Provides an overview of SAP HANA and how in-memory technology helps banks solve the business challenges around liquidity risk management.

1. Liquidity Risk Management
powered by SAP HANA

2. Legal disclaimer
This presentation is not subject to your license agreement or any other agreement
with SAP. SAP has no obligation to pursue any course of business outlined in this
presentation or to develop or release any functionality mentioned in this
presentation. This presentation and SAP's strategy and possible future
developments are subject to change and may be changed by SAP at any time for
any reason without notice. This document is provided without a warranty of any
kind, either express or implied, including but not limited to, the implied warranties of
merchantability, fitness for a particular purpose, or non-infringement. SAP assumes
no responsibility for errors or omissions in this document, except if such damages
were caused by SAP intentionally or grossly negligent.
© 2012 SAP AG. All rights reserved. 2

3. Agenda
What is HANA?
Challenges in Liquidity Risk Management
LRM@HANA Overview
© 2012 SAP AG. All rights reserved. 3

4. What is HANA?

5. Banks face an information availability problem
Data volume
? ?
?Calculation speed
is exploding is stagnating
Requirements on information availability are increasing
Traditional approach of OLTP and OLAP fails
© 2012 SAP AG. All rights reserved. 5

6. Boundary conditions for high performance computing
CPUs do not get faster Number of cores on the rise
CPU clock speed – memory bandwidth –
Memory and storage prices (1955-2010) memory latency
© 2012 SAP AG. All rights reserved. 6

7. In-memory computing – the time is NOW
The elements of In-Memory computing are not new. However, dramatically improved hardware
economics and technology innovations in software has now made it possible for SAP to
deliver on its vision of the Real-Time Enterprise with In-Memory business applications.
HW Technology Innovations SAP SW Technology Innovations
Multi-Core Architecture Row and Column Store
(8 x 8 core CPU in one server)
Massive parallel scaling with
many blades Compression
+
One blade ~$50.000 =
1 Enterprise Class Server
Partitioning
64bit address space
max at 2TB in current servers
100GB/s data throughput
Dramatic decline in No Aggregate Tables
price/performance
© 2012 SAP AG. All rights reserved. 7

8. SAP HANA appliance software
SAP
BusinessObjects SAP NetWeaver Other query tools
SAP HANA™ tools
In-Memory software + hardware
(HP, IBM, Fujitsu, Cisco, Dell) SQL BICS SQL MDX
Data Modeling and Data Management
SAP HANA
Real-time Data Replication
SAP BO Data Services for ETL capabilities from SAP HANA Studio and Modeler
SAP Business Suite, SAP Business Warehouse
(SAP NetWeaver BW), and 3rd Party Systems SAP In-Memory Database
SAP NetWeaver as In-Memory app. server
Calculation and Row & Column
Planning Engine Storage
Capabilities Enabled
Analyze information in real-time at unprecedented
speeds on large volumes of non-aggregated data SAP Business
Real-Time Data
Objects Data
Create flexible analytic models based on real-time Replication
Services
and historic business data
Build new category of applications (e.g., planning,
simulation) to significantly outperform current
SAP NetWeaver
applications in category SAP Business
Business
Other data
Suite sources
Minimize data duplication Warehouse
© 2012 SAP AG. All rights reserved. 8

9. Memory in TB area is becoming available on
commodity hardware
32 bit Systems 2^32 = 4.294.967.296
4GB limit per CPU
64 bit Systems 2^64 = 18.446.744.073.709.551.616
Only constraint by physics (64/128 modules)
Capacity per module grows Price per module shrinks
with new production processes with new production processes
(8GB – 16GB – 32GB) (-30% with 32nm)
1 blade with 64 modules can hold up to 1TB (16GB)
© 2012 SAP AG. All rights reserved. 9

10. Thinking in-memory
Delegation of data intense operations to the in-memory computing
High performance apps
delegate data intense
Application Layer operations to the
in-memory computing
Today‘s applications
execute many data Data Layer
intense operations in
the application layer
In-Memory Computing Imperative
Avoid movement of detailed data –calculate first, then move results
© 2012 SAP AG. All rights reserved. 10

11. SAP HANA in action – tier 1 bank
(see below for SAP LRM-specific performance results)
Standard System
73
GB
In-Memory
System
5,2 GB
60 minutes 10 seconds
© 2012 SAP AG. All rights reserved. 11

12. How HANA helps banks
Opportunities for your business
Sales, Service,
Human Resources Corporate Services Finance & Risk Transactional Banking Marketing
Strategic Workforce Advanced and Fast and accurate Transaction history Sales Analysis
Planning and optimized Finance Reporting and advanced across all channels
Reporting Purchasing analysis capabilities
Liquidity Risk Customer
Invoicing analysis Management Real time fraud segmentation and
and acceleration Accelerated detection & action exploration for cross-
Accounting Loan portfolio selling and marketing
analysis campaigns
Integrated
Profitability Monitor mission Know your customer
Management critical processes by a consistent,
up-to-date 360° view
© 2012 SAP AG. All rights reserved. 12

13. Categories of usage scenarios of SAP HANA
AFI RDL Extension
CO-PA Accelerator
Accelerators
Transaction History BW on EDW for SAP and
Financial Reporting Reporting HANA Non-SAP data
Database
Analytics on High Liquidity Risk
any data source Technology Performance Management
Applications Fraud
SAP HANA
Management
Business Suite
on HANA
© 2012 SAP AG. All rights reserved. 13

14. Available usage scenarios of SAP HANA for banks
CO-PA BW on AFI RDL Fraud
Technology Accelerator HANA Extension Management
Q1/2013
Q3/2012
Q4/2011
Q4/2011
Q2/2011 …/…
Q4/2012
Q1/2012
Q4/2011
Q3/2011 Planned
Transaction FI/CO Accelerated Liquidity Potential
History Accelerator Financial Risk Future
Reporting Management Functions
Not exhaustive
© 2012 SAP AG. All rights reserved. 14

15. SAP HANA™ provides the solution to the information
availability problem
Manage high
? ?
?Increase
data volume calculation speed
Reduce information latency
Next Gen Platform for SAP Apps integrating OLAP+OLTP
© 2012 SAP AG. All rights reserved. 15

16. Challenges in Liquidity Risk
Management

17. Funding Liquidity Risk
Internal Risk Management
Risk that the firm will not be able to meet efficiently both
expected and unexpected current and future cash
flow and collateral needs*
A first step of a funding liquidity risk calculation consists
in calculating the Forward Liquidity Exposure in terms of
the Legal Cash Flow Gap.
In a second step hypothetical cash flows should be
taken into account as well. These simulations should be
driven by market development, customer behavior and
bank strategy to generate a more realistic
Economic Cash Flow Gap.
If liquidity gaps are detected when analyzing the
economic cash flow gap, a third step consists in
calculating the Counterbalancing Capacity. All assets
like bonds or committed lines are used to resolve
potential liquidity bottlenecks.
* Basel Committee on Banking Supervision – BCBS 144 Principles for Sound Liquidity Risk Management and Supervision
© 2012 SAP AG. All rights reserved. 17

18. Market Liquidity Risk
Internal Risk Management
Risk that a firm cannot easily offset or
eliminate a position at the market price
because of inadequate market depth or market
disruption*.
This risk could come up in conjunction with OTC
trades or when solving liquidity gaps with the
release of huge positions exceeding usual trading
volumes.
Market Liquidity Risk is currently not in focus.
* Basel Committee on Banking Supervision – BCBS 144 Principles for Sound Liquidity Risk Management and Supervision
© 2012 SAP AG. All rights reserved. 18

19. Funding Liquidity Risk to be based on cash flows
being the least common denominator
Funding Liquidity Risk Management needs to be done comprehensively, all
on- and off-balance sheet positions have to be taken into account.
Cash flow view supports New Product Procedure in terms of flexibility.
Relevant reporting and steering could be done on Cash Flows.
Cash Flow roll out for complex instruments to be done by dedicated systems.
– Consistency with other risk categories crucial (e.g. different risk types based on the same
curves).
– Actual market data needed, due to illiquidity traders’ expertise sometimes required
– Complex pricing algorithms needed, difficult to replicate
– Banks often do not want to disclose pricing algorithms
© 2012 SAP AG. All rights reserved. 19

20. Liquidity Risk Management
Regulatory requirements
Issue date/
issuer 2008 2009 2010
BCBS BCBS 136 Liquidity BCBS 155 Principles for sound stress BCBS 188 Basel III:
(Basel Committee Risk: Management and testing practices and supervision International framework for
on Banking Supervisory Challenges BCBS 157 Enhancements to the Basel II liquidity risk measurement,
Supervision) BCBS 144 Principles framework standards and monitoring
for Sound Liquidity BCBS 158 Revisions to the Basel II
Risk Management and market risk framework
Supervision BCBS 159 Guidelines for computing capital
for incremental risk in the trading book
EBA CEBS (CP 28) Guidelines on Liquidity CEBS (CP36) Guidelines on
(European Banking Buffers Liquidity Cost Benefit
Authority) CEBS (CP 31) Guidelines on aspects of Allocation
the management of concentration risk
CEBS (CP 32) Guidelines on Stress
Testing
UK FSA CP 08/22 CP 09/13 Strengthening liquidity BIPRU Chapter 12:
(Financial Services Strengthening standards 2: Liquidity reporting Liquidity standards
Authority) liquidity Standards CP 09/14 Strengthening liquidity
CP 08/24 Stress and standards 3: Liquidity transitional measures
scenario testing
US Dodd-Frank Wall Street
Reform and Consumer
Protection Act
© 2012 SAP AG. All rights reserved. 20

21. BCBS 188: Basel III
Intern. framework for liquidity risk measurement, standards and monitoring
Level 1: Cash, Sovereign and Central Bank Debt
High Quality (usually 0 % Risk Weight*), …
Liquid
Assets Level 2: Sovereign and Central Bank Debt (usually 20 %
LCR Risk Weight*), AA- or higher rated bonds, …
Ratio:
Net Cash Cash Outfllows: Retail deposits, Unsecured Wholesale
Outflow Funding, Repos, CCLs, Derivative Outflow
(30 D
Cash Inflows: Reverse Repos, Obtained Credit Lines,
Horizon)
Other Inflows
Liquidity
Risk
> = 100 %
Regulatory Capital
Available
Stable
(Less) Stable Deposits, Wholesale Funding
Funding
(Sources)
All other Liabilities
NSFR
Ratio:
Cash, Securities, Debt, Off-balance Sheet Exposures
Required
Stable
Bonds, Equities, Gold, Specific Loans
Funding
(Uses)
All other Assets
* Risk Weights could be retrieved from SAP Basel II Credit Risk Solution
© 2012 SAP AG. All rights reserved. 21

22. Challenges in Liquidity Risk along
different dimensions
BASEL III requirements
New Liquidity Rules under Basel III
Reduzierung des
Ut enim ad
Moving Target as full Basel III Implementation runs to 2018
minimBASELZeithorizontes
veniam, III
quis Market
LRM Environment
Market situation nostrud exercitation
Mortgage crisis, European debt crisis, what´s next?
Increasing costs for refinancing and liquidity procurement
LIQUIDITY
Organization & processes Organi- RISK
Data
Strong collaboration between different LoBs required zation & MANAGEMENT
volumes
Change in liquidity management processes possible processes
Aktualität der
High data volumes Planungsgrundlage
mit entsprechend
Cash flow orientation causes huge data volumes
konkreten
Analytics
How to handle these volumes for ad hoc steering purposes? Zielvorgaben
Analytics
Simulations, predictive analytics, scenario analysis required
A solution needs to cover compliance, analytics and steering
Multidimensionality impacts the entire banking and liquidity arena
© 2012 SAP AG. All rights reserved. 22

23. LRM@HANA overview

24. SAP LRM@HANA meets the challenges
SAP LRM@HANA content supports Predict liquidity needs on basis of
Basel III compliance scenarios, simulations and stress
testing in real-time
Ut enim ad
Reduzierung des
minim veniam,III
BASELZeithorizontes
quis Market
nostrud exercitation
Intuitive User HANA technology allows
LIQUIDITY
Interfaces Organi- RISK for intraday processing
Data of large data volumes
Collaborative zation & MANAGEMENT
volumes
processes support processes ... in atomic granularity
Aktualität der
holistic handling of Planungsgrundlage
liquidity risk mit entsprechend
konkreten
Analytics
Zielvorgaben
Stress testing, scenario analysis and simulations
Seamless drill-down from group-level results to individual cash-flows
© 2012 SAP AG. All rights reserved. 24

25. LRM@HANA –
enabling real time Liquidity Risk Management
Extreme aggregation of 200+ Mio. cash flows in 1 second
performance real time load and analysis
extensible architecture for modeling of customer
Open platform for specific logic
specific models extensive configuration capabilities for complex
filtering, aggregation and calculation rules
what-if analysis on behavioral and market
Ad-hoc simulation parameters
and drill down single contract level including full drill down
© 2012 SAP AG. All rights reserved. 25

26. SAP Liquidity Risk Management Test Results
>60 minutes
290M
Cash
Flows 4000x faster
Aggregated
& Selected
<1 seconds
Standard System In-Memory System
© 2012 SAP AG. All rights reserved. 26

27. Product Scope LRM 1.0
SAP LRM@HANA, enables banks to perform real time,
high-speed liquidity reporting and risk management on
large volumes of individual cash flows
The application allows for pooling all types of cash
flows, including operative, simulated, and stressed
data from various SAP and non-SAP source systems
Framework to calculate risk key figures including
regulatory requirements like Basel III ratios
Users can apply basic stress factors to the data, for
example to gauge the effect of varying haircut and
run-off rates, or the re-classification of certain assets
Intuitive UIs enable business users to analyze and
compare scenarios
© 2012 SAP AG. All rights reserved. 27

28. SAP Liquidity Risk Management 1.0 Architecture
BI Comprehensive Liquidity Risk
Reporting
Netweaver High Performance Cash Flow
SAP Liquidity Risk App Aggregation and Key Figure
Calculations
ETL
SAP HANA
Cash Flow Pool (non-SAP) SAP Bank Analyzer Upload of Stressed / Unstressed
Cash Flow Engine
SAP Cash Flow Engine/ Cash Flows for Current and
Strategy Analyzer
Simulated Business
Operational Systems (SAP and non-SAP)
Loans Deposits Securities Derivatives
© 2012 SAP AG. All rights reserved. 28

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