1. Andmeaida kasutamine Hansapangas
Indrek Heinloo
Äriteabe osakonna juhataja, Hansapank

2. Teemad Veidi andmeaida arenguloost Ülevaade mõnest äriülesandest
Kuluarvestus (Activity Based Costing)
Kasumlikkuse arvestamine
Data Stewardship

3. DWH/CRM evolution in Hansabank
1Q02 - Personal pre- calculated long-term credit limits.
Customers Regular Income calculations.
Personal pre-calculated short-term credit limits.
1Q02 - Customers needs (& products) based segmentation (v3.0)
Personal offers to customers.
Customers assets & products based segmentation (v1.x)
Customers Income & Products based segmentation (v2.0).
3Q01 - Personal credit cards & overdraft offers in HanzaNet
Customers Loyalty program (v1.0)
1Q02 – SingleView v1.0.
FTP, ABC calculations.
Customers Profitability (v1.0)
Customers Profitability v2.0
1Q02 - CM App v1.2.
1Q00 – CM App v1.0.
2Q02 - CM App v1.3.
4Q99 – Starting with NCR Teradata (V2.R3) DWH & NCR LDM (2.1)
1Q02 –Upgrading to new 2-Node MPP system WM (V2.R4.1)

4. DWH/CRM evolution in Hansabank
3Q04 –after LT data loading upgrading dwh to 4-Node
2Q 03 Data mining tool selection & purchase
2Q03 – CM platform change, multi-language support
4Q03 – SME scoring in CM EE, LV
3Q04 - CM in LT, SME scoring and contact management functionality
3Q03 – dwh based Single view of customers in LV
2Q 2003 LV, LT ABC calculations.
3Q03 – CM in LV
1Q 03 Hummingbird web version purchase & deployment LV, EE
2Q03 – EE, LV first round of loading done, incl. Markets’ data
3Q03 – EE, LV all ABC model data (except OF) from dwh
3Q03 – contact management functionality in CM
3Q03 – LT dwh loading pilot
4Q03 – customer profitability calculations on dwh data from one cube
2Q04 – EE all Powerplay cubes migrated from Analysis to dwh
2Q04 – EE all klient2.exe functionality in Single View
3Q04 – LT dwh 1st data loading round complete

5. Andmeaida esimesed kasutuskohad
Automatiseeritud müük
Segmendiarvutused
Limiidiarvutused
Automaatsed pakkumised
Operatiivne kliendihaldusprogramm (CM)
Kliendi koondvaade “SingleView”
Finantsmõõtmine
Activity Based Costing (ABC)
Fund Transfer Pricing (FTP)

6. Activity Based Costing

7. Activity Based Costing (ABC)
Product
Product
Product
Product
Product
Products
Loans
+ Interest Income
- FTP Expense
Deposits
+ FTP Income
- Interest Expense
Maturity
Mismatch
+ Interest Income
- Interest Expense
+ Net Fees
+ Other Income
- Operating Expenses
- Credit Losses
= EVA
- Capital Charge
Different Expense Types
Personnel
Administration IT
etc.
Products
Payments
Cash Services
Fund Management
etc.
Activity
Activity
Activity
Activity
Activity
Different Expense Types
Personnel
Administration IT
etc.
Product
Product
Product
Products
Product
Product
Products

8. ABC in Hansabank Resource Activity Cost Object Support Units
1. Direct allocation to Product/Channel/ Segment
Support Units
Operating Expenses
Support Activities
2. BU overhead expenses IT
Operating Expenses
IT services
Business Units
1. Operating Expenses
Cost allocation to Product/Channel/ Segment
BU Activities
2. Support and IT service expenses

9. “ABC” ülesande sisu IT jaoks
I Andmete kättesaadavus & kvaliteet
Kulude arvestus raamatupidamises
Piisav detailsus
Kvaliteet -> 100%
Toodete “faktid” dimentsionaalses struktuuris
Kõik tooted, kõik lepingud
Piisav kvaliteet +-10%
Mappingud
II Andmemahud & arvutused (1 kuu kohta):
~ 10,000 kuluallikat (Resource) (osakond x kululiik)
~ 5,000 kulukandjat (Cost Object) (toode x kanal x segment x riik)
Kokku ~ 30,000 kuluobjekti (“Account”)
Iga object on seotud keskmiselt 10 teise objektiga
Iga kulukandja on seotud läbi mudelite ~ 500 kuluallikaga

10. Kasumlikkuse arvestamine

11. Kasumlikkuse mudel
EVA (economic value added) = Net Interest + Fee Income + Other Income – Operating Expenses – Risk cost – Capital cost
interest
rate
maturity
FTP* rate
loan interest
deposit interest
deposit
income
loan
mismatch
* Funds Transfer Pricing

12. Ülesande sisu IT jaoks Andmevajaduse hüppeline kasv Segments Channels
Fact
Products

13. Ülesande sisu IT jaoks Andmevajaduse hüppeline kasv
Andmete kvaliteet -> 100% + kontrolli võimalus (!)
“Keerulised” andmed
Ärireeglid
Arvutused

14. Data Stewardship & Data Governance

15. Information Value Chain
Creation and modification
Storage
Transformation
Key issues:
Availability – information has to exist
Accuracy – information has to be correct
Consistency – information has to match definitions
Standardization – information has to be consistent throughout all transformations
Accessibility – information has to be available for end-users
Timeliness – information has to be available at the right time
Usability – information has to be presented in an efficient way
Efficiency – information has to help to make the right decisions
Comparability – information has to be comparable for different periods and usable for benchmarking
Delivery
Usage

16. Traditional business intelligence management process
Business Manager: need for management information
Sales Reporting
Portfolio Overview
Profitability + Risk Measurement
The setbacks of such setup
1. Reporting is time consuming
2. Inefficient use of human resources
3. Business formulas and definitions are kept in working files (excel)
4. Different versions of “truth” bacause of
+ differences in data between sources
+ difference in definitions
5. High risk of human error
Business Analyst:
Searching for the most appropriate data source
Data handling (excel, access, etc)
Calculations
EDW, analytical databases, operational databases:
ad-hoc queries, regular queries

17. Data Stewardship Framework
Data Users
Finance & Analysis
Risk Management
IR + CB + Swed
Marketing
Consolidation,
standardization,
translating,
documenting
requirements
Data Stewards
solution
knowledge
sharing 
requirements
requirements
solution
Data Custodians
= IT service managers
Data Owners
= Product Managers 

18. Tänan! 