The document outlines the key considerations for asset liability management, including data governance, behavioral assumptions, and cash flow analysis methodologies. It emphasizes the importance of risk aggregation, liquidity risk modeling, and various statistical methodologies to estimate client behavior. Additionally, it discusses the integration of data management in banking systems for effective scenario analysis and portfolio optimization.

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Asset Liability
Management
Vineet Khanna

2. Copyright © 2012 SAS Institute Inc. All rights reserved.
Asset Liability Mangement – Key Considerations
• Data Governance
• Data Integrity
• Models
• Processes
• Documentation
• Static
NII, Repricing gaps,
Economic value, duration
convexity, projected
balance sheet EV
• Scenarios
• Simulated values
at risk values (NII,
EVE),
Data Handling
FTP &
Profitability
Cash Flow
Analysis &
Optimization
• Methodologies
• Add on Costs
Credit
OAS
Capital Cost
Overheads
• Period End Data
Portfolio & Market
GL Recon
Behavioural Assumptions
• New Business
Templates
Volume & Rates
New Products
Chart of Accounts
• OutputData
Asset Liability
Management
Liquidity Risk &
Behavioural
Models

3. Copyright © 2012 SAS Institute Inc. All rights reserved.
Data Management
 Month End New Data
Portfolio and Market Data
Correct errors
Reviewing behavioral
assumptions
 Tying back to GL
 New products
 Behavioral Assumption
Decay / Volume Curves /
Draw Downs / Roll Overs

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New Business Assumptions
 New Business Volumes and Rates
New business templates
behavioral assumptions
 Adding new product
 Reviewing Chart of Accounts
Creating / Updating
Mappings portfolios
 Run Analysis
 Output data checks
# exposure (in vs. out)
Market data (base case and simulated states)
Review analysis log files

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Cash Flow Analysis & Optimization
 Base Case
 Scenario
 Simulation Based
 Optimization
 Stress Testing

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Liquidity Risk
 Basel III Ratios
 Scenarios
•Deposit runoff scenarios
•Risk factor scenarios
•Scenario cash flows
•Haircuts on asset values
• Intraday Liquidity Risk
• Behavioral Models

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Behavioral Modelling & Liquidity
• Statistical methodology to
estimate future client
behaviour.
•Linear Regression, Logistic Regression
•Time Series – AR, MA, ARMA, ARIMA, ARCH, GARCH, ARIMAX
•Hazard Rate Models
•Monte Carlo Simulation, Historical Simulation
•Delta Normal (Analytical) Simulation
•Trigger and Threshold Models
• Adjust contractual cashflows
to reflect the mostly likely
client behaviour.
• Transform results of these
models into estimated
cashflows
ASSETS
Prepayments
Draw-downs
Roll-over
New Business
LIABILITIES
Core / Non-core
Early redemption
Roll-over
New Business
Administered Rates

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Behavioral Modelling Workbench

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Behavioral Model - Prepayments
Interest Rates
Risk Drivers
Model Strategy
Macro Factors Client Characteristics
Endogenous Pre - Endogenous Discriminatory
∑ Prepayment_value1
-----------------------------
∑ Asset_value1
Target Variable
ContinuousTarget Variable Type
Linear RegressionModel Type

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Behavioral Model – Core / Non Core
Interest Rates
Risk Drivers
Model Strategy
Macro Factors Confidence Indices
Endogenous Endogenous Endogenous
Core
-----------------------------
Total
Target Variable
ContinuousTarget Variable Type
Historical Simulation / Linear Regression / Trigger ModelModel Type

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FTP & Profitability
 Methodologies
Matched Maturity, WAL,
Duration, Cash flow etc
 Costs
• Credit spread
• Option-adjusted spread
• Capital cost spread

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Risk Aggregation and ERM
Data Management – Data Models and Data Flows – DDS and Data Marts
Trading Systems Core Banking Loan Origination >>>
Mark to Market Portfolio Credit Risk Risk Aggregation
Market Risk Credit Risk ALM
Firm-wide
Risk
Scenario Analysis,
Risk (VaR) Calculation
Market Portfolio Optimization
Counterparty Exposure
Credit Portfolio Optimization
Cash Flow Optimization
Economic Value Calculation
Firmwide Risk Analysis
Firmwide Portfolio
Optimization
Application Common: Reconciliation, Portfolio Segmentation, Backtesting
Risk Reporting Data Model
SAS Risk Clients: Business User and Analytical Risk Users
Executive Risk Portal Add-in for MS Office Other SAS Clients
Cash Flow Analysis, FTP
and Liquidity Risk
Common Risk Foundation: Pricing Models, Cash Flow Models and Methods

13. Copyright © 2012 SAS Institute Inc. All rights reserved.
SAS RISK MANAGEMENT FOR BANKING
Data Management – Data Models and Data Flows – DDS and Data Marts
Trading Systems Core Banking Loan Origination >>>
Mark to Market Portfolio Credit Risk Risk Aggregation
Market Risk Credit Risk ALM
Firm-wide
Risk
Scenario Analysis,
Risk (VaR) Calculation
Market Portfolio Optimization
Counterparty Exposure
Credit Portfolio Optimization
Cash Flow Optimization
Economic Value Calculation
Firmwide Risk Analysis
Firmwide Portfolio
Optimization
Application Common: Reconciliation, Portfolio Segmentation, Backtesting
Risk Reporting Data Model
SAS Risk Clients: Business User and Analytical Risk Users
Executive Risk Portal Add-in for MS Office Other SAS Clients
Cash Flow Analysis, FTP
and Liquidity Risk
Common Risk Foundation: Pricing Models, Cash Flow Models and Methods

14. Copyright © 2010, SAS Institute Inc. All rights reserved.
make connections • share ideas • be inspired
Copyright © 2014, SAS Institute Inc. All rights reserved.
Vineet.Khanna@sas.com