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CONFIDENTIAL & LEGALLY PRIVILEGED
Wealth Management Solutions
Page 2© adiyanth – Distribution Restricted
Content
• Wealth Management
• Analytics as Enabler
• Typical Analytics Roadmap
Page 3© adiyanth – Distribution Restricted
Key Players in Wealth Management Delivery
1. Trusted
Advisors
2. Bouquet
of Services
3. Delivery
Channels
Customer Value Proposition
• Single Point of Contact
• Personalized Attention
• Bundled Products across Personal
Banking, Wholesale Banking & Treasury
Services
• Portfolio-Specific customized views
and reports
• Other Facilities
• Special FD Rates
• Concierge Services
Critical to Success: “Alignment of Interests”
Role of Advisors: Aid in Diversification and Risk Mitigation
Page 4
Wealth Management Business Model is based on Customer-Centricity, Service
Offering & IT Platform
Wealth Management Value Chain
Technology – Direct Banking /
CRM / Personalized View
Bouquet of Offers – Partnership
Tie-ups / Investment Services /
Portfolio Management
Trusted Advisors – Qualified
Financial Planners, Relationship
Managers, Branch Managers
Page 5
Wealth Management by Objectives – Primary Performance Metrics
Relationship Manager’s KPI
Length of Relationship
Beginner Seasoned
FinancialObjectives
Share of Mind
Share of Wallet
1. Number of Sales Contacts
2. Enrollment in Concierge Service
3. Product Holding Ratio
4. Size of Loan Portfolio
5. Assets Under Management
Page 6
Critical to Success – Managing Changing Client Expectations (Alignment of Interests)
3. Activation Efforts
- High Value Proposition
- Unique and customized
1. Solicitation Efforts
- Open & Honest
- Setting realistic expectations
- Upfront on Fee Structure
2. Account Set UP
- On-time
- First Time Right
- Welcome Kit
6. Retention Efforts
- Value Matching
- Highly Subsidized
“White Goods” offers
4. Value Enhancement Efforts
- Cross-Sell /Up-Sell
- Add-on: Family/Business Associates
- International Offerings
5. Loyalty Building Efforts
- Speaking Opportunities
- Access to “Page 3” events
- Personalized Attention
Impacts on
Life Time Value
Solution should enable a Bank’s Wealth Management team to “Keep Eye on the
Ball” across stages
Page 7
Achieving Targets - Focusing on Pipeline and Efficient “Closing”
Opinions – Favorability in Usage
Positive Neutral Negative
1. Loyalty Programs 2. Value Enhancement Programs
3. Retention Program 4. Winback Programs
5. Courtesy Calls
Behavior-SpeedtoDecision
Aggressive
Fast
Slow
2
2
2
51
1
44
3
Objective: Increase efficiency of Relationship Manager
Potential Attrition
Page 8© adiyanth – Distribution Restricted
Content
• Our Approach
• Analytics as Enabler
• Typical Analytics Roadmap
Page 9© adiyanth – Distribution Restricted
Data is the Lubricant of the Engagement Engine
• Our Approach
• Analytics as Enabler
• Typical Analytics Roadmap
Page 10
Analytics as Enabler – Overview
Marketing Mix
Models
Promotion Response
Models
Forecasting Models
Personal
Visits
Campaigns
Programs
Execution Planning
Analytics will increase Relationship Manager’s Effectiveness and Efficiency
Page 11
Analytics as Enabler (Effectiveness) - Identifying my Wealth Management Candidate
Segmentation framework follows three-step segmentation approach evaluation
process, centering around the solution’s business objectives.
1. Both attitudinal and behavioral segmentation approaches are equally well-suited for usage as
customer classification and/or description mechanisms – Identify desired functionalities
• Understanding the structure of the market
• Derive preference/affinity segments
• Use consumer attitude/preference-driven descriptive segmentation
• Require segmentation schema capable of driving cross-sell / up-sell programs
• Require assigning segments to the newly acquired customers
2. Leverage your current informational assets, but do not lose sight of the marketing need at
hand – Investigate data availability
• Rich in transactional data - use behavioral segmentation
• Rich in abounding reservoir of customer preferences – use attitudinal data
3. Differences between population and customer samples – Evaluate spatial population drift
Page 12
Analytics as Enabler (Efficiency) - Dashboards
INR 0
INR 1,000
INR 2,000
INR 3,000
INR 4,000
INR 5,000
INR 6,000
INR 7,000
INR 8,000
INR 9,000
INR 10,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
(INR 5,000,000)
INR 0
INR 5,000,000
INR 10,000,000
INR 15,000,000
INR 20,000,000
INR 25,000,000
1 2 3 4 5
INR 0
INR 10,000,000
INR 20,000,000
INR 30,000,000
INR 40,000,000
INR 50,000,000
INR 60,000,000
INR 70,000,000
INR 80,000,000
East West North South Central
Assets by RegionDaily Average in Flow
Net Flows by Product Net Flows by Region
Example – Advisor’s home page providing overview of performance
Page 13
Analytics as Enabler - Dashboards
Daily Average in Flow
2%
9%
30%
20%
8%
10%
21% Cash
International
Large Cap
Fixed Income
Other
Small Cap
Mid Cap
INR 0
INR 100,000
INR 200,000
INR 300,000
INR 400,000
INR 500,000
INR 600,000 Top Advisor Opportunities
Asset Allocation Advisorswiththegreatestriskfactors
Advisor AUM RollingProduction
ShyamSundar INR3.5Crores INR12Lakhs
AmeyaJoshi INR1.45Crores INR20Lakhs
RahulBhagat INR4.34Crores INR0.48Lakhs
SureshPatwardhan INR0.76Crores INR0.12Lakhs
ShyamalSurana INR0.54Crores INR0.23Lakhs
0
50
100
150
200
250
INR 0
INR 2,000,000
INR 4,000,000
INR 6,000,000
INR 8,000,000
INR 10,000,000
INR 12,000,000
INR 14,000,000
INR 16,000,000
INR 18,000,000
UGDC AHDF DSER FGHU HJIU
Top Recruitment Profiles
Example – Manager’s home page providing overview of business and opportunities.
Page 14
Analytics as Enabler - Dashboards
Example – Advisor’s home page providing further drilldown of customers.
Sharukh Salman Preity Nagesh Chiranjeevi Nagarjuna Mahesh Firoz Philip
AUM
Days Since Last Contact
Days Since Last Service
Service Pipeline Eligible For
Attrition Risk
Potential Score
Cross-Sell Score
Satisfaction Index
Next Revision Date
Age
Income
Prescence of Children
Occupation
Education
Lifestyles
Opinions
Brand Loyalty
Shopping Pattern
Distribution Channel Preferences
Product Preferences
Perception of Product
Needs to be fulfilled
Age
Occupation
Education
Gender
Geography
Nature of Employment
Address
Industry
Ownership
Sales Turnover / Profit
Year of establishment
Number of Locations
Geography
Export / Import
IT Budget
II. Pscychographic Information
III. Demographic Information
IV. Firmographic Data
I. Financial Drivers
Page 15© activecubes – Distribution Restricted
Content
• Wealth Management
• Analytics as Enabler
• Typical Analytics Roadmap
Page 16
Structuring Analytics Solution Engagement – 3 Year Timeline
Year 1
Define Analytics Objectives:
MIS/Decision Analytics /
Predictive Modeling/ Strategy
Design
Contact Strategy:
Developing Contact Intensity
Cross-Sell Framework:
Identifying Eligible Customers
Year 2
Refine Analytics Objectives:
MIS/Decision Analytics /
Predictive Modeling/ Strategy
Design
Automating data preparation &
Improving campaign processes
Year 3
Imbibe Analytics Objectives:
MIS/Decision Analytics /
Predictive Modeling/ Strategy
Design
Automating data preparation &
Improving campaign processes
Cross-Sell Framework:
Evaluating Product/Service
Sequencing based on LTV
Contact Strategy: Developing
contact schema based on
contact channels and messages
Automating data preparation &
Improving campaign processes
Cross-Sell Framework:
Integrating LTV metric across
service lines and products
Contact Strategy: Instituting
organization-wide contact rules
including DNC Management
• Agree on timeline for start of engagement.
• This will help plan the appropriate team to work with Wealth Management team
• Agree on sequence of projects
• This will help identify the type of data needed; and the teams can work to get this ready in
the background, while other paperwork is being worked on. This will ensure a quick start.
Page 17© adiyanth – Distribution Restricted
Social Media
Website Logs
Search Logs
Journal entries
Online Enquiries
Product feedbacks
Analytics Architecture
Data is the Lubricant of the Engagement Engine
Page 18© adiyanth – Distribution Restricted
Solution Considerations – Big Data Capabilities on a Hype Cycle
Page 19
Solution Considerations – Data Stream
C-Sat Data
Agent Logs
CRM Data
Call Transcripts
Payment Data
Data Linking
& Cleaning
Text Mining
Framework
Derived
Attributes
Framework
Common Text
Representation
Indexed XML/
CSV files
Data
warehouse
Data Sources
Data Processing & Conversion
Stage
Data Storage Stage Analysis & Reporting Stage
Assisted Insight
generation
Decision Matrix
Reporting &
Automation
Social Signals
Digital Pathways
Enabling highest data quality and governance
Page 20© adiyanth – Distribution Restricted
Solution Considerations – Structuring the Unstructured !!
Cruising Altitude (Fitness Value):
1. Sum of mutual information between cue & environment
2. Linear function of environment probabilities
Transition Altitude (Half-Life Value):
1. Qualitative Data Value =( Data Usefulness ) * ( Loss to
Competitive Advantage ) * ( Timeliness )
2. No. of days it takes for Qualitative Data Value to Half itself
Landing Altitude (Quality Value):
1. Completeness
2. Consistency & Integrity
Ground Level (Decision Value):
1. Quantitative Decision Matrix
2. Behavioral Decision Matrix
Page 21© adiyanth – Distribution Restricted
Solution Considerations –Decisions enablement
Page 22© adiyanth – Distribution Restricted
Questions?
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Wealth management

  • 1. CONFIDENTIAL & LEGALLY PRIVILEGED Wealth Management Solutions
  • 2. Page 2© adiyanth – Distribution Restricted Content • Wealth Management • Analytics as Enabler • Typical Analytics Roadmap
  • 3. Page 3© adiyanth – Distribution Restricted Key Players in Wealth Management Delivery 1. Trusted Advisors 2. Bouquet of Services 3. Delivery Channels Customer Value Proposition • Single Point of Contact • Personalized Attention • Bundled Products across Personal Banking, Wholesale Banking & Treasury Services • Portfolio-Specific customized views and reports • Other Facilities • Special FD Rates • Concierge Services Critical to Success: “Alignment of Interests” Role of Advisors: Aid in Diversification and Risk Mitigation
  • 4. Page 4 Wealth Management Business Model is based on Customer-Centricity, Service Offering & IT Platform Wealth Management Value Chain Technology – Direct Banking / CRM / Personalized View Bouquet of Offers – Partnership Tie-ups / Investment Services / Portfolio Management Trusted Advisors – Qualified Financial Planners, Relationship Managers, Branch Managers
  • 5. Page 5 Wealth Management by Objectives – Primary Performance Metrics Relationship Manager’s KPI Length of Relationship Beginner Seasoned FinancialObjectives Share of Mind Share of Wallet 1. Number of Sales Contacts 2. Enrollment in Concierge Service 3. Product Holding Ratio 4. Size of Loan Portfolio 5. Assets Under Management
  • 6. Page 6 Critical to Success – Managing Changing Client Expectations (Alignment of Interests) 3. Activation Efforts - High Value Proposition - Unique and customized 1. Solicitation Efforts - Open & Honest - Setting realistic expectations - Upfront on Fee Structure 2. Account Set UP - On-time - First Time Right - Welcome Kit 6. Retention Efforts - Value Matching - Highly Subsidized “White Goods” offers 4. Value Enhancement Efforts - Cross-Sell /Up-Sell - Add-on: Family/Business Associates - International Offerings 5. Loyalty Building Efforts - Speaking Opportunities - Access to “Page 3” events - Personalized Attention Impacts on Life Time Value Solution should enable a Bank’s Wealth Management team to “Keep Eye on the Ball” across stages
  • 7. Page 7 Achieving Targets - Focusing on Pipeline and Efficient “Closing” Opinions – Favorability in Usage Positive Neutral Negative 1. Loyalty Programs 2. Value Enhancement Programs 3. Retention Program 4. Winback Programs 5. Courtesy Calls Behavior-SpeedtoDecision Aggressive Fast Slow 2 2 2 51 1 44 3 Objective: Increase efficiency of Relationship Manager Potential Attrition
  • 8. Page 8© adiyanth – Distribution Restricted Content • Our Approach • Analytics as Enabler • Typical Analytics Roadmap
  • 9. Page 9© adiyanth – Distribution Restricted Data is the Lubricant of the Engagement Engine • Our Approach • Analytics as Enabler • Typical Analytics Roadmap
  • 10. Page 10 Analytics as Enabler – Overview Marketing Mix Models Promotion Response Models Forecasting Models Personal Visits Campaigns Programs Execution Planning Analytics will increase Relationship Manager’s Effectiveness and Efficiency
  • 11. Page 11 Analytics as Enabler (Effectiveness) - Identifying my Wealth Management Candidate Segmentation framework follows three-step segmentation approach evaluation process, centering around the solution’s business objectives. 1. Both attitudinal and behavioral segmentation approaches are equally well-suited for usage as customer classification and/or description mechanisms – Identify desired functionalities • Understanding the structure of the market • Derive preference/affinity segments • Use consumer attitude/preference-driven descriptive segmentation • Require segmentation schema capable of driving cross-sell / up-sell programs • Require assigning segments to the newly acquired customers 2. Leverage your current informational assets, but do not lose sight of the marketing need at hand – Investigate data availability • Rich in transactional data - use behavioral segmentation • Rich in abounding reservoir of customer preferences – use attitudinal data 3. Differences between population and customer samples – Evaluate spatial population drift
  • 12. Page 12 Analytics as Enabler (Efficiency) - Dashboards INR 0 INR 1,000 INR 2,000 INR 3,000 INR 4,000 INR 5,000 INR 6,000 INR 7,000 INR 8,000 INR 9,000 INR 10,000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec (INR 5,000,000) INR 0 INR 5,000,000 INR 10,000,000 INR 15,000,000 INR 20,000,000 INR 25,000,000 1 2 3 4 5 INR 0 INR 10,000,000 INR 20,000,000 INR 30,000,000 INR 40,000,000 INR 50,000,000 INR 60,000,000 INR 70,000,000 INR 80,000,000 East West North South Central Assets by RegionDaily Average in Flow Net Flows by Product Net Flows by Region Example – Advisor’s home page providing overview of performance
  • 13. Page 13 Analytics as Enabler - Dashboards Daily Average in Flow 2% 9% 30% 20% 8% 10% 21% Cash International Large Cap Fixed Income Other Small Cap Mid Cap INR 0 INR 100,000 INR 200,000 INR 300,000 INR 400,000 INR 500,000 INR 600,000 Top Advisor Opportunities Asset Allocation Advisorswiththegreatestriskfactors Advisor AUM RollingProduction ShyamSundar INR3.5Crores INR12Lakhs AmeyaJoshi INR1.45Crores INR20Lakhs RahulBhagat INR4.34Crores INR0.48Lakhs SureshPatwardhan INR0.76Crores INR0.12Lakhs ShyamalSurana INR0.54Crores INR0.23Lakhs 0 50 100 150 200 250 INR 0 INR 2,000,000 INR 4,000,000 INR 6,000,000 INR 8,000,000 INR 10,000,000 INR 12,000,000 INR 14,000,000 INR 16,000,000 INR 18,000,000 UGDC AHDF DSER FGHU HJIU Top Recruitment Profiles Example – Manager’s home page providing overview of business and opportunities.
  • 14. Page 14 Analytics as Enabler - Dashboards Example – Advisor’s home page providing further drilldown of customers. Sharukh Salman Preity Nagesh Chiranjeevi Nagarjuna Mahesh Firoz Philip AUM Days Since Last Contact Days Since Last Service Service Pipeline Eligible For Attrition Risk Potential Score Cross-Sell Score Satisfaction Index Next Revision Date Age Income Prescence of Children Occupation Education Lifestyles Opinions Brand Loyalty Shopping Pattern Distribution Channel Preferences Product Preferences Perception of Product Needs to be fulfilled Age Occupation Education Gender Geography Nature of Employment Address Industry Ownership Sales Turnover / Profit Year of establishment Number of Locations Geography Export / Import IT Budget II. Pscychographic Information III. Demographic Information IV. Firmographic Data I. Financial Drivers
  • 15. Page 15© activecubes – Distribution Restricted Content • Wealth Management • Analytics as Enabler • Typical Analytics Roadmap
  • 16. Page 16 Structuring Analytics Solution Engagement – 3 Year Timeline Year 1 Define Analytics Objectives: MIS/Decision Analytics / Predictive Modeling/ Strategy Design Contact Strategy: Developing Contact Intensity Cross-Sell Framework: Identifying Eligible Customers Year 2 Refine Analytics Objectives: MIS/Decision Analytics / Predictive Modeling/ Strategy Design Automating data preparation & Improving campaign processes Year 3 Imbibe Analytics Objectives: MIS/Decision Analytics / Predictive Modeling/ Strategy Design Automating data preparation & Improving campaign processes Cross-Sell Framework: Evaluating Product/Service Sequencing based on LTV Contact Strategy: Developing contact schema based on contact channels and messages Automating data preparation & Improving campaign processes Cross-Sell Framework: Integrating LTV metric across service lines and products Contact Strategy: Instituting organization-wide contact rules including DNC Management • Agree on timeline for start of engagement. • This will help plan the appropriate team to work with Wealth Management team • Agree on sequence of projects • This will help identify the type of data needed; and the teams can work to get this ready in the background, while other paperwork is being worked on. This will ensure a quick start.
  • 17. Page 17© adiyanth – Distribution Restricted Social Media Website Logs Search Logs Journal entries Online Enquiries Product feedbacks Analytics Architecture Data is the Lubricant of the Engagement Engine
  • 18. Page 18© adiyanth – Distribution Restricted Solution Considerations – Big Data Capabilities on a Hype Cycle
  • 19. Page 19 Solution Considerations – Data Stream C-Sat Data Agent Logs CRM Data Call Transcripts Payment Data Data Linking & Cleaning Text Mining Framework Derived Attributes Framework Common Text Representation Indexed XML/ CSV files Data warehouse Data Sources Data Processing & Conversion Stage Data Storage Stage Analysis & Reporting Stage Assisted Insight generation Decision Matrix Reporting & Automation Social Signals Digital Pathways Enabling highest data quality and governance
  • 20. Page 20© adiyanth – Distribution Restricted Solution Considerations – Structuring the Unstructured !! Cruising Altitude (Fitness Value): 1. Sum of mutual information between cue & environment 2. Linear function of environment probabilities Transition Altitude (Half-Life Value): 1. Qualitative Data Value =( Data Usefulness ) * ( Loss to Competitive Advantage ) * ( Timeliness ) 2. No. of days it takes for Qualitative Data Value to Half itself Landing Altitude (Quality Value): 1. Completeness 2. Consistency & Integrity Ground Level (Decision Value): 1. Quantitative Decision Matrix 2. Behavioral Decision Matrix
  • 21. Page 21© adiyanth – Distribution Restricted Solution Considerations –Decisions enablement
  • 22. Page 22© adiyanth – Distribution Restricted Questions?
  • 23. CONFIDENTIAL & LEGALLY PRIVILEGED Thank you