The material in this presentation is the property of Fair Isaac Corporation, is provided for the recipient only, and shall not be used, reproduced, or disclosed without Fair Isaac Corporation's express consent.© 2009 Fair Isaac Corporation. 1
The Value of Connected Decisions
David Lightfoot Vice PresidentFair Isaac
David ParisAssociate PartnerIBM
© 2009 Fair Isaac Corporation.2
Top 10 Business Drivers, Strategic Responses, and Technology Initiatives in Retail Banking (2009)
Business Drivers1. Current economic
environment2. Regulatory
change and compliance
3. Competitive threats
4. Changing customer preferences
5. Revenue growth
6. Operational efficiency 7. Business growth/ contraction
8. Customer loss/ dissatisfaction
9. Fraud and financial crime
10. Information security
Strategic Responses
Developing short/long- term strategies to mitigate losses
Increased oversight to ensure compliance
Targeted pricing and product initiatives
Focused investments/ disinvestments in delivery channels
Improving customer acquisition, retention, cross-sales capability
Company-wide cost reduction initiatives; rightsourcing
Identifying and exploiting new market opportunities
Capital preservation Increased cooperation with other banks and third parties
Tighter controls and increased audits of data access
Technology Initiatives
Upgrade loan processing- modification/ collections/foreclosure processing
Modify systems; deploy new processes for compliance
Improve analytics and performance management
Support new product and channel initiatives, divestitures
Enable a single customer view; improve customer analytics
Automate/streamline processes; employ software as a service (SaaS); outsource; consolidate systems
Implement core systems renewal, service-oriented architecture (SOA) capabilities
Automate problem tracking and resolution
Support improved fraud detection and risk analysis
Improve data access controls and data tracking; expand use of encryption
Automate/streamline processes; employ software as a service (SaaS); outsource; consolidate systems
Implement core systems renewal, service-oriented architecture (SOA) capabilities
Improve analytics and performance management
Enable a single customer view; improve customer analytics
Support improved fraud detection and risk analysis
Developing short/long- term strategies to mitigate losses
Increased oversight to ensure compliance
Capital preservation
Exhibit #: 57:04R-E2Source: TowerGroup
© 2009 Fair Isaac Corporation.3
What is a “Connected Decision”?
» A decision executed within a specific Decision Management application or lifecycle area, made smarter through leveraging insights and capabilities from another application or lifecycle area, such as» Data» Shared decision logic and scores» Advanced analytic capabilities» Integrated and shared workflows
© 2009 Fair Isaac Corporation.4
9 Ways Connected Decisions Bring Value
1. Enhanced rule management and scoring in Collections………….. $7M
2. Identify First Party Fraud in originations and early in the lifecycle………………………………………………………….. $6M
3. Easily extend the use of external data in collections………………. $4M
4. Identify First Party Fraud among collection cases…………………. $2.4M
5. Improve account management with integration of transaction based scores……………………………………………... $2.3M
6. Improve collections through assessing the impact of operational negation…………………………………………………… $1.6M
7. Improve agency assignment in collections………………………….. $1.1M
8. Improve early account management and cross-sell………………... $827K
9. Improved on-going strategy management…………………………… Priceless
Value*
*1 Year Benefit based on: client portfolio of 2mm accounts with average balance of $2k and industry standard bad debt and interest income rates.
© 2009 Fair Isaac Corporation.5
Decision Management Suite Benefits
Improved results through…
Connected Technology: Drive cost and risk out of technology adoption
Connected Decisions: Making better individual decisions
Connected Strategy Adaptive control and business Management: simulation across lifecycle and portfolios
© 2009 Fair Isaac Corporation.6 © 2008 Fair Isaac Corporation..6
Agenda
» Business Challenges» Value of Connected Technology
» Value of Connected Decisions
» Value of Connected Strategy Management
» Achieving Connected Decisions
© 2009 Fair Isaac Corporation.7 © 2009 Fair Isaac Corporation..7
» Drive Risk and Cost out of Technology Adoption
Connected Technology
© 2009 Fair Isaac Corporation.8
Suite Architecture — High Level
Smarter decisions — across the lifecycle
Marketing Origination CustomerManagement
Collections& Recovery Fraud
Decision Management ArchitectureCommon Components
Decision Management Application Suite
Data Model Model and RulesRepository Case Management ReportingRules Management
© 2009 Fair Isaac Corporation.9
Architecture — High LevelCommon Data Sourcing and Use>> Reduced Data Application & Server Investment Plus Operational Time to Access and Integrate
Marketing Origination CustomerManagement
Collections& Recovery Fraud
Decision Management Application Suite
Standard Data Content & Dimensions
» Client type» Product type» Org unit» Generic
attributes» Probabilities» Wallet size
» Client type » Product type» Org unit » Capacity to
pay» Loan amount» Risk Rating
» Client type » Product types» Org unit » Product
balances » Specific
attributes
» Client type» Product type» Org unit» Product
balance» Capacity to
pay
» Client type» Product type» Org unit
© 2009 Fair Isaac Corporation.10
Suite Architecture — High LevelFunctional Component Re-use>> Minimize Functional Application and Hardware Investment, Plus Simplifies Workflow
Common Architecture Components
Key Business Criteria & Attributes
»Logical & physical
»Common hierarchy, relational and metadata approaches
»Deals with clients, products, organization units and the like
»Applied by client, product, org unit, other attributes
»Relationally- sequenced and routed
»Use-case driven
»Linkage between model used and rules applied
»Common metadata for use consistency
»Rules-based»Control and
routing driven by attribute and relational elements
»Dimensions by client, product, org unit, other attributes
Data Model Model and RulesRepository
Case Management ReportingRules
Management
Marketing Origination CustomerManagement
Collections& Recovery Fraud
© 2009 Fair Isaac Corporation.11
Increase IT Efficiency
» Growth — organic and manage acquisitions» Common functional architecture> easier
to identify ‘gaps’ for ‘plug and play’ capacity remediation/increase
» Efficiencies — agility, speed, and cost management IT strategies» Common hardware and middleware>
greater load balancing flexibility and server capacity optimization
» Speed — faster to market — smaller, more manageable projects» Add business application to common
hardware & middleware platform> simpler implementation and faster ‘into production’ cycle
© 2009 Fair Isaac Corporation.12
Reduce System Ownership Costs
BeforeClient ITCosts
InstallationFees
LicenseFees
Client ITCosts
InstallationFees
LicenseFees
“Internal Costs”Costs
Application Investment
AfterBefore
© 2009 Fair Isaac Corporation.13
Reduce System Ownership Costs and Time to Deployment
Two » Application servers » Application server
software copies» Server administration
costs » Server ‘footprint’ costs
» Data center space» Energy costs
Before ‘Connected Architecture’
Recent Sample Installation of Debt Manager & TRIAD in UKAfter ‘Connected Architecture’One » Application server* » Application server
software copy» Server administrator » Server ‘footprint’
» Data center space» Energy costs
*UNIX accomodating multiple application and operating system loads
Client ITCosts
Client ITCosts
“Internal Costs”
Plus » Reduced ‘one-off’ time to
» Source» Configure» Install
» Uniform architecture >> » Managed
infrastructure ‘hosting’ opportunity
» Managed service ‘hosting’ opportunity
» Reduced data center space & energy use improves ‘green agenda’ compliance
© 2009 Fair Isaac Corporation.14 © 2009 Fair Isaac Corporation..14
» Making Better Individual Decisions
Value of Connected Decisions
© 2009 Fair Isaac Corporation.15
Case Example 1
Certain Client Types Tend to Result in Certain Risk Profiles . . .
Marketing Origination CustomerManagement
Collections& Recovery Fraud
Decision Management Application Suite» Comprehensive Data
Standard Data Content & Dimensions
» Client type» Product type» Org unit» Generic
attributes» Probabilities» Wallet size
» Client type » Product type» Org unit » Capacity to
pay» Loan amount» Risk Rating
» Client type » Product types» Org unit » Product
balances » Specific
attributes
» Client type» Product type» Org unit» Product
balance» Capacity to
pay
» Client type» Product type» Org unit
© 2009 Fair Isaac Corporation.16
Case Example 1
Helping to Determine Average Utilization and Drawdown . . .
Marketing Origination CustomerManagement
Collections& Recovery Fraud
Decision Management Application Suite» Comprehensive Data
»Combining real time with historical information
Standard Data Content & Dimensions
» Client type» Product type» Org unit» Generic
attributes» Probabilities» Wallet size
» Client type » Product type» Org unit » Capacity to
pay» Loan amount» Risk Rating
» Client type » Product types» Org unit » Product
balances » Specific
attributes
» Client type» Product type» Org unit» Product
balance» Capacity to
pay
» Client type» Product type» Org unit
© 2009 Fair Isaac Corporation.17
Case Example 1
Which Could Exceed or Align With Actual Capacity to Re-Pay . . .
Marketing Origination CustomerManagement
Collections& Recovery Fraud
Decision Management Application Suite» Comprehensive Data
»Combining real time with historical information»Shared decision logic and scores
Standard Data Content & Dimensions
» Client type» Product type» Org unit» Generic
attributes» Probabilities» Wallet size
» Client type » Product type» Org unit » Capacity to
pay» Loan amount» Risk Rating
» Client type » Product types» Org unit » Product
balances » Specific
attributes
» Client type» Product type» Org unit» Product
balance» Capacity to
pay
» Client type» Product type» Org unit
© 2009 Fair Isaac Corporation.18
Case Example 1
Leading to Possible Fraud to Avoid or Reduce Repayment . . .
Marketing Origination CustomerManagement
Collections& Recovery Fraud
Decision Management Application Suite» Comprehensive Data
»Combining real time with historical information»Shared decision logic and scores»Integrated and shared workflows
Standard Data Content & Dimensions
» Client type» Product type» Org unit» Generic
attributes» Probabilities» Wallet size
» Client type » Product type» Org unit » Capacity to
pay» Loan amount» Risk Rating
» Client type » Product types» Org unit » Product
balances » Specific
attributes
» Client type» Product type» Org unit» Product
balance» Capacity to
pay
» Client type» Product type» Org unit
© 2009 Fair Isaac Corporation.19
Case Example 1
This Should then be Fed Back to Adjust Marketing by Client Types
Marketing Origination CustomerManagement
Collections& Recovery Fraud
Decision Management Application Suite» Comprehensive Data
»Combining real time with historical information»Shared decision logic and scores»Integrated and shared workflows
»Balancing strategic and operational decisions
Standard Data Content & Dimensions
» Client type» Product type» Org unit» Generic
attributes» Probabilities» Wallet size
» Client type » Product type» Org unit » Capacity to
pay» Loan amount» Risk Rating
» Client type » Product types» Org unit » Product
balances » Specific
attributes
» Client type» Product type» Org unit» Product
balance» Capacity to
pay
» Client type» Product type» Org unit
© 2009 Fair Isaac Corporation.20
Case Example 2: Attacking First Party Fraud
» Losses compared to Third Party fraud?
» How many collections cases really FP Fraud?
» Performance of Detection Solution?.
» 100 BP vs 10-12
» 50% FPF loss reduction
» 10-20%
© 2009 Fair Isaac Corporation.21
First Party Fraud Solution Requirements
» Information across accounts and lifecycle — history and real-time
» Best data, analytics, investigative capabilities — anticipate & combine
» Mitigate risk across the lifecycle — protect relationships and revenue
© 2009 Fair Isaac Corporation.22
The Building Blocks of a Better First Party Fraud Solution
Data
DataData Prediction engine
Multiple transaction scores
Multiple transaction scores Adaptive ModelsAdaptive Models Call Transaction Scoring
Engine from Application Call Transaction Scoring Engine from Application
Integrated Account Treatment
Workflows
Integrated Account Treatment
WorkflowsCommon
data model Common
data modelShared
Policy Logic Shared
Policy Logic
StatusActions
ActionsActions
workflow
Data capture opportunities
Investigation workflows
© 2009 Fair Isaac Corporation.23
Cutting First-Party Fraud at the Source
YES
NO
Is Application Approved and
Accepted by customer?
Book Loan to Client Host System and Assign Account #
Send application data (with application ID & acct #) and Risk
Scores
Is profile initiated?
Initiate and update profile with data and score
Update profile with data and score
Does score indicate high probability of
suspect fraud?
Do rule conditions of transaction &
other data fulfill case creation logic?
Dispositions and Actions stored for
future risk segmentation and
fraud modeling and employee
tracking
First-Party Fraud Identify Data
collected for file update
Case Generates
Fraud Analyst Investigates for first-party
fraud
Analyst dispositions
case and takes
appropriate action
Originations Process
New account’s monetary & non-monetary transactions
scored leveraging application data/score
Originations
Fraud
Client Host System Provides Acct #s to
Application IDs
First-Party Fraud Identify Data is updated into Originations Fraud Check lookup tables
YES
YES
YES
NO
Send application data (with application ID & acct #) and Risk
Scores
Is profile initiated?
Initiate and update profile with data and score
Update profile with data and score
Fraud
YES
Dispositions and Actions stored for
future risk segmentation and
fraud modeling and employee
tracking
First-Party Fraud Identify Data
collected for file update
Originations Process
First-Party FraudIdentify Data is updatedinto Originations FraudCheck lookup tables
First-Party FraudIdentify Data is updatedinto Originations FraudCheck lookup tables
Does score indicate high probability of
suspect fraud?
Do rule conditions of transaction &
other data fulfill case creation logic?
Case Generates
Fraud Analyst Investigates for first-party
fraud
Analyst dispositions
case and takes
appropriate action
New account’s monetary & non-monetary transactions
scored leveraging application data/score
YES
YES
© 2009 Fair Isaac Corporation.24
Identifying Fraud Among Collection Cases
Fraud
Is profile initiated?
Has contact been made via phone?
Is account First
Payment Default (FPD)?
# Call Attempts >X
Has Mail been Returned?
Confirmed Fraud?
Queue Collection
Case for Call
Route Collection
Case to Skip Trace
Confirmed first-party fraud abuse. Move to
Collections Fraud Process
Confirmed Non Fraud. Continue Skip Trace
Suspect Fraud — Continue Skip Trace
Initiate and update profile with data and
score
Update profile with data and
score
Case Generates
Dispositions and Actions stored for future risk segmentation
and fraud modeling
Collections rule (based on score or
hotlist) fires. Generates case.
Fraud score or other rule generates case.
Collections data supplements investigation.
Model scores high based on collections score and/or data. Generates case.
Store data into
database
Confirmed first-party fraud
abuse. End Case.
Confirmed Non Fraud. End Case
Suspect Fraud —
Case still open
Fraud Analyst Investigates and
takes appropriate
actions/disposition
Collections and Recovery
Updating Collections with Fraud
Analysis Results
YESNO
YES
NO
YES
NO
YES
Fraud
Is profile initiated?
# Call Attempts >X
Has Mail been Returned?
Initiate and update profile with data and
score
Update profile with data and
score
YES
NO
YES
Collections rule (based on score or
hotlist) fires. Generates case.
Fraud score or other rule generates case.
Collections data supplements investigation.
Model scores high based on collections score and/or data. Generates case.
Store data into
database
Confirmed Fraud?
Route Collection
Case to Skip Trace
Confirmed first-party fraud abuse. Move to
Collections Fraud Process
Confirmed Non Fraud. Continue Skip Trace
Suspect Fraud —Continue Skip Trace
Case Generates
Dispositions and Actions stored for future risk segmentation
and fraud modeling
Confirmed first-party fraud
abuse. End Case.
Confirmed Non Fraud. End Case
Suspect Fraud —
Case still open
Confirmed first-party fraud
abuse. End Case.
Confirmed Non Fraud. End Case
Suspect Fraud —
Case still open
Fraud Analyst Investigates and
takes appropriate
actions/disposition
Updating Collections with Fraud
Analysis Results
© 2009 Fair Isaac Corporation.25
Quantifying Value of FPF Solution
Value Estimated Benefits *
Reduced First Party Fraud Losses by 20% in Originations and Early Detection through integration of Originations and Transaction Fraud solution
$6 million
Reduced First Party Fraud Losses by an incremental 10% through integration of Collections and Transaction Fraud solution
$2.4 million
First Year Total Savings from both $8.4 million
*Based on: client portfolio of 2mm accounts with average balance of $2k and industry standard bad debt and interest income rates
© 2009 Fair Isaac Corporation.26
Estimated Client Value of Other Connected Decisions
Connected Decisions Expected Year 1 Benefit*
Improve early account management and cross-sell originations through cross-leveraging data and scores in originations and customer management
$827k
Improve customer management decisions with use of a transaction score. $2.3mm
Improve collections through assessing impact of operational negation. $1.6mm
Enhanced rule management and scoring in collections $7.1mm
Improved agency assignment $1.1mm
Easily extend the use of external data in collections $4.1mm
*Based on: client portfolio of 2mm accounts with average balance of $2k and industry standard bad debt and interest income rates
© 2009 Fair Isaac Corporation.27 © 2009 Fair Isaac Corporation..27
» Adaptive Control and Business Simulation Expanded Across Lifecycle and Portfolios
Value of Connected Strategy Management
© 2009 Fair Isaac Corporation.28
Enabling Connected Strategy Management
» Ability to:» Universally manage adaptive control» infer and hypothesize root cause - generate new approaches» Isolate cause and effect across lifecycle» Evaluate future business results» Simulate future results through stress testing
© 2009 Fair Isaac Corporation.29
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone % Response Capstone
% Approval Capstone % Net Response Capstone
Avg. FICO (NR) Capstone
Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
% FPD TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
($) C/O (ann) TRIAD
(#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD Avg. Balance TRIAD
Avg. Line TRIAD Avg. FICO TRIAD
(%) Inactive TRIAD Auth. Approval TRIAD
(#) CLI TRIAD (#) CLD TRIAD
(#) Attrition TRIAD Bankruptcy TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD ($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD (#) RR 2 - 3 DM / TRIAD (#) RR 3 - 4 DM / TRIAD (#) RR 4 -5 DM / TRIAD ($) RR 1 - 2 DM / TRIAD ($) RR 2 - 3 DM / TRIAD ($) RR 3 - 4 DM / TRIAD ($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon Net Fraud Loss Rate Falcon False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated Risk-Adjusted Yield Calculated
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
Holistic Strategy Evaluation
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
% FPD TRIAD
(#) Entry-Rate TRIAD
(2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
($) C/O (ann) TRIAD
(#) C/O (ann) TRIAD
UNDERWRITING METRICS
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
Avg. FICO TRIAD
(%) Inactive TRIAD
Auth. Approval TRIAD
(#) CLI TRIAD
(#) CLD TRIAD
(#) Attrition TRIAD
Bankruptcy TRIAD
(#) Entry-Rate TRIAD
(2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD
($) C/O (ann) TRIAD
CUSTOMER MGT. METRICS
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon
Net Fraud Loss Rate Falcon
False-Positive Rate Falcon
FRAUD METRICS
© 2009 Fair Isaac Corporation.30
Strategy Evaluation Example: Impact of Transaction Fraud Strategy on Sales and Attrition
D M SUITE SOURCE 0 - 3 M OB 4 - 6 M OB 7 - 12 M OB 13 - 24 M OB 25+ M OBValue Value Value Value Value
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
Avg. FICO TRIAD
(%) Inact ive TRIAD
Auth. Ap proval TRIAD
(# ) CLI TRIAD
(# ) CLD TRIAD
(# ) At trit ion TRIAD
Bankrup tcy TRIAD
(#) Entry-Rate TRIAD
(2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD
($) C/O (ann) TRIAD
(# ) RR 1 - 2 DM / TRIAD
(# ) RR 2 - 3 DM / TRIAD
(# ) RR 3 - 4 DM / TRIAD
(# ) RR 4 -5 DM / TRIAD
($ ) RR 1 - 2 DM / TRIAD
($ ) RR 2 - 3 DM / TRIAD
($ ) RR 3 - 4 DM / TRIAD
($ ) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Paym ent DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD
Recovery Rate DM / TRIAD
($ ) Chargeof f Falcon Sales TRIAD
Recovery Falcon
Net Fraud Loss Rate Falcon
False-Posit ive Rate Falcon
CUSTOM ER M GT. M ETRICS
COLLECTIONS M ETRICS
RECOVERY M ETRICS
FRAUD M ETRICS
# ATTRITION TRIAD -10%
$ CHARGE OFF FALCON +0.01%SALES TRIAD +15%
FALSE-POSITIVE RATE FALCON - 0.05%
© 2009 Fair Isaac Corporation.31
The Suite Difference
Before
» Fraud strategies usually not tested in champion/challenger mode
» If done, tests were not set up to isolate the effect of Fraud strategy on non-Fraud metrics from the effect of customer management strategies
After
» Champion/ challenger strategies indicate impact of fraud strategies on sales and attrition
» Fraud strategies chosen based on overall business impact, not just improving fraud detection
© 2009 Fair Isaac Corporation.32
Ability to Project Future Business Results: Impact of Marketing and Originations Strategies on Collections
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone % Response Capstone % Approval Capstone
% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
% FPD TRIAD
(#) Entry-Rate TRIAD
(2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
($) C/O (ann) TRIAD
(#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
Avg. FICO TRIAD
(%) Inactive TRIAD
Auth. Approval TRIAD
(#) CLI TRIAD
(#) CLD TRIAD
(#) Attrition TRIAD
Bankruptcy TRIAD
(#) Entry-Rate TRIAD
(2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD
($) C/O (ann) TRIAD
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
UNDERWRITING METRICS
# MAILED CAPSTONE +5 %% RESPONSE CAPSTONE +5%% APPROVAL CAPSTONE +2%
AVG FICO (NR) CAPSTONE -3ptsAVG U/W SCORE (NR) CAPSTONE -5pts
© 2009 Fair Isaac Corporation.33
Ability to Project Future Business Results: Impact of Marketing and Originations Strategies on CollectionsDM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOB
Value Value Value Value Value
(#) Mailed Capstone % Response Capstone % Approval Capstone
% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD Avg. Balance TRIAD
Avg. Line TRIAD % FPD TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
($) C/O (ann) TRIAD (#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD Avg. Balance TRIAD
Avg. Line TRIAD Avg. FICO TRIAD
(%) Inactive TRIAD Auth. Approval TRIAD
(#) CLI TRIAD (#) CLD TRIAD
(#) Attrition TRIAD Bankruptcy TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD ($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD
(#) RR 2 - 3 DM / TRIAD
(#) RR 3 - 4 DM / TRIAD
(#) RR 4 -5 DM / TRIAD
($) RR 1 - 2 DM / TRIAD
($) RR 2 - 3 DM / TRIAD
($) RR 3 - 4 DM / TRIAD
($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD
Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon Net Fraud Loss Rate Falcon False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated Risk-Adjusted Yield Calculated
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone % Response Capstone % Approval Capstone
% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD Avg. Balance TRIAD
Avg. Line TRIAD % FPD TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
($) C/O (ann) TRIAD (#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD Avg. Balance TRIAD
Avg. Line TRIAD Avg. FICO TRIAD
(%) Inactive TRIAD Auth. Approval TRIAD
(#) CLI TRIAD (#) CLD TRIAD
(#) Attrition TRIAD Bankruptcy TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD ($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD
(#) RR 2 - 3 DM / TRIAD
(#) RR 3 - 4 DM / TRIAD
(#) RR 4 -5 DM / TRIAD
($) RR 1 - 2 DM / TRIAD
($) RR 2 - 3 DM / TRIAD
($) RR 3 - 4 DM / TRIAD
($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD
Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon Net Fraud Loss Rate Falcon False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated Risk-Adjusted Yield Calculated
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone % Response Capstone % Approval Capstone
% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD Avg. Balance TRIAD
Avg. Line TRIAD % FPD TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
($) C/O (ann) TRIAD (#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD Avg. Balance TRIAD
Avg. Line TRIAD
Avg. FICO TRIAD
(%) Inactive TRIAD Auth. Approval TRIAD
(#) CLI TRIAD
(#) CLD TRIAD
(#) Attrition TRIAD Bankruptcy TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD
($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD
(#) RR 2 - 3 DM / TRIAD
(#) RR 3 - 4 DM / TRIAD
(#) RR 4 -5 DM / TRIAD
($) RR 1 - 2 DM / TRIAD
($) RR 2 - 3 DM / TRIAD
($) RR 3 - 4 DM / TRIAD
($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD
Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon Net Fraud Loss Rate Falcon False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated Risk-Adjusted Yield Calculated
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone
% Response Capstone
% Approval Capstone% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
% FPD TRIAD
(#) Entry-Rate TRIAD
(2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
($) C/O (ann) TRIAD
(#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD
Avg. Balance TRIAD
Avg. Line TRIAD
Avg. FICO TRIAD
(%) Inactive TRIAD
Auth. Approval TRIAD
(#) CLI TRIAD
(#) CLD TRIAD
(#) Attrition TRIAD
Bankruptcy TRIAD
(#) Entry-Rate TRIAD
(2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD
($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD
(#) RR 2 - 3 DM / TRIAD
(#) RR 3 - 4 DM / TRIAD
(#) RR 4 -5 DM / TRIAD
($) RR 1 - 2 DM / TRIAD
($) RR 2 - 3 DM / TRIAD
($) RR 3 - 4 DM / TRIAD
($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD
Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon
Net Fraud Loss Rate Falcon
False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated
Risk-Adjusted Yield Calculated
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
» Historical
» + 6 Months
» + 1 Year
» + 2 Years
(#) RR 1 - 2 DM / TRIAD(#) RR 2 - 3 DM / TRIAD(#) RR 3 - 4 DM / TRIAD(#) RR 4 -5 DM / TRIAD($) RR 1 - 2 DM / TRIAD($) RR 2 - 3 DM / TRIAD($) RR 3 - 4 DM / TRIAD($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIADAvg. Payment DM / TRIAD
Flow-Through Rate Calculated
© 2009 Fair Isaac Corporation.34
The Suite Difference
Before
» Champion/ challenger strategies evaluations compared metrics within lifecycle only
» Evaluations take into account historical results only
After
» Champion/ challenger reports indicate impact that changes in one part of lifecycle have on rest
» Future projections provide earlier assessment of potential impact
» Strategies with undesired impacts can be rejected or improved earlier
© 2009 Fair Isaac Corporation.35
One Step Further: Integrated Portfolio Stress Testing
» + 6 Months
» + 1 Year
» + 2 Years
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone % Response Capstone % Approval Capstone
% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD Avg. Balance TRIAD
Avg. Line TRIAD % FPD TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
($) C/O (ann) TRIAD (#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD Avg. Balance TRIAD
Avg. Line TRIAD Avg. FICO TRIAD
(%) Inactive TRIAD Auth. Approval TRIAD
(#) CLI TRIAD (#) CLD TRIAD
(#) Attrition TRIAD Bankruptcy TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD ($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD
(#) RR 2 - 3 DM / TRIAD
(#) RR 3 - 4 DM / TRIAD
(#) RR 4 -5 DM / TRIAD
($) RR 1 - 2 DM / TRIAD
($) RR 2 - 3 DM / TRIAD
($) RR 3 - 4 DM / TRIAD
($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon Net Fraud Loss Rate Falcon False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated Risk-Adjusted Yield Calculated
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone % Response Capstone % Approval Capstone
% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD Avg. Balance TRIAD
Avg. Line TRIAD % FPD TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
($) C/O (ann) TRIAD (#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD Avg. Balance TRIAD
Avg. Line TRIAD
Avg. FICO TRIAD
(%) Inactive TRIAD Auth. Approval TRIAD
(#) CLI TRIAD
(#) CLD TRIAD
(#) Attrition TRIAD Bankruptcy TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD
($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD
(#) RR 2 - 3 DM / TRIAD
(#) RR 3 - 4 DM / TRIAD
(#) RR 4 -5 DM / TRIAD
($) RR 1 - 2 DM / TRIAD
($) RR 2 - 3 DM / TRIAD
($) RR 3 - 4 DM / TRIAD
($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon Net Fraud Loss Rate Falcon False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated Risk-Adjusted Yield Calculated
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
DM SUITE SOURCE 0 - 3 MOB 4 - 6 MOB 7 - 12 MOB 13 - 24 MOB 25+ MOBValue Value Value Value Value
(#) Mailed Capstone % Response Capstone % Approval Capstone
% Net Response Capstone
Avg. FICO (NR) Capstone Avg. U/W Score (NR) Capstone
(#) Accounts TRIAD Avg. Balance TRIAD
Avg. Line TRIAD % FPD TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD (2+) DQ ($) TRIAD
($) C/O (ann) TRIAD (#) C/O (ann) TRIAD
(#) Accounts TRIAD Total Balance TRIAD
Total Credit Line TRIAD Avg. Balance TRIAD
Avg. Line TRIAD
Avg. FICO TRIAD
(%) Inactive TRIAD Auth. Approval TRIAD
(#) CLI TRIAD
(#) CLD TRIAD
(#) Attrition TRIAD Bankruptcy TRIAD
(#) Entry-Rate TRIAD (2+) DQ (#) TRIAD
(2+) DQ ($) TRIAD
(#) C/O (ann) TRIAD
($) C/O (ann) TRIAD
(#) RR 1 - 2 DM / TRIAD
(#) RR 2 - 3 DM / TRIAD
(#) RR 3 - 4 DM / TRIAD
(#) RR 4 -5 DM / TRIAD
($) RR 1 - 2 DM / TRIAD
($) RR 2 - 3 DM / TRIAD
($) RR 3 - 4 DM / TRIAD
($) RR 4 -5 DM / TRIAD
Avg, DQ Balance DM / TRIAD
Avg. Payment DM / TRIAD
Flow-Through Rate Calculated
($) Recovered DM / TRIAD Recovery Rate DM / TRIAD
($) Chargeoff Falcon Sales TRIAD
Recovery Falcon Net Fraud Loss Rate Falcon False-Positive Rate Falcon
Finance Charge Yield Calculated Non-Interest Income Calculated
Loss Rate Calculated Risk-Adjusted Yield Calculated
ORIGINATIONS METRICS
CUSTOMER MGT. METRICS
COLLECTIONS METRICS
RECOVERY METRICS
FRAUD METRICS
PROFITABILITY METRICS
UNDERWRITING METRICS
Finance Charge Yield CalculatedNon-Interest Income Calculated
Loss Rate CalculatedRisk-Adjusted Yield Calculated
Impact of Unemployment + 5%
Finance Charge Yield CalculatedNon-Interest Income Calculated
Loss Rate CalculatedRisk-Adjusted Yield Calculated
Impact of GDP - 10%
© 2009 Fair Isaac Corporation.36
The Suite Difference
Before
» Champion/ challenger strategies evaluations compared metrics within lifecycle only
» Evaluations take into account historical results only
» Evaluations assume similar exogenous conditions
After
» Future projections provide earlier assessment of potential impact
» Stress testing enables comparison of strategies under varying economic conditions
» Stress testing becomes standard practice embedded within your decision management infrastructure
» Strategies with undesired impacts can be improved or rejected earlier
» Worst case scenarios can be avoided or mitigated
© 2009 Fair Isaac Corporation.37 © 2008 Fair Isaac Corporation..37
Agenda
» Business Challenges» Value of Connected Technology
» Value of Connected Decisions
» Value of Connected Strategy Management
» Achieving Connected Decisions
© 2009 Fair Isaac Corporation.38
Forward-Looking Statements
Product roadmaps and similar marketing materials should be considered forward looking and
subject to future change at Fair Isaac’s discretion.
Future functionality, features or enhancements as shown are Fair Isaac’s current projections of the product direction,
but are not specific commitments or obligations.
© 2009 Fair Isaac Corporation.39
Advanced Analytic Capabilities to Leverage TODAY
» Adaptive analytics
» Decision modeling
» Economic modeling / Portfolio stress testing
© 2009 Fair Isaac Corporation.40
Application Releases
2008 2009 2010
FICO Debt Manager™ 7
FICO TRIAD™ 8.4
FICO Falcon™ Fraud Manager 6 – Scoring Server pre-release
FICO Falcon™ Fraud Manager 6
PlacementsPlus 5.6
FICO Debt Manager™ 8
FICO Originations Manager
FICO TRIAD™ Profit Manager 9
»Enhanced rule management & scoring in Collections
»Connect loss mitigation to customer retention
»Spot misaligned decisions across decision points
»Adaptive Analytics
»Reduce first party Fraud Losses through connections to collections
»Improve customer management decisions with transaction scores
»Improve Agency assignment
»Identify fraud among collections cases
»Cut first party fraud at the source
»Collect more while retaining more customers
»Easily extend the use of external data in Collections
© 2009 Fair Isaac Corporation.41
Conclusion
Connected Technology: Drive cost and risk out of technology adoptionConnected Decisions: Making better individual decisions
» Comprehensive data» Shared decision logic and scores» Advanced analytic capabilities» Integrated and shared workflows
Connected Strategy Management:
Adaptive control and business simulation across lifecycle and portfolios» Universal management of adaptive
control strategies» Ability to infer and hypothesize root cause» Ability to isolate cause and effect» Ability to evaluate future business
impact of strategies» Ability to simulate future results through
stress testing
Improved results through…
© 2009 Fair Isaac Corporation.42
Learn More at InterACT
Related Sessions» Optimizing Decisions in Turbulent Times» Take Control of Portfolio Performance through Stress Testing» The Economics of Collections and Recovery» A Practical Approach to Enterprise Fraud Management» Analytic Innovations in Fraud Detection» When Customers Attack: First Party Fraud» Connected Customer Management with Collections» Does “Test and Learn” Determine a Nation’s Credit Health?
Products in Expo» Debt Manager 7.0, Falcon 6.0
Experts at InterACT» Brad Jolson, Jose Tagunicar, Doug Clare, David Lightfoot, David Paris IBM
Discussion Online» decisions.fairisaac.com/interact
© 2009 Fair Isaac Corporation.43
FICO can help you make every decision count»Control risk and fraud»Grow profitably»Empower your customers
www.fico.com
The material in this presentation is the property of Fair Isaac Corporation, is provided for the recipient only, and shall not be used, reproduced, or disclosed without Fair Isaac Corporation's express consent.© 2009 Fair Isaac Corporation. 44
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