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Practical Methods that Convert Data to Dollars™
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Architects of Fact-Based Decisions™
Analytics in Financial Services:Practical Methods that Convert Data to Dollars™
Jaime Fitzgerald -- Founder and Managing Partner,
Fitzgerald Analytics, Inc.
August 18th, 2011
2Financial Services Symposium
“If You Like to Tweet…”
Symposium Collaborators
#FSIUG @AdelphiU @Oracle
Event Hashtag: #FSIUG
My Team
@JaimeFitzgerald @fitzanalytics @Data2Dollars
3Financial Services Symposium
Presentation Outline
1. Quick Intro
2. The Challenge
Business Challenges
Challenges in Addressing via Analytics
3. A Methodology That Helps: Causal Clarity™
4. Application to Your Business Models
5. From Opportunities to Results
6. Key Takeaways
4Financial Services Symposium
Introduction
Jaime Fitzgerald,Founder @ Fitzgerald Analytics
Professional Focus:
• Find & unlock opportunitiesvia data, technology, people, and processes.
Easier Ways toFind Opportunities
Better Ways toUnlock That Potential
andKey Success
Factors:
PrinciplesI Work By:
“Begin with the End in Mind” (Covey) -> Goal Definition is Key“Quality is Free” (McGregor) -> Process Matters
5Financial Services Symposium
Presentation Outline
1. Quick Intro
2. The Challenge ("The Gap")
Business Challenges
Challenges in Addressing via Analytics
3. A Methodology That Helps: Causal Clarity™
4. Application to Your Business Models
5. From Opportunities to Results
6. Key Takeaways
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A Challenging Time in Financial Services
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“Rough Seas” in Financial Services
The Tide is No Longer Rising1
Regulatory Currents Customer Behavior Shifting
Risk Management has Become Über-Strategic
New Competitive Threats
2 3
4
5
8Financial Services Symposium
1. The Tide is No Longer Rising: with a few exceptions—most notably parts of wealth management—growth no longer “just happens”….you have to make it happen
The Waters are Choppy -- with today’s trends, the captain can’t leave the helm!
2. Regulatory Currents: existing models and assumptions have been upended. Lots of “re-routing” underway to protect profits and “work around” new constraints.
3. Customer Behavior Shifting: information-empowered customers are revisiting their options, choosing in different ways, and taking advantage of more transparency
4. Risk Management has become Über-Strategic: always essential, it has become do-or-die, and harder than ever as the spectrum of risks and threats grows
5. New Competitive Threats. Non-traditional players are increasingly seeking to “poach” business from incumbent players. These sharks show up suddenly, whether from Greenwich or from the other side of the world.
Five Trends Creating “Rough Seas” in the Financial Services Market
Trends and Challenges: “Rough Seas”
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Overcoming the Challenges
While these challenges threaten, those who adapt to them best will profit.
Challenge A Path to Overcoming It... Key Performance Indicators
1. Tide not rising
Optimize profit from existing customers
Avoid attrition / protect customer equity
Retention Rate
Share of Wallet
2. Regulatory Changes
New rules change drivers of revenue and cost for our products and operations
“Explosion of redesigns” (Products, Processes, Policies, Reporting, etc.)
Product Profitability (driven by “revenue replacement” during product redesign)
Risk Mgt / Controls Performance
Cost Control / Efficiency
3. Customer Behavior
Adjust to new customer buying criteria
Retention rate
Share of wallet
Customer lifetime value
4. Risk Mgt Manage high stakes risks more robustly Risk Mgt / Controls Performance
(varies by business model)
5. Competitive Threats
Leverage sources of differentiation
Foster customer loyalty to reduce defection
Share of target segments
Customer experience + loyalty
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Five Profit Engines
These Five Analytically-Driven Profit Engines are Powerful Weapons as you Compete in Today’s Environment…
New Product Design
Adapt to new regulations, customer preferences, and costs Predict in advance the costs and benefits of product changes Systematically test product features to find the most
profitable designs
5
Customer Lifetime Value + Segmentation
Customer Retention
Cross-Sales /Up-Sales
Method
Allocate resources to your most profitable customers Use WITH predictive analytics to INFER WHO WILL be most
profitable in the future, not just the present. You won’t be right all the time, and you don’t have to be
Offer customers products they are most likely to buy Choose the optimal time, method, and terms of the offer
Keys to Profit Impact
1
2
3
Identify the drivers of customer loyalty vs. defection Target high-ROI tactics to retain most valuable customers
Marketing ROI4 Allocate marketing spend to the highest impact efforts
Use predictive models to choose best target customers, timing, message, and channel mix
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Key to Success: Integration!
New Product Design5
Customer Lifetime Value + Segmentation
Customer RetentionCross-Sales /
Up-Sales
1
2 3
Marketing ROI4
Don’t Build These Engines as Silos! Connect the Dots to Magnify Impact.
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Customer Profitability & Segmentation Analysis
Analysis of customer-level profitability reveals valuable insights regarding the differences between customers
Example: Use of customer profitability analysis to determine strategiesfor each unique group of customers…
Top(MostProfitable10%)
2nd 3rd 4th 5th 6th 7th 8th 9th Bottom(LeastProfitable10%)
Profitability Deciles(each bar represents 10% of existing customers, ranked by profitability)
Average
Illustrative1. Retain Best Customers
2. Increase Share of Wallet Among Mid-Value Customers
3. Rationalize Benefits vs. Costs Among Least Profitable Customers
Pro
fit
per
Cu
sto
mer
Loss
per
Cu
sto
mer
Cu
sto
me
r P
rofi
tab
ility
($
/ye
ar)
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Build Customer Profitability Models
Identify costs & revenues
Build profiles
Feed data from internal and external sources
Maintain data warehouses
Profitability Management Becomes More Refined Over Time through an Iterative Process Driven by Customer Knowledge
• Create consistent message
• Target action to individuals
• Optimize product / service
portfolio Data
Warehouse
New Customer Knowledge
Feed campaign results into data warehouses
Test predictive accuracy of model
Break down segment into individual customer analyses
Drive Action Into Frontline Systems
Create consistent message
Target action to individuals
Optimize product/service portfolio
Face-to-Face
Phone
InternetExternal Data
Sources
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Putting it Together: Growth and Profitability
Let’s look at four segments with different profiles, starting with their growth rates, their size, and their profitability per customer…
Gro
wth
Rat
e in
# o
f C
ust
om
ers
-20 -10 30 400 10 20 80 9050 60 70 110 120100
Direct Customer Profit
-60%
-40%
-20%
0%
20%
40%
60%
80%
1
23
4
Fast-Growing, No Profit(Product Redesign)
Profitable segment: grow faster?(X-sell / Up-sell)
Acquire More via Targeted Marketing
Size of Bubble = Number ofCustomers
Our Biggest Problem: Retention
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Integration: Connecting The Dots
New Product Design5
Customer Lifetime Value + Segmentation
Customer RetentionCross-Sales /
Up-Sales
1
2 3
Marketing ROI4
A few examples of how inter-related these processes are…
Ne
w In
form
atio
n a
nd
Insi
ghts
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Why are Analytics Projects Risky?
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Achieving the Potential of Analytics – Closing the Gap
Let’s discuss the keys to increasing your odds of success…
To profit from analytics, you need results not buzz…
Best-selling books on Analytics (Competing on Analytics, Supercrunchers, etc.) New efforts (business units, teams, roles, initiatives)
1. So Much “Buzz” about the Potential of Analytics
Selected firms have made analytics a source of competitive advantage It happens every day… just not as broadly as would be ideal
2. When Analytics Works, the Impact is Buzz-Worthy!
Right Focus Right Method Execution Results!1 2 3 4
18Financial Services Symposium
Higher Impact
Simpler
More Efficient
Simplify Your Analytic Process via “Causal Clarity”
Clearly defining “Cause and Effect” is the most crucial enabler of analysis that is
Find Opportunity
Faster
Unlock More Easily
Fewer Wasted Steps
Benefit /Cost
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Three Simplifying Concepts
To “begin with the business goal in mind,” I recommend three concepts
1. Point of Opportunity
2. Causal Clarity
3. Causal Model
Term
An opportunity for improvement within YOUR business model
Defined because it impacts key drivers of your results
Clear Definition of key drivers, cause + effect in your business model, business unit, etc.
Easy to Explain to others, preferably visually
A visual representation of “what drives results” in your business model
Create this, and you have achieved “Causal Clarity”
Definition
Cause Effect
PriceRevenue
Transactions
20Financial Services Symposium
Causal Models: A Simple “Base Case”
Each business model has an inherent “causal model,” but the “core branches” are similar
Revenue
Cost of Revenue
Operating Costs
Marketing
Overhead
Other
Gross Profit
Other Costs
Net Profit
less
less
Example: Drivers of Net Profit
Your Business Model
Has
21Financial Services Symposium
What Happens If We Skip the Causal Clarity?
…We are stuck “trying” rather than causing. We may “try hard but cause less” than if we find the “points of leverage” in the causal model
If we don’t establish a “causal model”…
…It’s pretty easy. It takes careful thought, but we are not building a spaceship…
The Good News Is…
Let’s take a look at how painless — and valuable — this can be
Why not just get to work?
22Financial Services Symposium
The Good News: Establishing “Causal Clarity” is Not Rocket Science
Easy and Quick: There are 3 Main Steps
Goal Business Model Causal Model
1 2 3
Usually net profit
Can be anything!:
– Marketing ROI
– Non-profit impact
– Customer satisfaction
– Etc.
Products / services
Distribution
Target customers
At what price
Cost structure
Known KPIs and rationale for them
Aka “drivers tree”
Makes the causal model visual
InputsTo
Use:
3 ThingsTo
Define:
23Financial Services Symposium
The “Point of Opportunity” Concept Illustrated
Your Business Model
Has “Causal Model”
(aka Drivers)A Point of
Opportunity
Creating
Returning to the causal model above on the previous slide, let’s find a concrete point of opportunity
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A Point of Opportunity
Here is an opportunity to enhance ROI on Marketing + Sales efforts:
Volume
Price per Transaction
Sales and Marketing
Transactions per Client
# of Clients
X
Point of Opportunity: “Efficiency of New Client Acquisition”
Key Driver / KPI: Acquisition Cost per New Client
Formula: [spending on new client marketing]/[# New Clients)
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What We Need to Get Practical
To get practical about analytics, we need three things…
What We Need Definition
1. Causal Clarity re: Your Business Model
How You Make Money Key Drivers of Results
2. Definition of Your Points of Opportunity
Gaps vs. Potential Room for Improvement
3. A Plan to Capture the Opportunity
Insight You Need Method to Get It
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Insights or Information Required
Analysis Methods Required to Create this Information
Required Data
Tools, Platforms, Technology, People, and Processes
Your Point of Opportunity (Decision or Process)
Translates to
Which drives
Allowing definition of
And selection of the right
Planning Your Analysis
Planning starts with the goal, the “point of opportunity”
27Financial Services Symposium
Summary of Key Takeaways
We hope you will benefit from the concepts shared today
Executives Leadership Establish “causal clarity” visually so that everyone understands Encourage teams to use this context to prioritize and target effort Expect recommendations to be justified by their impact on key drivers
Business Professionals Identify points of opportunity
before investing time in analytic details
Technology Professionals Insist upon understanding the
business context and causal logic of requests for analytic systems and effort
1. Begin Your Business Model
2. Define + Agree on the Causal Model
3. Identify Points of Opportunity
4. Define the info needed to unlock the oppor-tunity
5. Keep analysis as simple as possible…
For AllAttendees
Tips By Role:
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Invitation to Two Free Communities
This is a great place to learn and network with other professionals in analytics, both specific to Financial Services, and Beyond
To Join: http://www.meetup.com/Analytics-and-Data-in-Financial-Services/
The Practical Analytics Portal
To Join: email me [email protected] for an invitation
Our MissionTo "democratize analytics" by sharing knowledge and tools.
Our VisionThe potential of analytics "within reach" to an exponentially larger community of professionals.
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Analytics Democratized™
To Join: Text “Analytics” to 41242
….or find us on Facebook & Twitter
30Financial Services Symposium
Q & A
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“Bonus Slides”
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Background: Types of Questions Analytics May Answer
Source: Tom Davenport in “Analytics at Work”, Harvard Business School Press
We are about to get practical, let’s keep the following in mind…
Past Present Future
Information
What happened?
(Reporting)
What is happening now?
(Alerts)
What will happen?
(Extrapolation)
Insight
How and why did it happen?
(Modeling, experimental
design)
What’s the next best action?
(Recommendation)
What’s the best/worst that
can happen?
(Prediction,optimization, simulation)
33Financial Services Symposium
One More Framework: Value vs. Volume
Source: Neil Raden and James Taylor in “Smart Enough Systems,” Prentice Hall.
In some cases, analytics makes a single high stakes decision better. In other cases, we “make it up in volume”
High-Value, Low-Volume Decisions
Example: M&A, capital investment,strategic market positioning
High VolumeLow Volume Decision Volume
Low Value
High Value
Eco
no
mic
Imp
act
of
Ind
ivid
ual
De
cisi
on
Medium-Value, Medium-Volume Decisions
Example: Product development andpricing, customer segmentation, andtargeting
Low-Value, High-Volume Decisions
Example: Loan approval, customer cross-sell offer, customer upgrade request, prospect marketing offer assignment
34Financial Services Symposium
Financial Services Business Models
To get practical, let’s establish causal clarity for several key business models in Financial Services
Business ModelCore Products /
ServicesKey Drivers (illustrative)
1. Retail FinancialServices
Deposit Products Loan Products Investment Products
Customer acquisition, retention, and profitability
Product pricing Share of wallet
2. Commercial / Business Banking / Financial Services
Debt Financing Institutional Financial Services
(e.g. for Money Managers) Cash Management
Fee structure / yields Volume Cost efficiencies
3. Trading Proprietary trading Market-making Trade execution
Risk-adjusted returns Transaction spreads Cost efficiencies
4. InvestmentBanking
Underwriting M & A Other advisory services
Deal flow Deal completion rates Fee structure
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1. Retail Financial Services
* P = Profit per year per customer, n=number of years the customer stays
Illustrative Example
Point of Opportunity:
Increase ROI on Marketing SpendBY Decreasing Acq. Cost / Customer*
Key Driver / KPI: Acquisition Cost per New Client
Formula: [spend on new client marketing]/[# New Clients)
1. Deposits
2. Investments
3. Loans
Products
Volume
Profit per Product
Products per Client
# of Clients
XAllocation of Marketing $
*2nd Order Causality + Pt of Opportunity
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2. Commercial/Business Banking / FS
* “Total Client Fees” includes spending on ALL companies that offer the same or similar products/services
Illustrative Example
Point of Opportunity:
Grow Fees BY Increasing “Share of Wallet” from Corporate Clients
Key Driver / KPI: Share of Wallet (“SOW”)
Formula: [Total Fees from Client]/[Total Client Fees on Products YOU offer, via ALL providers]
Share of Wallet
Total Size of Wallet
X
The size of the pie we are sharing….
Marketing
Customer Loyalty
Client benefit of using your
platform more exclusively
Customer Experience
Optimization
Better Outreach via Predictive
Analytics
• Everything ok?• You would benefit
from product X
37Financial Services Symposium
3. Trading Illustrative Example
Point of Opportunity:
Maximize Alpha!
Key Driver / KPI: Risk-Adjusted Return
Formula: Alpha
Volume: # Trade-able
Opportunities
Quality: Profit per
Opportunity
X
Quality of Real-Time Decision Models + Tools
Trading Profits
“Cost of Discovery”
Less…
Investments in Finding these Opportunities
How “Big” are these Trades
1. Accuracy of “Triggers”2. Cost of False Positives3. How well do models
adjust to changed world?
38Financial Services Symposium
4. Investment Banking Illustrative Example
Point of Opportunity:
Increase Profit per Employee
Key Driver / KPI: Return on Human Capital (“HCROI”)
Formula: [NET Profit] / [# Employees]
Staff & Team Profit per
Person-Hour
# Hours
XStaff + Team Effectiveness
Gross Profit
“Other Investments in Staff Performance”
Less…
• Cost of analysis• Cost of training• Cost of new systems
(e.g. knowledge mgt + workflow)
1. Resource allocation (Who does what. Why?)
2. Re-use of IP: How well do we re-purpose?
3. Task Value to Cost: How much waste?
Net Profit