what’s the payback on connected decisions?what’s the payback on connected decisions? sharing...

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What’s the payback on Connected Decisions?Sharing data, analytics and intelligence across the customer lifecycle produces better decisions, enhanced profitability and a sustainable competitive advantage.

It makes business sense that sharing intelligence to connect decisions across the customer

lifecycle will produce smarter decisions. And decisions that are better informed have been proven

to enhance performance. But exactly how can decisions be connected, and what is the value that

can be expected?

Historically, lenders have acquired separate decisioning systems to support

individual functions in the credit customer lifecycle. These stand-alone systems

have served them well. Lenders have also sought out insights from additional

sources to help improve the choices they make in managing their operations.

For example, lenders have relied on data from credit bureaus to help them

assess customer risk and opportunity.

While upgrades and enhancements to existing systems will improve their

performance, taking a “silo” approach has its limits. There are efficiency gains

and competitive advantage that can only be obtained by paying attention to

what happens between decisions—for example, between an originations decision and a collections

decision, or an authorization decision and a fraud decision.

This opportunity is not lost on the industry. According to a recent Tower Group survey of consumer

lenders, 80% of respondents believe an “integrated view of customer data” will become increasingly

important in their decision processes in the next two years. Yet very few institutions take a “holistic”

approach to decision making. The problem is not lack of interest—it’s execution. To date, there has

not been a viable solution that makes connected decisions possible across the entire lifecycle.

That’s about to change.

Under FICO’s initiative, Decision Management technology is evolving rapidly from stand-alone

products to a Connected Decisions™ approach that will create greater value. This paper describes

this integrated approach and presents three examples that are representative of the potential ROI

from Connected Decisions.

FICO believes that delivering a Decision Management suite that connects decisions is the

critical “next frontier” where productivity and profits are to be found. Institutions that make the

strategic move to a unified approach to decision management will find a new and distinctive

source of competitive advantage.

Number 9 — November 2008

www.fico.com Make every decision countTM

FICO has built a library of use cases in which sharing data, decisions and analytics across the credit lifecycle produces a significant and measurable bottom-line impact.

www.fico.com page 2

What’s the payback on Connected Decisions?

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The concept of Connected Decisions is all about taking a wide-angle view of the business, to see

problems and spot opportunities early while there is still time to take decisive actions that improve

results. It’s not just about better vision—it’s about making better decisions.

Connected Decisions means taking a customer lifecycle view rather than a functional view. It rec-

ognizes that access to historical information, previous actions, and current policies at one decision

point in the lifecycle can influence decisions at another point. This influence can be negative, when

lack of awareness fails to account for all risk, or positive, when the additional information uncovers

hidden revenue opportunity. The real challenge is to figure out what is required to support a

Connected Decision environment. That is precisely the problem FICO has invested in solving.

Today’s decisioning systems are typically segregated by lifecycle function: marketing, origination,

account management, collections and recovery, and fraud management. As a result, decisions made

in any one function do not take into account the total customer relationship. This includes not only

the customer’s holdings inside and outside the firm, but also the historical information and activity

related to that customer in other lifecycle areas. For example, a high-value customer that by over-

sight misses a payment might receive a harsh collection notice, when only a “collections” perspective

is considered. But when the history of the customer’s good standing from account management is

“connected,” a more courteous treatment is applied.

Of course, a lender would always extend favorable policies to high-value customers. But these are

not manual events. Scenarios like this one are buried in the millions of transaction and policy deci-

sions made each year. So any real solution that delivers Connected Decisions must be woven into

the operations of the Decision Management systems. This means the lifecycle products need to be

designed to work as a suite.

What Are Connected »Decisions?

Decision Management Application Suite

Decision Management ArchitectureCommon Components

Origination CustomerManagement

Collections& Recovery Fraud

Data Model Rules Management Model and Rules Case Management Reporting Repository

FICO is bringing this approach to market through our Decision Management suite. Taking a unified view of decisioning across the credit lifecycle, the Decision Management suite provides linkages between leading solutions for origination, customer management, collections and recovery, and fraud management.

Figure 1: A New Approach to Decision Management

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Enabling Connected Decisions

In order to make Connected Decisions possible and realize tangible value from them, Decision

Management solutions need to be built on a common technology architecture. A service-oriented

architecture ensures flexibility and reuse in order to lower the cost of deployment. It is not,

however, the primary source of added value. The core driver of incremental business benefit is

insights from the entire lifecycle and access to FICO’s market-leading analytics. The unified

architecture will enable higher analytic performance and better decisions by leveraging a set of

shared components, including:

Data Model—• A common data model ensures that data is consistent from one application to

the next, and that data updated anywhere within the suite is available across the suite of applica-

tions. We have designed this data model to improve analytic development by: 1) providing clean,

normalized data; and 2) linking data and decisions from various parts of the lifecycle. An analyst

building an originations model, for example, can better recognize the factors that identify fraud

risk or predict default. Knowing what to include in the model is critical, which is where FICO’s 50

years of experience with Decision Management solutions makes a difference.

Rules Management• —All applications in the Decision Management suite share a common

system of creating and changing business rules. The result is that consistent decisions and policies

can be deployed across the lifecycle and even across offices from a single, centralized system. Our

Decision Management architecture uses the industry-leading FICO™ Blaze Advisor® business rules

management system, which is ranked #1 by Yphise, an independent technology research and

analyst firm, and other third parties.

Model and Rules Repository• —All rules and predictive models are stored in a central repository,

where they can be accessed via any application for any decision across the lifecycle. This feature of

our Decision Management architecture is also based on the FICO Blaze Advisor system.

Case Management• —A unified case management system will make it easier to review and

resolve cases across functions of the customer lifecycle, and to move cases from one area

to another. FICO brings deep expertise to the specific requirements for case management

throughout the customer lifecycle, based on our Decision Management applications.

Reporting• —Shared reporting functionality and formats allows for consistent reporting across

all applications and easier transfer of knowledge from one functional area to another. The critical

factor in reporting is the linking of performance data back to individual decisions. That enables

business managers to track, for example, the impact of originations strategies on collections, and

to follow individual accounts through the lifecycle.

these vital components add value within each functional area while also making it possible to extract the value that lies between different functions.

www.fico.com page 4



Besides enabling Connected Decisions and the resulting business benefits, the Decision

Management suite will also bring a number of operational benefits. By having a single analytic

development, testing and deployment process across the entire lifecycle, operational complexity is

reduced substantially. The common architecture allows rapid deployment and makes implemen-

tation less costly. Upgrading will also be easier, faster and less costly than it has been with stand-

alone solutions. In a service-oriented architecture with shared components, businesses can install

upgrades and add new modules without a “rip-and-replace” approach common in today’s systems.

FICO’s Decision Management architecture includes the strategy design functions, powered by our tools for building models and managing rules, and the deci-sion services layer, which orchestrates execution of the right rules and models to deliver the right decisions and actions to each operational transaction.

Portal

CallingApplication

Identity Mgmt

System Mgmt

. . .

DESIGN TIME EXECUTION TIME CLIENT ENVIRONMENT

Common Browser-Based GUI

Strategy Design

Services Layer

Common Data Model

ModelManagement

AnalyticsDevelopment OLAP/Reporting OLTP

RuleManagement

Simulation &Optimization

Con�guration & Deployment

Rules &

Models

Client Data Store

3rd Party Data

Data Integration Layer

Software ServicesDecision Services

Decision OrchestrationBusiness Process

Mgmt & Monitoring

Case Management

Business Services

Security

Enterprise ServicesPerformanceManagement

Learning

Rules ModelsAdaptiveEngines

Service Invocation

Event Management

Provider Access

Enterprise Service Bus

Figure 2: The FICO Decision Management Architecture

www.fico.com page 5


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How Connected Decisions create value

Connected Decisions can deliver a wide range of business and operational benefits. Before

covering the specific examples, it is helpful to point out some of the areas where Connected

Decisions create value.

Vision:• Improved business visibility and reporting across the entire customer lifecycle.

Segmentation:• Finer categorization of customers leads to better matches between actions

and outcomes.

Lifecycle coordination:• Individual and incremental value-add through connections that

span different types of decisions:

Treatments based on the customer’s total relationship and lifetime value•

Identification of cross-sell and up-sell opportunities, in-stream with customer touchpoints•

Early detection and prevention of customer dissatisfaction mistakes (collections calls, •

blocked authorizations from fraud risk) that can damage relationships

Improved marketing effectiveness—from both an operational perspective and •

acquisition success

Fraud detection; early and often—across the enterprise•

Policy and compliance management:• Consistent management and shared best practices of

policies at all levels: account, customer, location/branch, geography and parent/subsidiary.

Time to market and cycle-times:• Risk avoidance and actions on opportunities in real-time or

batched, as needed; flexible architecture allows for quicker spin-up of new product offerings.

FICO has created numerous scenarios in which interoperability between different Decision

Management applications enables Connected Decisions that produce measurable value. Our

objectives were to:

Quantify the potential return on investment when decision points are connected.•

Illustrate the types of opportunities that are possible by sharing data and analytics between •

functions to produce more effective decisions.

Invite a dialogue with our clients to explore Connected Decisions that have future potential.•

The following three examples demonstrate the value of Connected Decisions in a Decision

Management suite environment.

The Value of Connected »Decisions: Case Studies

www.fico.com page 6



Scenario 1. Cutting First-Party Fraud at the Source

In this example, we examined how integrating originations data with fraud management analytics

improves detection of first-party fraud, in which the fraudster obtains credit under false pretenses

with no intention of repayment. Conventional fraud analytics focus on third-party fraud, looking for

changes in transactional behavior patterns, such as unusual purchase types, amounts or locations

indicative of activity by someone other than the legitimate cardholder. With first-party fraud,

however, the fraudster is the customer, and the behavior may remain typical until the moment

of “bust out,” when the fraudster maximizes spending before disappearing.

Most lenders classify first-party fraud losses within bad debt losses rather than measuring them

separately. Based on case studies with participating banks, FICO found that first-party fraud losses

can be as high as 100 basis points ($0.01 loss/$1.00 revenue) compared to third-party fraud

at 10–12 basis points ($0.001 loss/$1.00 revenue).

By factoring originations data and risk score into transactional fraud scoring once the account is

established, banks will be able to identify and treat first-party fraud. First a model should be

deployed to detect potential first-party fraud at the origination stage.

Second, the identification and investigation of first-party fraud should continue after the account

is active by monitoring the monetary and non-monetary transactions. Our clients experience up

to 50% in the reduction of first-party fraud losses with a first-party fraud detection capability,

combined with supporting services. An analytic model combining origination data with fraud

detection analytics can produce from 15% to 20% reduction in fraud losses. Adding rules strategies

and professional consulting can create further reductions of 25% to 30%.

www.fico.com page 7


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This diagram illustrates how originations data and risk scores are fed into FICO™ Falcon® Fraud Manager. The fraud management system leverages application data and risk score in its analytics. The model utilizes the customer behavior with the monetary transactions to produce a transactional score indicating fraud. Rules on case generation based on fraud score and/or fulfilled decision criteria will generate a case for investigation. Identified first-party fraudster demographic data is fed back into the origination system and factored into future origination decisions.

ORIGINATIONS FRAUD

YES

NOIs Application Approved and

Accepted by customer?

Book Loan to Client Host System and Assign Account #

Send application data (with application ID & acct #)

and Risk ScoresIs pro�le initiated? Initiate and update pro�le

with data and score

Update pro�le with data and score

Does score indicate high probability of

suspect fraud?

Do rule conditions of

transaction & other data ful�ll case creation logic?

Dispositions and Actions stored for future risk segmentation

and fraud modeling

First-Party Fraud Identify Data collected for �le update

YES

Case Generates

Fraud Analyst Investigates for �rst-party fraud

Analyst dispositions case and takes appropriate action

Originations Process

First-Party Fraud Identify Data is updated into Originations Fraud

Check lookup tables

Client Host System Provides Acct #s to

Application IDs New account’s monetary & non-monetary transactions scored leveraging application data/score

YES YES

Figure 3: Pass Originations Data and Risk Scores into FICOTM Falcon® Fraud Manager

www.fico.com page 8


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Financial BenefitsThe chart below shows a sample ROI calculation for a bank with 2 million accounts. Based on an

estimated first-party fraud loss reduction of 20%, the savings from integrating origination data and

fraud analytics are projected at $6 million.

Scenario 2. Identifying Fraud Among Collection Cases

First-party fraud cases usually wind up in collections as unpaid debts, and may not be recognized

initially as fraud. In this example, we looked at the benefits of sharing data between fraud and

collections and recovery applications, specifically automating fraud case creation from collections

and recovery and common case management from fraud to collections and recovery.

In the current environment, creating potential fraud cases for review from collection data requires

either manual intervention or custom integration. Similarly, cases or customers identified as fraud

require manual updating in the collections system or custom integration.

In a Connected Decisions approach, collections and fraud share common data that is critical for both

areas. This data can be used both to improve fraud analytic models and to drive collection strategies,

making the entire operation more efficient while reducing losses. Common case management will

allow collections departments to systematically create potential fraud cases for immediate evalua-

tion and action by fraud analysts, which will in turn drive the appropriate collection workflows.

Institution Profile

Portfolio Size in Accounts 2,000,000

Average Balance—Active Accounts $2,000

Portfolio Size—Active Accounts 1,600,000

Portfolio Value—Active Accounts $3,200,000,000

Third-Party Fraud Loss $4,000,000

First-Party Fraud Loss $30,000,000

Revenue per Active Account $50

Value

Reduced First-Party Fraud Losses by 20% $6 million

Reduced Implementation Costs $50,000 savings by utilizing our Decision Management suite

First Year Total Savings $6.05 million

Estimated Benefits from Interoperable Origination and Fraud

www.fico.com page 9


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Advanced analytics, rules and robust case handling capabilities—combined with cooperation

between fraud and collections departments—are the keys to early detection of threats that may

otherwise be invisible until it’s too late to prevent large losses. In addition, the ability to identify

fraudulent accounts before they are written off as bad debt provides operational efficiencies in the

collections and recovery process.

Institutions that integrate data between fraud and collections and recovery functions stand to realize:

Reduced losses on cards and lines of credit through early detection and suspension of spending.•

Reduced losses on secured loans through early detection and recovery of collateral.•

Reduced collection costs through avoidance of unproductive collection activity.•

This diagram illustrates how the collections and recovery and fraud functions can exchange data to identify fraud cases in the collections and recovery system and initiate appropriate actions. The issuer will be better able to determine which uncollected debts are most likely first-party fraud cases, and can contain losses by freezing card usage or cutting off access to credit. As a result, collection and recovery efforts shift more quickly to the fraud protocol.

COLLECTIONS AND RECOVERY FRAUD

YES

NO

Has contact been made via phone?

Queue Collection Case for Call

Route Collection Case to Skip Trace

Is pro�le initiated? Initiate and update pro�le with data and score

Update pro�le with data and score

Collections rule (based on

score or hotlist) �res. Generates

case.

Fraud score or other

rule generates case. Collections data

supplements investigation.

YES

Model scores high

based on collections score and/or data.

Generates case.

Case Generates

Dispositions and Actions stored for future risk segmentation and fraud modeling

Store data into database

Is account First Payment Default (FPD)?

# Call Attempts >X

Has Mail been Returned?

Con�rmedFraud?

NO

YES

YES

YES

Con�rmed �rst-party fraud abuse.

Move to Collections Fraud Process

Con�rmed Non Fraud. Continue Skip Trace

Suspect Fraud — Continue Skip Trace

NO

Con�rmed �rst-party fraud abuse. End Case.

Con�rmed Non Fraud. End Case

Suspect Fraud— Case still open

Fraud Analyst Investigates and takes appropriate actions/disposition

Updating Collections with Fraud Analysis

Results

Figure 4: Automated Fraud Case Creation in Falcon from FICO® Debt ManagerTM Collections System

www.fico.com page 10


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Financial BenefitsThe chart below shows a sample ROI calculation for a bank with 2 million accounts. Based on an

estimated first-party fraud loss reduction of 10%, the savings from integrating originations data and

fraud analytics are projected at more than $3 million.

Scenario 3. Coordinating Treatment from Customer Management to Collections

Customer management and collections systems work best when they work together. In order to do

this, integration work is required, which is often time-consuming and costly to perform. Frequently,

clients decide to cut corners by including only the most obvious data elements. The net result is an

implementation that misses out on key elements that drive value.

Passing detailed data between customer management and collections systems greatly enhances

the segmentation and decision capabilities. Integration will include those pieces of data that will

help lead to reduced charge-off losses and reduced attrition.

FICO is in the process of updating the bi-directional interface between our FICO® TRIAD® adaptive

control system and FICO® Debt Manager™ solution for collections and recovery, so that the two

systems will act in concert. For example, using Debt Manager, a collector will accept a promise to

pay from a customer. With the integrated system, TRIAD will be “aware” of this promise and therefore

Institution ProfileInstitution Profile

Value

Reduced First-Party Fraud Losses 10% reduction—$3 million(Identification & Treatment)

Reduced Cost of Collections $40,000 Reduced Cost of Collections 1,200 Fewer Charge-Off Accounts @ $33/Account

Reduced Implementation Costs $50,000 savings by utilizing our Decision Management suite

First Year Total Savings $3.1 million

Estimated Benefits from Interoperable Collections and Fraud





24 Month Recovery Rate 12%

Baseline Annual Loss $145,000,000

First-Party Fraud Loss $30,000,000

Cost of Collections /Account Cycle 2–4 $33



insights »

will not recommend inappropriate actions, either on the downside (such as sending additional

collections letters) or on the upside (such as authorizing overlimit transactions).

In the integrated solution, TRIAD adaptive control system will perform the segmentation that drives

appropriate accounts into collections while Debt Manager will manage the day-to-day operations

on those accounts. Debt Manager will keep TRIAD informed of operational activities that may lead

to changes in recommended actions, and the two systems together will feed data into the reporting

subsystem that will keep both portfolio and collections managers informed about the interaction

between the two systems.

Main Customer Management benefits:Allows identification of operational negation by ensuring consistency between the intended •

strategy and operational actions.

Permits assessment of the cost of collection relative to amounts collected, allowing strategy •

improvements to be made.

Allows identification of productive actions being taken in the collections system which are not •

part of strategies, so that strategies can be improved.

Leverages recent customer contact insights for more precise strategy determination•

Increases precision of treatment determination, by using analytic insights and results of cham-•

pion/challenger test outcomes.

Main Collections and Recovery benefits:Increases collector efficiency by queuing only those accounts that need to be worked.•

Reduces losses through more targeted actions, improved segmentation and decisions.•

Helps ensure consistency between strategy as defined and operational execution. •

Allows simplification of how operational process is defined within the collections system.•



insights »

This diagram illustrates how the collections and recovery and customer management functions can exchange data. FICO TRIAD recognizes an account is delin-quent and determines the appropriate treatment; those accounts identified with higher risk are sent to FICO Debt Manager for customer contact. Activity about the contact is captured in Debt Manager and passed back to TRIAD in order to determine the next steps. These next steps could include continuing on with the previously determined treatment or a new treatment based on the activity. TRIAD and Debt Manager actions and costs will be captured in a common reporting database, giving collections and risk managers insight into decisions made on accounts by the two systems.

ACCOUNT MANAGEMENT COLLECTIONS AND RECOVERY

To Debt Manager

(Actions from TRIAD)

ClientMaster�le

Client Bill/Post Process

Client Billing System

TRIADReporting Database

(part of common data model)

Debt Manager stored data for

TRIAD

TRIADDriver

Load TRIADData

TRIADLinkage

TRIAD200C

(nightly bill/post called module)

TRIADReportRecord

Debt ManagerdatabaseTRANSFER

Separate batch jobs run outside the nightly billing and posting routine

TRIADreporting process (several separate

items including tally, �le transfer and extract/transform/load DB)

Debt Manager creates output in a �le that is then sent to TRIAD for nightly processing. The �le contains “manual handling status” which is used in TRIAD triggering and segmentation to keep TRIAD from processing accounts in the middle of important collections actions (such as promise to pay in e�ect).

TRIAD processes the data sent to it from the client’s system and creates a �le known as the TRIAD instruction �le. That �le is processed by Debt Manager updating a number of Debt Manager �elds which are used by core Debt Manager processes such as Routers and Multiple Account Rerouting (MARR) to progress accounts through strategies and work�ows.

To TRIAD (indicator of

Debt Manager status)

Write TRIADdata to �le

Debt Manager Feedback

process

Debt Manager Strategy

Execution

CaseManagement

Same database as above. Shown here for

reporting purposes.

TRANSFER

Reports (seen through reporting

tool in UI)

Reports (seen through reporting

tool in UI)

TRIAD and Debt Manager actions and costs will be contained in reporting database so managers can see the interaction of the two systems

Action/Result Tracking

Cost of Collection

Interaction with collectors

Debt Managerdatabase

(part of common data model)

Figure 5: Connecting FICO® TRIAD® Adaptive Control System and FICO® Debt ManagerTM Solutions



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Financial BenefitsThe charts below estimate the benefits of integrating the TRIAD system and the Debt Manager

solution, for a client with 2 million accounts. Based on this profile, the first year benefits would be an

additional $1.6 million on top of the $7.1 million in reduced charge-offs.

As shown, the client would receive value from each individual product, but the integration of the

two products yields even greater value. For example, clients implementing Debt Manager frequently

reduce their charge-offs by 5%, driven mainly by more efficient and timely collections activity and

management of their collections queues. By the same token, clients implementing TRIAD frequently

reduce their charge-offs by 2%, primarily by improved segmentation targeting high-risk customers

for early collections treatment. By integrating the two products, clients could gain an additional half a

percent reduction in charge-offs, since segmentation achieved within TRIAD will be improved through

the knowledge of Debt Manager’s operational actions that are captured and passed into TRIAD.

Institution ProfileInstitution Profile

Value FICO® Debt ManagerTM Only

Interoperable Debt Manager and TRIAD

Potential Benefit of Total DebtManager & TRIAD Solution*

FICO® TRIAD® Adaptive Control System Only

Reduced 5% reduction in 2% reduction in .5% additional reduction Charge-off Charge-offs—$7.1 million Charge-offs—$2.9 million for both Debt Manager $8.7 million Losses and TRIAD—$1.56 million

Reduced Implementation costs Implementation costs $45k savings by Implementation between and Collections between Account utilizing our Decision $45k Costs and Account Management Management and any Management suite Solution—$90k Collections Solution—$90k Reduced NA 5% reduction in 1% additional reduction $384k Attrition attrition—$320k in attrition—$64k

First Year Total $7.1 million $3.1 million $1.6 million $9.1 million* Savings





24 Month Recovery Rate 12%

Baseline Annual Loss $145,000,000

Attrition Rate 8%

Revenue per Active Account $50

* Potential Benefit of Total Debt Manager and TRIAD Solution represents the minimum amount of total benefit gained by implementing an interoperable Debt Manager and TRIAD system. The $8.7 million total for reduced charge-off losses is based on the $7.1 million gained via Debt Manager installation plus the $1.56 million gained in additional reduction in charge-offs as a result of the interoperable system. Benefits may be even greater in this aspect, as suggested by the $2.9 million in savings from the TRIAD-only solution. However, since there is some overlap in benefits gained as a result of each individual system, it is incorrect to as-sume that total benefits are the sum of the Debt Manager-only, TRIAD-only, and Interoperable Debt Manager and TRIAD amounts.

The Insights white paper series provides briefings on research findings and product development directions from FICO. To subscribe, go to www.fico.com/insights.


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For more information US toll-free International email web +1 888 342 6336 +44 (0) 207 940 8718 [email protected] www.fico.com

Reduced implementation costs of the integrated solution come as the result of the Decision

Management Suite’s common infrastructure.

Similar to the improvement in charge-off losses, reduced attrition via the integrated solution

is achieved by additional information passed by Debt Manager into TRIAD enabling better

identification of low-risk customers.

Realizing the Vision

FICO’s Decision Management suite strategy leverages decades of intellectual property and has been

validated with many of our clients. These capabilities are already being recognized in the

marketplace as the next frontier to improving business results.

The concept of Connected Decisions has been rigorously examined and found to deliver measur-

able ROI in a number of areas. Because the architecture is flexible, both FICO and its clients can add

new Connected Decisions at any time. And, since the Decision Management suite can be deployed

one application at a time, benefits compound with each additional product.

Development of the Decision Management suite has been carefully designed and the entire

blueprint has been defined. The products are road-mapped for sequential release, with many

components already in place. As each product is deployed for a client, it will plug into the Decision

Management suite, adding value provided by Connected Decisions and efficiencies of operation.

The applications that support the examples are targeted for release beginning in the spring of 2009

and running through the summer of 2010.

To learn more about FICO’s Decision Management suite and opportunities for Connected Decisions, contact us at +1 888 342 6336 or [email protected].

Fair Isaac, FICO, Connected Decisions, Blaze Advisor, Falcon, TRIAD, Debt Manager and “Make every decision count” are trademarks or registered trademarks of Fair Isaac Corporation in the United States and in other countries. Other product and company names herein may be trademarks of their respective owners. © 2009 Fair Isaac Corporation. All rights reserved.2504WP 05/09 PDF

Product roadmaps and similar marketing materials should be considered forward looking and subject to future change at FICO’s discretion. Future functionality, features or enhancements as shown are FICO’s current projections of the product direction, but are not specific commitments or obligations.

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