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The material in this presentation is the property of Fair Isaac Corporation. This material has been provided for the recipient only, and shall not be used, reproduced, copied, disclosed, transmitted, in whole or in part, without the express consent of Fair Isaac Corporation. © 2007 Fair Isaac Corporation. Confidential.
Payment Cards 2007Credit Bureau Scores vs. Internal Score Solutions
in emerging marketsFIC’s View
Esteban Sossa Credit Bureau Solutions, Senior
Consultant Fair Isaac
June 7th 2007
2© 2007 Fair Isaac Corporation. Confidential. 2Copyright © 2003 Fair Isaac Corporation. All rights reserved.
Agenda
Fair Isaac
Definitions
Credit Scoring
CB Scores
Application and use
FIC’s approach
Challenges during Implementation
Q&A
3© 2007 Fair Isaac Corporation. Confidential.
You are likely to touch Fair Isaac technology when you…
Buy or refinance a home Make online purchases Take out auto insurance
Buy or use a cell phone Submit a medical claimUse a credit/debit cardUse an ATM
File for workers’ comp
4© 2007 Fair Isaac Corporation. Confidential.
We are the proven standard in analytics and decision management
65% world’s credit cards managed by Fair Isaac technology
65% world’s credit cards protected by our fraud solutions
75% U.S. mortgages scored by Fair Isaac
70% of U.S. post charge-off processing performed using Fair Isaac collections system
9 of the top 10 Fortune 500 companies
51 of the top 100 banks in world
9 of the top 10 UK banks
99 of the top 100 U.S. banks
49 of the top 50 U.S. card issuers
22 of 25 top U.S. small business lenders
80% of top U.S. personal lines insurers
8 of top 10 U.S. wireline providers
Top 10 U.S. wireless providers0 50 100PERCENTAGE
AMONG OUR CLIENTS
5© 2007 Fair Isaac Corporation. Confidential.
EDM is about improving decisions in an integrated way across the enterprise.
Operational Systems and
Channels
CRMCRM
SCMSCM
ERPERP
Call CenterCall Center
WebsiteWebsite
EmailEmail
POSPOS
Etc.Etc.
Design:EDM Technology
Deployment:EDM System
Rules / StrategiesPredictive Analytics
Data Access Predictive Analytics
Rules Management
Enterprise Data External Data
Results
Decision
Request for Decision
Analyst Tools
Business User Tools
6© 2007 Fair Isaac Corporation. Confidential. 6Copyright © 2003 Fair Isaac Corporation. All rights reserved.
AgendaFair Isaac
Definitions
Credit Scoring
CB Scores
Application and use
FIC’s approach
Challenges during Implementation
Q&A
7© 2007 Fair Isaac Corporation. Confidential.
What is Credit Scoring?
“Credit scoring predicts the statistical probability that an account will fall into arrears”
ScoreScore
Bad Rate
HighHighLowLow
8© 2007 Fair Isaac Corporation. Confidential.
The Data-driven strategy roadmap:
Benefit • Brings all predictive analytics into a single decision framework
• Assigns the optimal action for each prospect/account given specific business constraints
• Creates micro segments by matrixing 2 or 3 predictive models
• Rank orders prospects on a single dimension
• Establishes broad segments based on customer profile data
HIGH
Multi-ScoreTrade-OffAssessment
Multi-ScoreTrade-OffAssessment
PredictiveModelsor “Scores”
PredictiveModelsor “Scores”
Profiling &SegmentationProfiling &Segmentation
XXXX
X
X
X X
XXX
X
X
XXX X
X
X
XXXXX X
X
X X
X
XX
X
XX
X
X
X
XX
XXXXX X X
X X
X
X X
X
XX
XX X
XX
X
XX X
X
X
X
X
XX
Incremental ProfitImpactover previous
5-20%5-15%0-15%0-10%
DecisionOptimizationDecisionOptimization
9© 2007 Fair Isaac Corporation. Confidential.
The value of Fair Isaac’s Analytic methodologies
Every year, Fair Isaac has helped banks realize an average annual increase of $2.80 profit per individual account.
Fair Isaac have created methodologies that have helped banks increase profits and control risks across key decision areas.
High
Policies
Score-based Strategies
Adaptive Control
Data DrivenDesign
NPV – BasedEvaluation
Optimisation
Rules
Expert Scores
Pooled MF Scores
Custom MF Scores
Integrated MF + CB Scores
TransactionData Scores
Incremental lift and sustainable competitive advantage
Low
Multiple Outcomes
High
Low
Pro
fita
bil
ity
Fair Isaac spent over $80m on Research & Development last year
10© 2007 Fair Isaac Corporation. Confidential.
Credit Bureau Scores
What is it?
11© 2007 Fair Isaac Corporation. Confidential.
What is in a “Typical”Credit Bureau File?
Retail revolving30 day updateRetail revolving30 day update
Enquiryonline update
Enquiryonline update
Court record datadaily/weekly updateCourt record data
daily/weekly update
Bank instalment/revolving30 day updateBank instalment/revolving30 day update
Sales/personal finance30 day updateSales/personal finance30 day update
Cellular30 day update
Cellular30 day update
Utility30 day update
Utility30 day update
Mail order30 day update
Mail order30 day update
12© 2007 Fair Isaac Corporation. Confidential.
HEADER RECORD (IDENTIFYING INFORMATION)I. Wishfor Credit 12 Lost Lane Sam’s Petrol & Oil
805 Main St. Somewhere, 6666 Attendant
Anytown, 9999 Date of Birth 1965-05-26
PUBLIC RECORDS (LEGAL ITEMS)1999-02-14 Judgment 1000
ENQUIRIES (SEARCHES)Date Subscriber Type2001-04-21 GoodBuy EQ2002-05-10 RocketFin EQ
ACCOUNT INFORMATION (PAYMENT PROFILE)
Supplier Date Date Opening Current Account Payment Reported Opened Balance Balance Type Profile
NiceWear 200206 19970110 700 54 I 1 1 2 2 1 0 0 0 0 0 1 0 0 0 0 0 0 2 2 2 1 1 0 0
SuperCall 200207 19990312 223 120 R P 2 1 0 0 0 0 0 0 1 1 2 2 1 1 0 0 0 0 0 0 0 0 0
Best Bank 200207 19930201 7,500 3,520 R 0 0 0 0 0 0 3 2 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
Village Bank 200207 20000214 12,000 7,358 I 0 0 0 0 0 0 1 0 2 1 0 0
1
2
3
4
The Value of CB Scores:Distilling the Predictive Power
680
13© 2007 Fair Isaac Corporation. Confidential.
Multiple Model Approach
Negative information
Default information
Inquiry information
Trade line information
Balance information # of accts with
balance > 0
Negative information
Default information
Inquiry information
Trade line information # of trade lines Payment status
Negative information Months since last
delinquency
Default information # of public records
Inquiry information # of inquiries
What Bureau Data is Available?
Multiple Model Technology
Full Shared Data Partial Positive Data Negative Data Only
14© 2007 Fair Isaac Corporation. Confidential.
Categories of Information
Aspects of the Credit Background Measured
Contribution toPredictive Power
Previous credit performance 35%
Current level of indebtedness 30%
Amount of time credit hasbeen in use
15%
Pursuit of new credit 10%
Types of credit available 10%
15© 2007 Fair Isaac Corporation. Confidential.
Example Scorecard
Characteristics Attributes Points
Number of payment profiles 0 15
1 22
2 30
3 40
4+ 30
Number of enquiries 0 75
1 55
2+ 40
Number of months in file below 12 12
12 to 23 35
24 to 47 60
48+ 75
Number of months since No judgement 75
0 to 5 10
6 to 11 15
12 to 23 25
24+ 49
most recent judgment
16© 2007 Fair Isaac Corporation. Confidential.
Credit Scoring-Versions & Applications:
Prospecting (Marketing)
Application (Risk)
Customer Management (Risk/MK)
Collections
Fraud
17© 2007 Fair Isaac Corporation. Confidential.
CB Scores vs. Internal Solutions
CB scores offer a 360 ° view of the market for the customer.
CB scores avoid distortions by self-segmentation.
Internal solutions represent better the strategy of the organisation.
I. solutions can be a strategic advantage when own database is stronger than the rest of the market.
Fair Isaac view is that they are complementary and both are needed.
18© 2007 Fair Isaac Corporation. Confidential.
Credit Bureau Scores Complement Custom Scores
Application or Behaviour ScoreB
ure
au
S
co
reLow
High
High
Strengthen your decisionChange your
decision
Change yourdecision
19© 2007 Fair Isaac Corporation. Confidential. 19Copyright © 2003 Fair Isaac Corporation. All rights reserved.
AgendaFair Isaac
Definitions
Credit Scoring
CB Scores
Application and use
FIC’s approach
Challenges during Implementation
Q&A
20© 2007 Fair Isaac Corporation. Confidential.
The use of Scoring (Strategic view) risk/return profile of retail credit portfolios
Risk Based Pricing Up or Cross-Selling Campaign Limit Management
portfolio auditing Business issues: Profitability and room for improvement Increase acceptance rates Consider potential new types information to collect Consider alternative score development and management methods Basel II certification process
21© 2007 Fair Isaac Corporation. Confidential.
600
620
640
680
Credit Bureau Scores Rank Consumer Risk
22© 2007 Fair Isaac Corporation. Confidential.
How Does the Solution Work?Summary of Models and Software
Scoring Models Combines worldwide bureau data
experience Tested against multiple datasets
Implementation Software Receives and processes input data Generates characteristics Applies the right model Generates scores Returns scores and reason codes
Documentation Installation instructions Interface specification Global FICO® scores user’s guide
Support Initial training and consultancy Helpdesk Fair Isaac analytics consultancy -
validations Systems integration consultancy
23© 2007 Fair Isaac Corporation. Confidential.
Ongoing Development Path
Global FICO® Score
NowNow
Refine alignment
capabilitiesacross
countries
Demonstrateperformance
in even more
countries
Implement in multiplecountries
Develop,validate
and refinemodels
24© 2007 Fair Isaac Corporation. Confidential.
600
620
640
680
Credit Bureau Scores Rank Consumer Risk
25© 2007 Fair Isaac Corporation. Confidential.
Use Through the Credit Lifecycle
ACCOUNTACQUISITION
ACCOUNTMANAGEMENT
APPLICANTSCREENING
Approve/decline
Setting initial credit limits
Tiered pricing of loans
Solicitation
Cross-sell
Portfolio acquisition
Limit increase/decrease
Authorisations
Collections
Reissue
26© 2007 Fair Isaac Corporation. Confidential.
Aligned across enterprise on: Target customer segments Size of opportunity Appropriate risk Winning sales/service propositions Functional roles
Relevant, personalised experiences: Guide each touchpoint & interaction Excel at ‘moments of truth’ Shape beliefs & attitudes
Targeting right customers: Messages, channels & timing Sales & marketing integration Closed-loop learning
Customer insight: Value Desired experience Propensities/responsiveness Buying process & behavior
Customer Segmentation & GFS
Enterprise Customer Strategy
Customer Experience
Effectiveness
Sales & Marketing
Effectiveness
Customer Data & Analysis
MarketingAnalytics
Continuous Learning &
Improvement
27© 2007 Fair Isaac Corporation. Confidential.
State of the Art Segmentation
ClusterBots
Cluster Analysis
DecisionTree A
B
C
D
E
F
G
Association Rules
[Age] [Beer]
[Shopping Frequency]
Under 30
Normal HighLow
A
BAbove 30
Multi-dimensional unsupervised approach that reveals natural groupings of customers within a collection of data
Supervised tree approach where the end-points of which represent segments or sub-segments
Basic multi-dimensional analysis approach to group logically or naturally related items together and describe common properties
Multi-dimensional supervised approach that groups individuals into clusters based on their similarities, while maximising segment differences
28© 2007 Fair Isaac Corporation. Confidential.
Simplified decision model for contractual repricing optimization
ProfitProfitPricingChange
$ Loss$ Loss
$ Rev$ Rev
Current Balance
BehaviorScore
Current Pricing
Utilization
BureauInfo
AttritionAttrition
BalancesBalances
Good / BadGood / Bad
Can be expanded to include credit line and fee changes
29© 2007 Fair Isaac Corporation. Confidential.
Example Data AttributesCredit Card Portfolio Segmentation Model
Reward programmeCurrent balance, avg
balance, reward preferences, last
redeemed, primary source
DemographicsAge, income, gender, household size, region
BehavioursSeasonality, categories
and bundles, cash withdrawals
Member AttributesOpt-ins, APR, annual fee,
card type, bus vs personal, total limit
ResponsivenessMarketing treatments and
responses
Credit Bureau Score
30© 2007 Fair Isaac Corporation. Confidential. 30Copyright © 2003 Fair Isaac Corporation. All rights reserved.
AgendaFair Isaac
Definitions
Credit Scoring
CB Scores
Application and use
FIC’s approach
Challenges during Implementation
Q&A
31© 2007 Fair Isaac Corporation. Confidential.
Modeling Tools
Typical scoring development pains
ProductionSystem
ProductionData
Other DataSources
ModelingDataset
CreateVariables
BuildModel
ValidateModel
ModelSpec.
CodeModel
CodeVariables
TranslateMetadata
TestModel
Production IT
Modeler
DeployModel
OtherModelers
ETL(IT)
Assorted filesand scripts
Software Tools
Copy
4Deployment
Delays
1
DelaysGetting Data
2Limited
Technology
5 ModelValidity
3Inefficient
Process
32© 2007 Fair Isaac Corporation. Confidential.
Scoring Building Blocks
5020-50% 4250-80% 38
35> 80%No Info 40
< 20%
Scorecard Module
Optional Modules
Data Preparation
Source Management
Sorting
Extraction & Load
Merging & Collation
Cleaning & Transformation
Sampling & Holdouts
Data Analysis
Variable Creation
Variable Binning
Statistical Data Analysis
Probability Table Generation
Correlation & Factors
Graphing & Charting
General Models
Variable Selection
Regression Models
Neural Network Models
Principal Components
Blended Models
Custom Models
Model Validation
Performance Analysis
Explanation Tools
Statistical Results Analysis
Performance Charting
Model Comparison & Selection
Unit Test Tools
Model Deployment
Model Instrumentation
Model Validation Reports
Real-Time Profiling
Runtime Alarming
Java Runtime Generation
XML Export
Interpretable Scorecard
Weights Engineering
Interactive Classing
Variable Selection
Reject Inference
Performance Reporting
33© 2007 Fair Isaac Corporation. Confidential.
Training and data quality are vital Standard techniques
Logistic regression Linear regression Neural network And more…
Advanced techniques Advanced scorecard technology. Auto-Variable creation. Automated “Expert” binning & Interactive Binning. Sample Bias Adjustment: Performance Inference Define Special Values and constrain their contribution. And a whole lot more…
34© 2007 Fair Isaac Corporation. Confidential.
Continuously Improve Business Results
• Runtime diagnostics provide insight into model quality and efficacy
• Results point out where to tune model
• Alerts if model decays over time
• Model easily tuned in Model Builder
Score
Check Data
Quality
MonitorDegradatio
n
Data
Model Scoring
35© 2007 Fair Isaac Corporation. Confidential.
Scoring Lifecycle Management
Continuous Improvement
Works with your applications
Minimize Modeling and Deployment Risk
More Scores from less peopleIntegrated environment from development through deployment
Task Automation and Object Reuse
Runtime model diagnostics and alarms
Access to New Techniques / Innovation
Quick to deploy into Decision Engine and Workflow applications
What you need How you get it
No manual hand-off to IT
Test code before going into production
Regulatory compliant scorecards
Customisable reports and documentation both for development and monitoring
Meet Regulatory Requirements
36© 2007 Fair Isaac Corporation. Confidential.
Some conclusions:
Data-driven strategies can produce real value.
True automation is not possible without proper data management.
Well informed managers produce better decisions, and faster.
Learning curve is softer for everybody in the organisation if lessons supported by measurable facts.
37© 2007 Fair Isaac Corporation. Confidential.
DATA
INFORMATION
INTELLIGENCE
STRATEGY
PROFITS !!!
FIC’s view of Analytics
38© 2007 Fair Isaac Corporation. Confidential.
Creating a new Decision Model across the organisation.
Map the decision model
Re-engineer the decision model
Provide measurable & realistic scenarios (consider business constrains)
Select desired scenario (s)
Implement & execute
Learn from results
Do it again from the beginning
39© 2007 Fair Isaac Corporation. Confidential.
Auditing & Improvement Process:
Decision Modeling
Optimizationand Simulation
Accelerated Learning
Interpretation
Establish mathematical relationships between customer treatment options, their reactions and profitabilityTest efficiently to learn
beyond historical operating regions to further increase future performance
Gain insight into key profit drivers and opportunity pockets through diagnostics and final strategy engineering
Identify optimal strategy scenarios subject to your multiple goals and business constraints as well as your forecasts for the future
40© 2007 Fair Isaac Corporation. Confidential.
The Decisioning roadmap to impact ROI
Analytic Applications
World Class Analytic Skills
InnovationPartnership
Project Support
Create better models
Better understand consumer behavior
Improve business planning
Build & retain distinctive teams with strong analytic and business skills
Adopt standard processes and methodology
Manage emerging regulatory and compliance requirements
Improve productivity
Automate processes, decisioning and reporting
Improve speed to market
Provide analytic capacity to meet peak demand
Outsource routine model development
Leverage third-party for more effective QA & Audit
41© 2007 Fair Isaac Corporation. Confidential.
Fair Isaac focus on helping youmake smarter decisions.
Fair Isaac is the leader in decision management powered by advanced analytics
Our solutions unlock value for people, businesses and industries
The material in this presentation is the property of Fair Isaac Corporation. This material has been provided for the recipient only, and shall not be used, reproduced, copied, disclosed, transmitted, in whole or in part, without the express consent of Fair Isaac Corporation. © 2007 Fair Isaac Corporation. Confidential.
THANK YOU
Esteban Sossa
+44 793 919 5111
+48 602 447 [email protected]