHY
comparison)
Operational risk above Threshold:
• No. of losses and Gross Loss Amounts
• No. of losses and Gross/Net Loss Amounts by Business
Line and Generic Process
• No. of losses and Gross Loss Amounts by Business
Line and Risk category
• No. of losses and Net Loss Amounts by Business Line
and Sub-Process
• No. of losses and Net Loss Amounts by Business Line
and Cause
• No. Of losses and Net Loss Amounts by State And Loss
Event type


Mitigants available by Business Line and Event Type
for Borrowal /Non Borrowal losses
Near Miss Events: Loss involved by Business Lines
and Loss Event Types in the last year
MO wise Loss Data across BL, Division, Activity and
Risk Category
MO-Wise Loss Data Report across Business Line,
Risk Category with Process and Control
Detailed loss data for a given period


External Loss Data Reports
External loss events : Loss involved by business lines
and loss event types
External operational risk above threshold: No. of
events and gross loss amounts by state and loss
event type
External Loss Events: Bank Wise Gross Loss and
Financial Information
Top 10 External Loss Events In Q.E. (per BL-RC
combination)
Summary Of External Loss Data (YoY/HYoHY/ QoQ)


Trend Reports
Summary of Trend Analysis of the major loss events
(Q/HY/Y basis)
Internal losses classified as loss event Category and
causal factor wise (Q/HY/FY wise trend analysis)
Business Line wise and Loss Event wise causal
factor analysis- Borrowal related losses
Analysis of Operational Risk Loss Data-Percentage of
Gross Losses above Threshold (Q/HY/Y)
Analysis of Operational Risk Loss Data-Percentage of
Net Losses above Threshold (Q/HY/Y)
Comparative position of losses (event-wise) for the
period (Q/HY/Y)


Live Reports
RCSA Comments Report (Live)
RCSA User Wise Exceptions Report (Live)
CO Wise Loss Data Report (Live)


SAS Operations Risk Solutions

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