Download SAS Data Warehouse for Risk analysis in Vilniaus Bankas AB

SAS Data Warehouse for
Risk analysis in Vilniaus
Bankas
AB Vilniaus bankas
www.vb.lt
Agenda
1. A little bit about our bank
2. Situation in Lithuania banking sector
3. Risk management concepts as we
take in our project
4. Architecture overview
5. Most important part of project Data
Model
6. SAS tools in use (some examples)
7. Data mining+DW administrator +
IntrNet=excellent solution to our bank
1. Largest bank in Lithuania
2. Have activity in all banking
sector
3. Problems transforming data to
information as usual
Some results for 1999
Profit before taxes increased by 34.7% to LTL 80.5 million
Net profit up by 24% to LTL 74.2 million
Assets of the Bank increased by 21%
Group's assets increased by 77% to LTL 5 billion during 1999
Earnings per Share LTL 4.95
Bank's Return on Equity 16.02%, Return on Assets 2.53%
Loan quality remains high despite the turbulent markets
Strong contribution from Bank's subsidiaries
Merger with Bankas Hermis completed
Very popular question. Data is everywhere
but where is information ?
Vilniaus Bankas Branches
and the transactional system is distributed
Banking sector more and more complicated
Lithuania banking sector. What
situation we have?
Market consolidation (so our portfolio is growing and becoming
more complicated
The new products and services emerge (portfolio is becoming
more complicated)
The entrance to market new players(competition increasing )
The volumes of data that we have on the hand is growing
New transactional systems emerge. So how to consolidate them ?
Decision support systems only in plans
We want the system for decision support
What choices we have?
To buy new system ?
To make everything with our programmers and
technology we know ?
Make a contract with third party company ?
Any other solution?
- Expensive
- The specialises system is difficult to integrate concerning banking management methodology
(usually the is no technical difficulties)
- Expensive maintenance and new subjects creation and integration
+ The is no headache for IT
+ We have starting methodology know-how on hand
+Guaranteed maintenance
To buy new system?
To make everything with our efforts?
- know-how shortage
- long project maturity
- The is headache for IT
+ Guaranteed maintenance
+ cheap maintenance
+ Good possibility integrating with existent systems
Our choice
Do yourself
Business process
analysis
Primary sources
analyses
Design of data model
Methodology
Administration
SAS representatives
SAS installation
Programming
Teaching
!!! Shareholder value added
That is our approach to project
Deep analysis of reporting processes in bank helped
as to make efficient reengineering of reporting and
after that efficient cost savings
We tried to minimise our need for application
customisation and maximise usage of SAS EIS
• More efforts to teach users how to work with
standard SAS tools helped us to minimise need for
programming
• After standard reports goes by the push of the key
we started to concentrate on risk management
system development
Risk factors that we
want to manage
•
•
•
•
•
•
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Interest rate
Market
Liquidity
Credit
Operational
Capital
But the first thing we must to think
it is quality of data
So how we done it ?
• First we decide to move
existing finical reports from
transactional system to
warehouse environment
• But the data models of
warehouse was not
transactional system but Risk
control in mind
Architecture overview
Financial analysis and risk management mart
Profit / lost
and internal transfer
model
Portfolio
scenarios
modulation
Interest rates
analysis
FX
analysis
Index
Time series Reporting
modulation
generator
models
DW
Multidimensional
portfolio
analysis
Liquidity
analysis
Cash flow
analysis
Tasks
Build in Multidimensional Objects (methods
and data)
reports
analysis
Additional error
check
DW
CAPTURE TRANSFORM CLEAN BUILD
Bank
transactional
system
Investment
banking
Reuters
KONDOR+
Cards
mang.system
PRIME
Leasing
company
Life
Insurance
Primary
sources
- DW The foundation to datamodel
Architecture
Business
Concept
Analyze (project)
Design (project)
A
B
Conceptiualmodell
C
C’
D
Logical datamodel
Physical datamodel
A-level
- Nine data concepts
A
B
C
C’
D
Involved
Involved
Party
Party(IP)
(IP)
Arrangement
Arrangement
(AR)
(AR)
Location
Location
(LO)
(LO)
Condition
Condition
(CD)
(CD)
Classification
Classification
(CL)
(CL)
Event
Event
(EV)
(EV)
Product
Product
(PD)
(PD)
Business
BusinessDirection
Direction
Item
Item(BDI)
(BDI)
Resource
Resource
Item
Item(RI)
(RI)
Involved Party
Arrangement
Condition
Product
LTL
%
Location
Classification
Event
SEB
Low Interest
Home Loan
Business Direction
Item
Resource
Item
One SEB
Share
B-level DM
- Three hierarchy's Involved
Party
Main
Descriptor
Occurrences within
one data concept
Additional information
about occurrences within
one data concept
Relationship
Relations between
occurrences within or
between data concepts
A
B
C
B-level in -DM
- Main-hierarchy -
C’
INDIVIDUAL EMPLOYMENT
STATUS TYPE
D
Individual
INDIVIDUAL MARITAL
STATUS TYPE
Organisation
INVOLVED
PARTY
TYPE
Organisational Unit
Employment Position
Working Individual
Not Employed Individual
Married Individual
Unmarried Individual
B-level-scoping
- Map the user needs to DM -
m1
DM
Modelled data concept in the risk mart-case
Involved
Involved
Party
Party(IP)
(IP)
Arrangement
Arrangement
(AR)
(AR)
Location
Location
(LO)
(LO)
Condition
Condition
(CD)
(CD)
Classification
Classification
(CL)
(CL)
Event
Event
(EV)
(EV)
Only a subset of the data concepts
are being modelled.
Product
Product
(PD)
(PD)
Business
BusinessDirection
Direction
Item
(BDI)
Item (BDI)
Resource
Resource
Item
Item(RI)
(RI)
C’-level in DW
- Business Objects -
A
B
C
C’
D
Involved
Party
Arrangement
Condition
Product
Individual
Product
Arrangement
Resource
Item
Accounting
Object
Transaction
Campaign
Segment
Address
A
B
Map conceptions in DM
against DW in m1
C
m1
C’
D
SEB-DM
Begrepp
SEBDW
Logisk C’-modell
Analysis tools we used
• User takes date from DW with SQL filters and reuse
tools we build
– SAS AF
– SAS EIS
– SAS BASE
– SAS GRAPH
– SAS STAT
– SAS EIS
• The main tool SAS EIS
Some examples
• The situation was extreme So we
build first Cards and Merchants
online monitoring system
• Risk management system
Cards and merchants management
Operational risk management
Good performance,online access mode , interacting with online s
as little as possible,there is no what report we need,from INFORM
possibility to learn,flexibility, statistics
Alternatives: INFORMIX,PROGRES,
JavaScript, Access, VB , C++
SAS EIS,AF
Some opinion
+ SAS EIS,DWA project time as short as possible
+ ETS, STAT, Data mining from simple to complex risk
management models realisation
+ Start in PC , and after then go to more and more powerful
server platform
+ Good maintenance (my practical experience)
+ Everything from one company
Main tasks we have
• Take data from INFORMIX (UNIX) data bases without
disturbing authorization system
• Show only changes from last snapshot
• Multidimensional analysis
• Maintenance of archive
• Take analysis from archive with the same tools
• The system must be able to learn from cheat facts
• Ho the system learns
– statistics is calculated
– we are setting priory identifications rules
– with a new data statistics is recalculated
– when we find the crime, system changes weight to statistics
• The main tool EIS
Risk management mart
Most important concerns
You must to have leader who understands
• Business
• Risk
• System analysis
• Design
• and have CEO’s support
You must to have team of specialists
• Business
• Risk
• System analysis
• Design
! Otherwise you will have substitute
Risk management mart
The first question from business
Can we find there some hidden money?
The answer
Wrong question !
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Dimensions that we use in measure risk
•
•
•
•
Lost profit
Shares price on the market
Economical share price
Others financial indicators as ROE,
ROA
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VaR (Value at Risk ) ?
• The question is very simple
• What is our portfolio value at fixed maturity with
some fixed probability measure
– Answer profit loss empirical probability probability
function
– J.P. Morgan/Reuters RiskMetrics methodology as
most know to business people
– For most analytically thinking users SAS have tools to
go more deeper
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If we look at basic VaR
methodology blocks ?
The horizons of
our prognoses
and confident intervals
Transformation of financial
portfolio instruments to
cash flow and some index
association
Transformation of
cash flow to some
fixed time
intervals
History of financial
indexes
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Evaluation of
portfolio
variation
VaR
(reports)
Results about financial instruments
variations and correlation
!
VaR
VRV
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Data Warehouse from risk management point
of view
• Consolidated reporting without
programming
• Derivatives portfolio management
• Good performance processing huge
amount of data
• VaR
• Monte Carlo
Data mining ?
• Huge amount of data analyses
• Statistics + Neural networks
SAS IntrNet
•
•
•
•
•
Administration minimum
SAS interface In internet
No need for Java coding
We are using Netscape WWW server
Standard tool remains in use