keynote on financial services analytics - presented aug 2011

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


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


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


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


A Challenging Time in Financial Services


“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


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”


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


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


Key to Success: Integration!

New Product Design5


Customer RetentionCross-Sales /

Up-Sales

1

2 3

Marketing ROI4

Don’t Build These Engines as Silos! Connect the Dots to Magnify Impact.


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)


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

Mail

Phone

InternetExternal Data

Sources


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


Integration: Connecting The Dots

New Product Design5


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


Why are Analytics Projects Risky?


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


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


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


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


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?


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:


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


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)


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


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”


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:


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.


Analytics Democratized™

To Join: Text “Analytics” to 41242

….or find us on Facebook & Twitter


Q & A


“Bonus Slides”


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)


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


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


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


2. Commercial/Business Banking / FS

* “Total Client Fees” includes spending on ALL companies that offer the same or similar products/services

Illustrative Example


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


3. Trading Illustrative Example


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?


4. Investment Banking Illustrative Example


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

keynote on financial services analytics - presented aug 2011

Business

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