Andmeaida kasutamine Hansapangas

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 4855 (V2.R4.1) ... 1999 2000 2001 2002

4. 1Q 03 Hummingbird web version purchase & deployment LV, EE 3Q03 – dwh based Single view of customers in LV 2Q04 – EE all klient2.exe functionality in Single View 2Q 03 Data mining tool selection & purchase 4Q03 – customer profitability calculations on dwh data from one cube 2Q 2003 LV, LT ABC calculations. 3Q03 – contact management functionality in CM 4Q03 – SME scoring in CM EE, LV 3Q04 - CM in LT, SME scoring and contact management functionality 2Q03 – CM platform change, multi-language support 3Q03 – CM in LV 3Q03 – LT dwh loading pilot 3Q04 – LT dwh 1st data loading round complete 2Q03 – EE, LV first round of loading done, incl. Markets’ data 3Q03 – EE, LV all ABC model data (except OF) from dwh 2Q04 – EE all Powerplay cubes migrated from Analysis to dwh 3Q04 –after LT data loading upgrading dwh to 4-Node 2003 2004 2005 DWH/CRM evolution in Hansabank

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. + Interest Income - Interest Expense + Net Fees + Other Income - Operating Expenses - Credit Losses - Capital Charge = EVA Activity Based Costing (ABC)

8. ABC in Hansabank Resource Activity Cost Object 1. Direct allocation to Product/Channel/Segment Support Units Operating Expenses Support Activities 2. BU overhead expenses IT Operating Expenses IT services BusinessUnits 1. Operating Expenses Cost allocation to Product/Channel/Segment BUActivities 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. interest rate loan interest loan income FTP* rate maturity mismatch income deposit interest deposit income maturity * Funds Transfer Pricing Kasumlikkuse mudel EVA (economic value added)= Net Interest + Fee Income + Other Income– Operating Expenses – Risk cost – Capital cost

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

18. Tänan! 