analytics in financial services - keynote tdwi and ny tech council - new york 2011

Architects of Fact-Based Decisions™

Analytics in Financial Services:A Competitive Imperative

Keynote Presentation: March 30, 2011

Inaugural Event on Practical AnalyticsPresentation Outline

1. Quick Intro

2. The Challenge ("The Gap")

3. A Solution to The Challenge ("Bridging the Gap")

2Analytics in Financial Services: How Analytics and Data are Changing the Financial Industry, © Fitzgerald Analytics 2011, all rights reserved


4. Application to Your Business Models

5. From Opportunities to Results

6. Key Takeaways

Inaugural Event on Practical AnalyticsIntroduction

Jaime Fitzgerald,Founder @ Fitzgerald Analytics

Professional

Mission:

To help clients find and unlock opportunities

via data, technology, and processes, while

always remembering the crucial role of people.


� Writing a book about the role of “thought-style” in the

information-era

� Collaborating with others in Analytics, Info Mgt, Data Mgt, &

Tech Innovation via Groups like TDWI, NYTC, DAMA, AIIM…

Easier Ways to

Find Opportunities

Better Ways to

Unlock That Potentialand

To Achieve

my Mission

I Focus On:

Other

Projects:

Inaugural Event on Practical Analytics

Retail Financial Services

Commercial/Business Banking / FS

Business Model Focus for Today

2

1


Trading

Investment Banking

3

4

Inaugural Event on Practical AnalyticsWhat Led to Today’s Event: “The Gap” Between Buzz and Reality

On the subject of data analytics, a gap has emerged between

buzz/hype and reality

� Best-selling books on Analytics(Competing

on Analytics, Supercrunchers, etc.)

� Entire new business units & teams

(e.g. IBM Business Analytics)

1. So Much “Buzz” About Analytics…

� Execs not yet satisfied with results

� Many professionals still not benefitting in

their roles and teams

� Lots of new tech efforts launched to meet

demand for analytics. Results vary.

2. …is not Proportional to Results


demand for analytics. Results vary.

Our goal today is to help to bridge that gap.

� Select firms use analytics unusually well,

and their profit growth shows it!

� I am a “witness” for 15 years of results

3. Analytics Does Have Potential

� You can’t deposit buzz into the bank!

� For more of us to benefit, we need:

� Simpler ways to identify opportunities

� Efficient ways to plan and execute analysis

� Transparent methods (less black boxes)

4. But This Potential Needs to Benefit YOU

Inaugural Event on Practical AnalyticsToday’s Themes

Based on our mission for today, we are guided by 3 themes

Getting Practical

� Share a Practical Methodology ...

� Explained via Real Examples…

� with Reference to Work of our

Panelists

Key Theme Therefore We Will

1


Takeaways

You Can Use

2� Be explicit about how concepts

apply to your businesses

� Review key takeaways at the end

“Bridging the Gap”

3 � Address both business context and

technical implications

� Show how the method helps bridge

the gap between business goals and

technical preconditions to those goals

Inaugural Event on Practical AnalyticsDefining a Few Terms I Will Use

To ensure clear communication, let me define up front a few terms I

will use today.

1. Point of Opportunity

Term

� An opportunity for improvement within YOUR

business model

� Defined because it impacts key drivers of your

results

Intended Meaning


2. Causal Clarity

3. Causal Model

� 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”

Cause Effect

PriceRevenue

Txns


1. Quick Intro







6. Key Takeaways

Inaugural Event on Practical AnalyticsThe Challenge: Closing the Gap between Hype and Reality

As we began to discuss… there is a “performance gap” here!

� Best-selling books on Analytics (Competing on Analytics, Supercrunchers, etc.)

� New efforts (business units, teams, roles, initiatives)

1. So Much “Buzz” about Potential of Analytics

� Selected firms have made analytics a source of competitive advantage

2. When Analytics Works, it Really Works…


� Selected firms have made analytics a source of competitive advantage

� It happens every day… just not as broadly as would be ideal

� Lots of effort, some wins, many losses… not “firing on all cylinders”

3. Yet Most Teams and Organizations are Not Benefitting Enough

What is the root cause of this “performance gap”?

Right Focus Right Method Execution Results!1 2 3 4

Inaugural Event on Practical AnalyticsThe #1 Cause: Complexity

Seeking opportunity in analytics is complex - there are “too many

options”…

1. Thousands of

Business Models

2. Infinite Decisions + Business Processes

(existing and potential)

Analytic


3. Many Types of Analysis w/

1000s of Sub-Concepts

4. Lots of Tech Tools, Platforms, Plug-ins,

Deployment Options

Analytic Initiatives

We need a way to simplify this complexity without losing the potential

Inaugural Event on Practical AnalyticsOther Root Causes of “Analytic Underperformance”

While complexity is the largest impediment to results in analytics,

there are several other challenges worth mentioning…

Cross-Functional Collaboration

Communication Challenges

1

2The good news is…


Communication Challenges

Technology and

Data Management Barriers

3

…managing complexity

makes all these other

problems easier to manage

also…

People: Talent, Skills, Learning,

Team Effectiveness

4


1. Quick Intro







6. Key Takeaways


� Simpler

Simplify Your Analytic Process via “Causal Clarity”

Find Opportunity

Faster

Unlock More Easily

Clearly defining “Cause and Effect” is the most crucial enabler of

analysis that is


� More Impactful.

� More Efficient Fewer Wasted Steps

Benefit /Cost

Inaugural Event on Practical Analytics“Causal Clarity”

If cause and effect are clear, practical analytics becomes feasible

Key Decisions

Drivers of Results…

Better

Decisions

Optimized by Our

Analysis of Data…

Revenue

Costs

Lead to

Better Results


Costs

Risks

ProfitKey Business

Processes

Better

Processes

Causes Effects

Inaugural Event on Practical AnalyticsCausal Models: A Simple “Base Case”

Each business model has an inherent “causal model,” but the

“core branches” are similar

Revenue

Cost of Revenue Gross Profit

less

Example: Drivers

of Net Profit

Your


Cost of Revenue

Operating Costs

Marketing

Overhead

Other

Gross Profit

Other Costs

Net Profitless

Your Business Model

Has

Inaugural Event on Practical AnalyticsThe “Point of Opportunity” Concept Illustrated

Your Business Model

Has “Causal Model”

(aka Drivers)A Point of

Opportunity

Creating


(aka Drivers)Opportunity

Returning to the causal model above on the previous slide,

let’s find a concrete point of opportunity

Inaugural Event on Practical AnalyticsA Point of Opportunity

Here is an opportunity to enhance ROI on Marketing + Sales efforts:

Price per TxnTransactions

per Client

Point of Opportunity: “Efficiency of New Client Acquisition”

Key Driver / KPI: Acquisition Cost per New Client

Formula: [spending on new client marketing]/[# New Clients)


Volume

Price per Txn

Sales and

Marketing

per Client

# of Clients

X

Inaugural Event on Practical AnalyticsThe 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 � Products / services � Aka “drivers tree”Inputs

3 Things

To

Define:


� 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

Inputs

To

Use:


1. Quick Intro







6. Key Takeaways

Inaugural Event on Practical AnalyticsBackground: Types of Questions Analytics May Answer

We are about to get practical, let’s keep the following in mind…

Past Present Future

Information

What happened? What is happening

now?

What will happen?


Source: Tom Davenport , et al. Analytics at Work: Smarter Decisions, Better Results (Harvard Business School Press, 2010)

(Reporting) (Alerts) (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)

Inaugural Event on Practical AnalyticsOne More Framework: Value vs. Volume

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

Value

Eco

no

mic

Im

pa

ct

of

Ea

ch D

eci

sio

n

Medium-Value, Medium-Volume

Decisions


Source: Neil Raden and James Taylor. Smart Enough Systems (Prentice Hall 2007).

High VolumeLow Volume Decision Volume

Low

Value

Eco

no

mic

Im

pa

ct

of

Ea

ch D

eci

sio

n

Decisions

Example: Product development and

pricing, customer segmentation,

targeting

Low-Value, High-Volume Decisions

Example: Loan approval, customer

cross-sell offer, customer request for

credit-line increase. Direct Marketing.

Inaugural Event on Practical AnalyticsFinancial Services Business Models

To get practical, let’s establish causal clarity for several key business

models in Financial Services

Business ModelCore Products /

Services

Key Drivers

(illustrative)

1. Retail Financial

Services

� Deposit Products

� Loan Products

� Investment Products

� Customer acquisition,

retention, and profitability

� Product pricing

� Share of wallet


� Share of wallet

2. Commercial /

Business Banking /

Financial Svcs

� Debt Financing

� Institutional Financial Svcs

(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. Investment

Banking

� Underwriting

� M & A

� Other advisory services

� Deal flow

� Deal completion rates

� Fee structure

Inaugural Event on Practical Analytics1. Retail Financial Services

Point of

Opportunity:Increase ROI on Marketing Spend

BY 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

Illustrative Example


* P = Profit per year per customer, n=number of years the customer stays

Volume

Profit per

ProductProducts per

Client

# of Clients

XAllocation of

Marketing $

*2nd Order Causality + Pt of Opportunity

Inaugural Event on Practical Analytics2. Commercial/Business Banking / FS

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]

Customer



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

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

Inaugural Event on Practical Analytics3. Trading

Point of

Opportunity:Maximize Alpha!

Key Driver / KPI: Risk-Adjusted Return

Formula: Alpha

Volume: #



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 Positives

3. How well do models

adjust to changed

world?

Inaugural Event on Practical Analytics4. Investment Banking

Point of

Opportunity:Increase Profit per Employee

Key Driver / KPI: Return on Human Capital (“HCROI”)

Formula: [NET Profit] / [# Employees]

Staff & Team

Profit per Gross Profit Net



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

Inaugural Event on Practical AnalyticsAnalytic Themes in Financial Services

Before getting into specific methods, here’s a quick tour of key topics

� Risk Management: always important, more now than ever

� Big data / quant frontiers (especially relevant to trading)

� “Recommendation engines,” other predictive models, and their

practical applications

� Process optimization & automation using data, analysis, and “system-

imbedded decision models”


imbedded decision models”

� Customer Experience Analytics: expectations, service levels,

satisfaction, and impact on client loyalty, retention, and profitability

� Marketing Analytics (esp. with the impact of multi-channel marketing)

� Customer Lifetime Value (CLV) analysis and related predictive analysis

� Product pricing analysis: a perennial that just became more crucial w/

new financial regulations, constraints, and customer behaviors

Inaugural Event on Practical AnalyticsAnalytic Methods: Top 5 “Most Promising” in Financial Services

The best methods depend on your business model & “point of

opportunity”, but this list is a good place to start…

“Predictive yet

Practical”

Customer

Method

� “Better odds” of accuracy (decision, offer, risk-assessment)

� You won’t be right all the time, and you don’t have to be

� Allocate resources to your most profitable customers

� Use WITH predictive analytics to INFER WHO WILL be most

Source of Impact

1

2


Operational

Analytics

� Use of analytic insights “in-system” to improve process

efficiency, quality, and automation

� Ranges of use include staffing, workflow enhancement, etc.

5

Customer

Lifetime Value

Price

Optimization

Risk Mgt

� Use WITH predictive analytics to INFER WHO WILL be most

profitable in the future, not just the present.

� Broad category: from deal-level risk to trade counter-party risk

� 2008 to 2011: remarkable changes in “parameters”

2

3

4

� Maximize profit yield per product, per transaction, per dollar

invested…

� By finding the optimal balance of price and feature parameters


Customer

Lifetime Value

Analytic Methods: Trends into the Future

While several “perennial” analytic methods remain essential, the

“mix of opportunity” is changingP

ote

nti

al

Va

lue Predictive

Analytics

Price

Open-Data w/

Proprietary

Risk Mgt


“Old Standby” New / Cutting Edge

Po

ten

tia

l V

alu

e

Price

Optimization

Video /

Image

Text Analytics

Proprietary

Analysis


1. Quick Intro







6. Key Takeaways

Inaugural Event on Practical AnalyticsWhat 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


Business Model � 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

Your Point of Opportunity (Decision or Process)

Translates to

Which drives

Planning Your Analysis

Planning starts with the goal, the “point of opportunity”


Analysis Methods Required to Create this Information

Required Data

Tools, Platforms, Technology, People, and Processes

Which drives

Allowing definition of

And selection of the right

Inaugural Event on Practical AnalyticsHow We Choose Analytic Methods

Selecting the right analytic method is a key success factor. Consider

the logic below…

1. Your Goals


2. Types of Info

you Need

3. Information

Available

Analytic MethodInforms

Note: This is a key topic, yet covering it fully would require more time than we have today.

The Practical Analytics Knowledge Portal will include a “method selection template” that helps select the right analytic method for your specific opportunity


1. Quick Intro







6. Key Takeaways

Inaugural Event on Practical AnalyticsSummary of Key Takeaways

Executives Leadership

1. Begin Your

Business

Model

2. Define +

Agree on

the Causal

Model

3. Identify

Points of

Opp.

4. Define the

info needed

to unlock

the opp.

5. Keep

analysis as

simple as

possible…

For All

Attendees

Tips By

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

Tips By

Role:

Inaugural Event on Practical AnalyticsFYI: Sources of the Methods Shared Today

In my quest to “Bridge the Gap” between business results & technical

solutions, I have been “integrating” & applying the ideas of others:

1. Although the methods I shared are my own creation, I feel a huge

debt of gratitude to numerous “idea sources”, innovators, and

subject matter experts who influenced my work

2. My focus has been on:


2. My focus has been on:

a. Applying their ideas in new ways

b. Combining their ideas to solve problems

c. Helping my team apply the ideas to get results

If you find my method helpful, take it and use it too!

Inaugural Event on Practical AnalyticsComplementary Resources You Can Access

After you leave today, you may want more information…

To provide you with ongoing access to relevant knowledge & tools, we are

creating a knowledge portal re “Practical Analytics.”

To signup for access to the portal:


1. Send an Email to [email protected]

2. Text the word “analytics” to 917-846-3759

We hope that today’s event, plus the portal, will help YOU benefit as

much as possible from analytics in your career

analytics in financial services - keynote tdwi and ny tech council - new york 2011

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