Transcript OFSA SIG 2004

Oracle Banking Data Template
Catalin BOGDAN
Oracle Romania – Senior Presales Manager
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Overview
 Bringing together data in one place is good
 Use a predefined industry template
 Of course, not all banks are the same
 Oracle BDT is wide ranging
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What is the Template?
 NOT a PRODUCT, IT’s a SOLUTION
 Collection of unified banking terms/data
organized into groups and containing relations
among them, describing banking
activities/operation.
 TEMPLATE for Logical Data Model as part of
DW projects.
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Business & Conceptual Model
Party
Event
Legal Contract
Account
Product
Transaction
Channel
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Why is it good?
 Customer analytics – ranging from customer value
analysis through to the application of data mining for
customer segmentation, cross-selling opportunities,
fraud detection etc.
 Economic and regulatory capital allocation to support
the calculation of Risk Adjusted Performance
Measurement – RAPM (RORAC, RAROC or
RARROC)
 Support Basel II, AML, IAS, compliance with SOX or
other Performance Management requirements &
measures.
 Seek to get a common definition of terms across a
business.
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REPORTING & ANALISYS
PILLARS I, II, III
RISK ADJUSTED PERFORMANCE MANAGEMENT
PILLAR I,II,III
PROFITABILITY
MINIMUM CAPITAL REQUIREMENTS
Credit Risk
Market Risk
Operational Risk
ASSETS AND
LIABILITIES
MANAGEMENT
AUDIT
INTERNAL PROCESSES
&
REGULATORY COMPLIANCE
Multidimensional
budgeting
(per product,
LOB, cost
center, business
unit)
Interest rate risk
(Banking Books)
PILLAR I
TRANSFER PRICING
Foundation for RWA
Operational Risk
MARKET
RISK
(VaR)
PILLAR I
PILLAR I
PILLAR II, III
BUDGETING
AND
PLANNING
PILLAR II, III
(Basel II
consequence)
DATA REPOSITORY
DATA MART
Profitability & Risk
Management
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Process Integration
General Ledger
Consolidation
DATAWAREHOUSE - Banking specific info
PILLARS I, II, III
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Objectives and roles
 Save time and money by building on years of
experience
 Defines data attributes required for management
information across the bank
 Introduces data constancy across the organisation
 Extendibility, providing a platform to model the bank’s
unique requirements
 Design basis for analysis
 Enables a business conversation, link IT and business
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Customer Analysis
 Segmentation
 Customer value analysis
 Retail banking analysis
 Corporate banking
analysis
 CRM
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Risk Analysis
 Credit Risk
 Credit Analysis
 Operational Risk
 Scoring, rating
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Performance Measurement
 Customer/Product profitability
 Teller performance
 Cost allocation
 Transfer Pricing
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Channel Utilization
 Sales report
 Campaing
 Channel utilization
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Experiences – Business side
 Visual understanding of the planned DW
 Accelerate business requirement survey
 Common definitions used across the bank
 Guideline for mapping Business processes &
products
 Report requirements could be easily validated
 Suggestions for Basel II (especially for PD, LGD
modeling)
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Experiences – IT side
 Early discussions on what data are available
and from which source system
 Accelerate logical data modelling, DW design
 High level data mapping between DW and
source system was supported
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BDT references, projects
 Data Warehouse project using BDT
–
–
–
OTP Bank, HU – Marketing, Basel II
K&H Bank, HU (KBC sub – Customer Analysis,
Performance measurement
DSK Bank, BG – Basel II, Controlling, Risk Analysis,
Customer Analysis
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