1. Steven Parker Head CRM Consumer Banking Standard Chartered
DATA MINING IN THE FINANCIAL SERVICES INDUSTRY PRESENTATION TO KNOWLEDGE DISCOVERY CENTRE (15 FEBRUARY 2001)
Steven Parker
Head CRM
Consumer Banking
Standard Chartered

2. STANDARD CHARTERED
World’s leading emerging markets bank - Asia, Sub-Continent, Africa, the Middle East and Latin America
740+ offices (55 countries); US$90bn in assets
Key business lines:
Consumer Banking - deposits, mutual funds, mortgages, credit cards, personal loans
Commercial Banking - cash management, trade finance, treasury, custody services
Long-term commitment to Hong Kong e.g. note issuer, #1 consumer credit card etc.

3. KNOWLEDGE - WHY? THE NEW IMPERATIVE GOAL METHOD RESULT +
Identify Opportunity and Key Success Factors
GOAL
Focus on a Precise Proposition
Business Plan
Build World-Class Talent
Amass Actionable Information
Gather Purpose-Appropriate Infrastructure
METHOD
Database +
Deliver Best-of-Breed Solutions
Business Plan
Earn Customer Loyalty
RESULT
I would like
to buy ...
Earn Superior Returns
Source: Corporate Executive Board

4. KNOWLEDGE - WHY? 1 2 3 4 5 6 7 8 9 10 Revenue Years of Relationship
Cost
It is the customers usage of the product over time which has the potential to create profit
And our ability to cross-sell & up-sell other products which are also used profitably

5. Customer Segmentation
KNOWLEDGE - HOW?
Retention
Customer
Relationship
Management
New Customer
Acquisition
Re-pricing
time (
months)
6-12
Model
Customer Segmentation
Retention Model

6. KNOWLEDGE - HOW? KNOWLEDGE OF CUSTOMERS Customer Retention +
Purchase Behaviour
Service Needs
Demographics
Product Usage
Relationship
Price Sensitivity etc.
Customer Retention
Cross-sell/Utilisation +
Pricing Optimisation +
Customer De-marketing +
Product Re-design
Channel Management +
___________________________
= HIGHER PROFIT
TAILORED PROGRAMMES AND COMMUNICATION
TAILORED CUSTOMER SERVICE

7. KNOWLEDGE - HOW? Learning Time
Test & Learn Cycle –
Definitive Results
Proprietary Knowledge = Competitive Advantage
Learning
Today - some learning based on assumptions about “what worked”
Time

8. DATA MINING INTO PRACTICE
Data Warehouse
Customer Profitability/ Segmentation
Campaign Management
Contact Management

9. DATA MINING INTO PRACTICE
Taiwan DW
Hong Kong DW
Campaign
Contact
India DW
Philippines DW
Thailand DW
Malaysia DW
Campaign Contact
Singapore DW
Campaign Contact
Brunei DW
Indonesia DW

10. CHALLENGES
Changing the culture - data-driven, product to customer, volume to value
Shortage of skills - analytical, technical, marketing
Immature market e.g. vendor networks, public data, lists etc.

11. SUCCESSES Building on “early wins”
Learn from developed markets - faster cycle time
No public data = proprietary data even more valuable
Ability to combine emerging markets channels with information capabilities

12. EXAMPLE: RETENTION Predict Attrition Win-Back Contact Management
Data Warehouse
Customer Profitability
Campaign Management

13. EXAMPLE: RETENTION No Pre-Attrition No Yes Post Attrition
Attrition Gating
Yes
Yes
Retained No
Yes No
High Profit
Post Post Attrition
High Profit No
Attritors
Low Potential
Low Potential

14. Customer Segmentation
EXAMPLE: MIGRATION
Customer Segmentation
7.6% 8
9.9%
10.0%
14.2% 7
9.7% 1
17.1% 2 6
15.6%
11.4% 3 5 4
Data Warehouse
Customer Profitability
Campaign Management
Contact Management

15. EXAMPLE: MIGRATION 8 7 6 5 4 3 2 1 1 2 ( 3 5 6 ) Maintain
Retain / Grow
Segment
Focus
( )
Mass Market
Mid Market
Affluent
Migration
and Relationship
Packages
Up-sell
Re-Package
Strategic
Importance
Profitability/Balance Sheet/Potential
Branch
Branch
Channel
Usage
Mix
Self- service
Self- service

16. EXAMPLE: CROSS-SELL Depth of relationship (no. of products held)
Intensity of relationship (no. of transactions)
Data Warehouse
Customer Profitability
Campaign Management

17. EXAMPLE: CROSS-SELL Business Value Centre Wealth Secured Un-Secured
BFS
BUILD CUSTOMER VALUE
Segment 1
Segment 2
Segment 3
Customer Segments
Segment 4
Segment 5
Segment 6
Segment 7

18. EXAMPLE: CROSS-SELL Established Loyals Developing Loyals I
Share of customers
Share of profits 3% 8%
Share of customers
Share of profits 9%
44%
Multiple account holding is common
Long relationship time
High transaction activities
High phone banking usage
Highest asset balance across segments
25% of segment has high bank assets
Liabilities low
Developing Loyals II
Borrowing Potentials
Card
bill
Share of customers
Share of profits
12%
13%
Share of customers
Share of profits
10%
12%
Highest level of multiple deposit account holding
Average account balance very high
Mean age is 45
All hold credit cards
Most have loans in small amounts
Deposit balance low

19. EXAMPLE: CROSS-SELL New Savers Low Value Savers Low Activity Savers
Share of customers
Share of profits
12% 3%
Dominated by single deposit account holders
Short relationship time
Open accounts in response to promotions
Low Value Savers
Low Activity Savers z z z
Share of customers
Share of profits
10% 0%
Share of customers
Share of profits
15% 2%
Single deposit account holders – mainly saving accounts
Longest relationship time with SCB
Mean age is 50
Over-represented by females
Mostly customers with one deposit account
Dormant customers over-represented
Highest proportion of static balance

20. TARGET BENEFIT - QUICK WINS
RETENTION
High
MIGRATION
Medium/high
CROSS-SELL
Medium/low

21. FACING THE CHALLENGES Building competencies
Integrating value concepts into all points of customer contact
Re-engineering processes in marketing, sales and service
Continuing technology investment