DATA MINING IN THE FINANCIAL SERVICES INDUSTRY PRESENTATION

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

STANDARD CHARTERED • World’s leading emerging markets bank - Asia, Sub. Continent, Africa, the Middle East and Latin America • 740+ offices (55 countries); US$90 bn 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. 2

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

KNOWLEDGE - WHY? Revenue Years of Relationship 1 2 3 4 5 6 7 8 9 10 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 4

KNOWLEDGE - HOW? Retention Customer Relationship Management New Customer Management Acquisition Re-pricing 0 Acquisition Model 6 -12 Customer Segmentation time (months) Retention Model 5

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

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

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

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

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. 10

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 11

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

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

EXAMPLE: MIGRATION Customer Segmentation 7. 6% 8 9. 9% 10. 0% 1 14. 2% 2 9. 7% 17. 1% 6 15. 6% 3 4 Data Warehouse 7 Customer Profitability 11. 4% 5 Campaign Management Contact Management 14

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

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

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

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

EXAMPLE: CROSS-SELL New 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 Share of customers Share of profits Low Activity Savers 10% 0% Share of customers Share of profits • z 15% 2% • Single deposit account holders – mainly saving accounts • Mostly customers with one deposit account • Longest relationship time with SCB • Highest proportion of static balance • Mean age is 50 • Over-represented by females • Dormant customers over-represented 19 • z

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

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 21